vaccination research paper questions

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed, retracted article.

Search in PubMed
Search in NLM Catalog
Add to Search

COVID-19 mRNA Vaccines: Lessons Learned from the Registrational Trials and Global Vaccination Campaign

Affiliations.

1 Biology and Nutritional Epidemiology, Independent Research, Copper Hill, USA.
2 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, USA.
3 Biostatistics and Epidemiology, Independent Research, Research Triangle Park, USA.
4 Immunology and Public Health Research, Independent Research, Ottawa, CAN.
5 Epidemiology and Biostatistics, Independent Research, Basel, CHE.
6 Data Science, Independent Research, Los Angeles, USA.
7 Cardiology, Epidemiology, and Public Health, McCullough Foundation, Dallas, USA.
8 Cardiology, Epidemiology, and Public Health, Truth for Health Foundation, Tucson, USA.
PMID: 38274635
PMCID: PMC10810638
DOI: 10.7759/cureus.52876

Retraction in

Retraction: COVID-19 mRNA Vaccines: Lessons Learned from the Registrational Trials and Global Vaccination Campaign. Mead MN, Seneff S, Wolfinger R, Rose J, Denhaerynck K, Kirsch S, McCullough PA. Mead MN, et al. Cureus. 2024 Feb 26;16(2):r137. doi: 10.7759/cureus.r137. eCollection 2024 Feb. Cureus. 2024. PMID: 38414517 Free PMC article.

Our understanding of COVID-19 vaccinations and their impact on health and mortality has evolved substantially since the first vaccine rollouts. Published reports from the original randomized phase 3 trials concluded that the COVID-19 mRNA vaccines could greatly reduce COVID-19 symptoms. In the interim, problems with the methods, execution, and reporting of these pivotal trials have emerged. Re-analysis of the Pfizer trial data identified statistically significant increases in serious adverse events (SAEs) in the vaccine group. Numerous SAEs were identified following the Emergency Use Authorization (EUA), including death, cancer, cardiac events, and various autoimmune, hematological, reproductive, and neurological disorders. Furthermore, these products never underwent adequate safety and toxicological testing in accordance with previously established scientific standards. Among the other major topics addressed in this narrative review are the published analyses of serious harms to humans, quality control issues and process-related impurities, mechanisms underlying adverse events (AEs), the immunologic basis for vaccine inefficacy, and concerning mortality trends based on the registrational trial data. The risk-benefit imbalance substantiated by the evidence to date contraindicates further booster injections and suggests that, at a minimum, the mRNA injections should be removed from the childhood immunization program until proper safety and toxicological studies are conducted. Federal agency approval of the COVID-19 mRNA vaccines on a blanket-coverage population-wide basis had no support from an honest assessment of all relevant registrational data and commensurate consideration of risks versus benefits. Given the extensive, well-documented SAEs and unacceptably high harm-to-reward ratio, we urge governments to endorse a global moratorium on the modified mRNA products until all relevant questions pertaining to causality, residual DNA, and aberrant protein production are answered.

Keywords: autoimmune; cardiovascular; covid-19 mrna vaccines; gene therapy products; immunity; mortality; registrational trials; risk-benefit assessment; sars-cov-2 (severe acute respiratory syndrome coronavirus -2); serious adverse events.

PubMed Disclaimer

Conflict of interest statement

Steve Kirsch is the founder of the Vaccine Safety Research Foundation or VSRF (vacsafety.org) but receives no income from this entity

Figure 1. Analysis of Pfizer trial’s weekly…

Figure 1. Analysis of Pfizer trial’s weekly mortality over a 33-week period

This representation of…

Figure 2. Charts illustrating Pfizer trial irregularities…

Figure 2. Charts illustrating Pfizer trial irregularities in reporting of COVID-19 cases and humoral immune…

Figure 3. Cleveland Clinic study showing increasing…

Figure 3. Cleveland Clinic study showing increasing COVID-19 cases with increasing mRNA vaccinations

Cleveland Clinic…

Figure 4. Cleveland Clinic study showing increased…

Figure 4. Cleveland Clinic study showing increased COVID-19 cases for subjects most "up to date"…

Figure 5. VAERS reports of autoimmune disease…

Figure 5. VAERS reports of autoimmune disease per million doses of COVID-19 mRNA (2021-2023) compared…

Figure 6. Factors contributing to COVID-19 mRNA…

Figure 6. Factors contributing to COVID-19 mRNA vaccine inefficacy

COVID-19 vaccines may lose efficacy in…

Figure 7. Myocarditis reports in VAERS Domestic…

Figure 7. Myocarditis reports in VAERS Domestic Data as of September 29, 2023, plotted by…

Figure 8. Registrational trial for Pfizer, projected…

Figure 8. Registrational trial for Pfizer, projected three-year mortality If the six-month Pfizer trial had…

Publication types

Search in MeSH

Related information

Linkout - more resources, full text sources.

Europe PubMed Central
PubMed Central

Miscellaneous

NCI CPTAC Assay Portal
Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Open access
Published: 09 November 2023

To vaccinate or not to vaccinate? The interplay between pro- and against- vaccination reasons

Marta Caserotti 1 ,
Paolo Girardi 2 ,
Roberta Sellaro 1 ,
Enrico Rubaltelli 1 ,
Alessandra Tasso 3 ,
Lorella Lotto 1 &
Teresa Gavaruzzi 4

BMC Public Health volume 23 , Article number: 2207 ( 2023 ) Cite this article

2446 Accesses

1 Altmetric

Metrics details

By mid 2023, European countries reached 75% of vaccine coverage for COVID-19 and although vaccination rates are quite high, many people are still hesitant. A plethora of studies have investigated factors associated with COVID-19 vaccine hesitancy, however, insufficient attention has been paid to the reasons why people get vaccinated against COVID-19. Our work aims to investigate the role of reasons in the decision to get vaccinated against COVID-19 in a representative sample of 1,689 adult Italians (March–April 2021) balanced in terms of age, gender, educational level and area of residence.

Through an online questionnaire, we asked participants to freely report up to three reasons for and against COVID-19 vaccination, and the weight each had in the decision to get vaccinated. We first investigated the role of emotional competence and COVID-19 risk perception in the generation of both reasons using regression models. Next, we studied the role that the different reasons had in the vaccination decision, considering both the intention to vaccinate (using a beta regression model) and the decision made by the participants who already had the opportunity to get vaccinated (using a logistic regression model). Finally, two different classification tree analyses were carried out to characterize profiles with a low or high willingness to get vaccinated or with a low or high probability to accept/book the vaccine.

High emotional competence positively influences the generation of both reasons (ORs > 1.5), whereas high risk perception increases the generation of positive reasons (ORs > 1.4) while decreasing reasons against vaccination (OR = 0.64). As pro-reasons increase, vaccination acceptance increases, while the opposite happens as against-reasons increase (all p < 0.001). One strong reason in favor of vaccines is enough to unbalance the decision toward acceptance of vaccination, even when reasons against it are also present ( p < 0.001). Protection and absence of distrust are the reasons that mostly drive willingness to be vaccinated and acceptance of an offered vaccine.

Conclusions

Knowing the reasons that drive people’s decision about such an important choice can suggest new communication insights to reduce possible negative reactions toward vaccination and people's hesitancy. Results are discussed considering results of other national and international studies.

Peer Review reports

Introduction

By mid 2023 the European Union reached nearly 75% vaccine coverage for the primary vaccine cycle against COVID-19, with countries such as Croatia, Slovakia, and Poland falling short of 60% and others such as France, Portugal, and Italy close to 90% [ 1 ]. Although vaccination rates are, on average, quite high, many people are still hesitant. Vaccine hesitancy indicates the delay or refusal of a vaccine despite availability in vaccine services [ 2 , 3 ] and is a multidimensional construct, resulting from the interaction between individual, social, and community aspects [ 4 ]. In the last two years, a plethora of studies have investigated factors associated with COVID-19 vaccine hesitancy showing, for example, that vaccine hesitancy is higher in women [ 5 , 6 ], in young people [ 5 , 7 , 8 ], in people with low education [ 8 , 9 ], low trust in authorities [ 10 , 11 ], and strong conspiracy beliefs [ 5 , 12 , 13 ]. However, to the best of our knowledge no one has investigated the interplay that pro- and against- vaccination reasons may play in the choice to get vaccinated, namely what happens when a person has both pro- and against-vaccine considerations. Trying to fill this gap in the literature, our work aims to investigate how different reasons and the importance people place on them are likely to influence the decision to get vaccinated against COVID-19.

In line with the vaccine hesitancy continuum defined by SAGE [ 2 ], while extremely pro-vax people are likely to express only reasons pro-vaccination and extremely no-vax people are likely to express only reasons against vaccination, individuals who fall between the two extreme end-points are likely to feel some doubts. This large number of people offer us the unique opportunity to assess which category of reasons (pro- vs. against- vaccination) is more impactful in driving people's vaccination decisions. As it is reasonable to imagine, among the reasons for choosing to get (or not) vaccinated some reasons are more rational, while others are more related to affect. For example, there are people who rationally recognize the importance of vaccines but at the same time are frightened by the side effects. Thus, the decision to get (or not) vaccinated is the result of a complex process, in which costs and benefits are weighed more or less rationally. Indeed, while several studies have pointed out that the decision to vaccinate is due to cognitive rather than emotional processes [ 14 , 15 , 16 , 17 ], others have highlighted the role of affect and risk perception in the vaccination decision [ 18 , 19 , 20 ]. Thus, the intention to accept the vaccine is driven by emotional and affective feelings as much as by cognitive and rational judgments. Particular attention to what people feel and think about vaccine-preventable diseases and vaccination in general is paid in the model developed by the “Measuring Behavioral and Social Drivers of Vaccination” (BeSD), a global group of experts established by the World Health Organization [ 21 ]. This model encompasses two groups of proximal antecedents of vaccination, namely, what people think and feel (e.g., perceived risk, worry, confidence, trust and safety concerns) and social processes (e.g., provider recommendation, social norms and rumors). Antecedents affect vaccination motivation (i.e., vaccination readiness, willingness, intention, hesitancy), which can then be strengthened or weakened by practical issues (such as vaccine availability, convenience and cost but also requirements and incentives), resulting in acceptance, delay or refusal of vaccination (vaccination behavior).

Although some studies have considered whether the cognitive or affective component has greater weight in determining the intention to vaccinate, no one, to the best of our knowledge, has studied the interplay between pro- and against- vaccination reasons, nor the weight these have in the choice to vaccinate. In addition to the drivers already studied in the literature [ 5 , 6 , 7 , 8 , 11 , 12 ], we believe that the focus on this interaction may be relevant to better understand the complex phenomena related to vaccine hesitancy. Few recent studies have attempted to investigate the complexity of vaccination choice by studying the reasons why people choose to get (or not) vaccinated against COVID-19. Fieselmann and colleagues [ 22 ] highlighted that among the reasons that reduce adherence to vaccination are a low perception of its benefits, a low perception of the risk of contracting COVID-19, health concerns, lack of information, distrust of the system, and spiritual or religious reasons. Another study, instead, shed light on the reasons that encourage hesitant people to consider vaccination, such as protecting themselves, their family, friends and community from COVID-19, and being able to return to normal life [ 23 ].

In the present study we asked the participants to spontaneously come up with their own reasons to get (or not) vaccinated, without limiting or influencing them with a set of predefined options to choose from, thus aiming to obtain more genuine answers that may better capture the intuitive aspect of people’s opinions (for a similar reasoning see [ 24 ]). The procedure we used has been implemented by Moore et al. [ 23 ], the only study, as far as we know, that asked for reasons with an open-ended question. Critically, in their study, participants were asked to report only reasons in favor of vaccination (e.g., "What are your reasons for getting the COVID-19 vaccine?"), excluding reasons against. By contrast, we asked participants to freely report up to three reasons in favor and up to three reasons against COVID-19 vaccination and to rate on a 5-point Likert scale their weight in the decision about getting (or not) vaccinated.

From a theoretical point of view, the reasons pro- and against vaccination may be seen within the framework of prospect theory [ 25 , 26 ] which suggests that people evaluate the outcome of a choice based on a reference point, against which losses and gains are determined: the former below this point, the latter above this point. Importantly, especially in this specific context, losses and negative consequences are weighted more than gains and benefits, making us hypothesize that if a person has one reason for and one reason against the vaccine, which are of equal importance, they will more likely lean toward choosing not to vaccinate. Consistently, it is known that negative experiences have a greater impact than neutral or positive ones (i.e., the negativity bias [ 27 ]).

Besides delving into the reasons that may influence the choice to get (or not) vaccinated, it would be interesting to also look at the individual differences that may determine the reporting of pro- and against- vaccination reasons and their valence. In this regard, the literature suggests that risk perception and emotion regulation can both have a great impact in the decision to get vaccinated. For instance, studies conducted during H1N1 influenza have shown that perception of disease-related risk is one of the strongest predictors of vaccine adherence [ 28 , 29 ]. Additional insights have been provided by more recent studies investigating the role of COVID-19 risk perception in the decision to get vaccinated against COVID-19. Viswanath and colleagues [ 30 ] showed that people are more willing to vaccinate themselves and those under their care to the extent to which they feel more vulnerable to COVID-19 and rate the consequences of a possible infection as severe. Such a relationship between COVID-19 risk perception and intention to vaccinate was confirmed by another study using a cross-sectional design, which focused on the early months of the pandemic [ 31 ]. This study also examined how risk perception changed during the pandemic phases and showed that during the lockdown, compared to the pre-lockdown phase, also those who reported some hesitancy were more likely to get vaccinated when they perceived a strong COVID-19 risk.

With regard to emotion regulation, the literature suggests that people react differently to affective stimuli [ 32 ] and that their decisions are influenced by their abilities to regulate emotions [ 33 , 34 ]. Recent works investigating the relationship between hesitancy in pediatric vaccinations and the emotional load associated with vaccinations, have shown that a negative affective reaction is one of the factors leading to lower vaccine uptake [ 35 , 36 ]. Specifically, Gavaruzzi and colleagues [ 36 ] showed that concerns about vaccine safety and extreme views against vaccines are associated with vaccine refusal. Interestingly, they also showed that parents' intrapersonal emotional competences, i.e., their ability to manage, identify, and recognize their own emotions, is critical to vaccine acceptance for their children. Therefore, in our study we measured people's risk perception and emotional competencies to assess their possible role in the production of reasons in favor and against vaccination.

As described in Fig. 1 , the relationship between different domains of interest can be hierarchically structured, using a directed acyclic graph, starting from the risk perception and emotion regulation, to the generation of pro- and against- vaccination reasons and their valence, and finally to the vaccination willingness/adherence. With respect to the mentioned structure, we are interested to investigate the following research hypotheses:

The number and weight associated with reasons pro- and against-vaccination should be influenced by individual differences in the ability to regulate emotions;

The number and weight associated with pro-vaccination reasons should be influenced by individual differences in COVID-19 risk perception;

A higher number of strong (i.e., with high weight) reasons pro- (vs. against-) vaccination should correspond to a more (vs. less) likelihood to accept the vaccination.

Generating an equal number of reasons in favor and against vaccination should lead to a weaker likelihood to accept the vaccination.

Directed Acyclic Graph (DAG) between variables considered in the study (PEC: Short Profile of Emotional Competence scale)

As we conducted the study between March and April 2021, a time when vaccinations were being progressively rolled out, we decided to consider the role of personal reasons on both the intention to get vaccinated (for those who had not yet had the opportunity to get vaccinated) and the choice already made (e.g., vaccine received or booked vs. refused).

Finally, through a non-parametric classification analysis, we will explore how specific pro- and against-vaccination reasons impact the decision to get (or not) vaccinated. Specifically, we will investigate the role that different categories of reasons play in the choice to vaccinate.

Participants

Data collection was commissioned to a survey and market research agency (Demetra Opinions.net), with the aim of securing a representative sample of the adult (+ 18) Italian population, estimated at 49.8 million [ 37 ]. The sample was balanced in terms of age, gender, educational level (middle school or lower, high school, degree or higher), and area of residence (North, Center, South, and Islands). The agency distributed via email the survey link to its panelists, who freely decided whether to participate in the study in exchange for financial compensation. Out of 1,833 participants who started the questionnaire, 77 (4%) were excluded because they did not complete the survey and 16 (0.9%) were excluded since they reported offensive content in open-ended questions. Finally, 124 (6.8%) participants were excluded because of missing information. Thus, the final sample consisted of 1,689 participants. The project was approved by the ethical committee for Psychology Research of the University of Padova (Italy), with protocol number 3911/2020 and informed consent was obtained for all participants.

We developed an ad-hoc questionnaire including a series of open-ended and closed questions (see Additional file 1 : Appendix 2 for the full material). We first investigated the vaccination status of the participants, asking whether they already had received at least the first dose, whether they had booked it or were still ineligible, and finally whether they had refused the vaccination. Those not yet eligible were asked to rate how likely they would be to get vaccinated at the time they responded (0 = Not at all likely , 100 = Extremely likely ). Then, we asked participants to report a maximum of three reasons both in favor of the COVID-19 vaccine and against it (in counterbalanced order) and to rate how much each of the reported reasons weighed in their choice to vaccinate or not, on a 5-point likert scale (1 = Not at all , 5 = Extremely ). Due to the sparsity on the rate and the number of provided reasons we re-coded the provided information into two semi-quantitative variables, one for pro- and one for against- vaccination reasons, as following: missing/invalid reasons, low average rating (answers 1–3 on the Likert scale) and 1–3 reasons, high rating (answers 4–5 points on the Likert scale) and 1 reason, and high average rating (answer 4–5 points on the Likert scale) and 2–3 reasons.

The questionnaire also included the 20-item Short Profile of Emotional Competence scale (S-PEC; [ 38 ]) to measure intra- and inter-personal emotional competences separately. The intra-personal scale (10 items) refers to emotional competences related to oneself and it includes items such as "In my life I never make decisions based on my emotions'' or "I don't always understand why I react in a certain way". The inter-personal scale (10 items) refers to emotional competences related to other people and it includes items such as “If I wanted, I could easily make someone feel uneasy” or “Most of the time, I understand why the people feel the way they do”. All items are answered on a 7-point likert scale (1 = Not at all agree , 7 = Completely agree ). The internal consistency of the S-PEC scale, measured by means of Cronbach’s α, was adequate (α = 0.81). Further, we measured participants' risk perception of COVID-19 by asking them to indicate how scared they felt of the virus, how serious they think the disease is, how likely they think they are to get sick, and how worried they feel about the various mutations [ 10 , 31 ]. We then asked participants to report their age, gender, educational level, their occupation (health workers, white-collar workers, entrepreneurs, other non-health-related contract forms, and the unemployed), whether they already had COVID-19 (No or don't know, Yes asymptomatic, Yes with few symptoms, and Yes with severe symptoms). The questionnaire was pilot tested by 30 participants who filled the questionnaire first then were asked to discuss and comment on the comprehension of the wording of questions and answer options. Two questions were slightly reworded to improve clarity.

Scoring of reasons

In the first instance, a bottom-up process from reasons to categories was followed by reading a sample of both types of reasons, with the aim of constructing initial categorizing patterns. Examples of pro-vaccination reasons include protection of personal and public health, return to normality, and civic duty; while reasons against vaccination include fears for one's health, sociopolitical perplexity, and distrust of science and institutions (see Additional file 1 : Appendix 1). At this stage, response information was added to the categorizations indicating whether the responses were valid or missing/invalid. Specifically, valid responses had both a reason and the respective weight; missing/invalid responses were those where reason, weight or both were missing or with utterly unrelated concepts or meaningless strings or letters. Finally, by applying a top-down process, we constructed macro categories by merging specific conceptually assimilated categories, so as to avoid the dispersion of data into too many ramifications (see Table S 5 ).

Statistical analysis

Descriptive analysis.

All the analyses were performed only on respondents with no missing observations on the variables of interest (1,681, 92%) excluding also a limited number of those with a non-valid set of pro- or against-vaccination reasons (Table S 1 ; 0.9%). The study variables were summarized in frequency tables and figures (frequency for categorical variables, median and Interquartile Range (IQR) for continuous variables). Kruskal–Wallis tests were computed to compare the distribution of continuous variables across the categories of vaccine status. Categorical variables were compared using chi-squared or Fisher's exact test where expected frequencies in any combination were less than 10. Statistical significance was assumed at the 5% level.

COVID-19 Perceived risk—exploratory factor analysis

An Exploratory Factorial Analysis (EFA) was performed on groups of variables related to COVID-19 perceived risk: scare, severity, contagiousness, and the likelihood of mutation. Since the presence of limited support (0–100 scale) and non-normal marginal distribution, the EFA was performed using a weighted least square mean and variance adjusted (WLSMV) estimator. We extracted from the EFA only the first factor, which explained the highest percentage of variance (Table S 2 ; 61%). The estimated loadings were then used to calculate the regression factor scores. The number and the name of items included, their internal consistency (Cronbach’s α), the estimated loadings, and the proportion of deviance explained are reported in Table S 2 .

Propensity score weighting

At the time of data collection (March–April 2021), the vaccine offer was not opened to the entire population. To adjust the estimates of the following regression models for the propensity to receive the vaccine, we estimated a logistic regression model in which the dependent variable was the response to the question about a previous vaccination offer (Yes/No), while all the factors that can influence the vaccine proposal served as independent variables: age-class (young ≤ 25, young adult 26–45, adult 46–65, elderly 66–84), gender (male, female), occupational status (health worker, not at work, not health worker-employer, not health worker-entrepreneur, not health worker-other), educational level (low = middle school or lower, medium = high school, high = degree or higher), key worker status (yes, no, I don’t know), past COVID-19 contagion (no, yes asymptomatic, yes low symptoms, yes severe symptoms), and familiar status (single/in a relation, married/cohabitant, divorced/separated/other). The predicted probability was used to estimate the weights for the following regression models using a framework based on an inverse probability of treatment weighting (IPTW; for further details, see [ 39 ]).

Regression models

Our research questions can be summarized by trying to describe the relationship exploited by the directed acyclic graph in Fig. 1 . The first step regression model aims to assess how S-PEC scores (inter- and intra-personal) and COVID-19 risk perception influenced the reasons pro- and against-vaccination produced by participants while considering the presence of a set of confounders (age-class, gender, occupational status, educational level, key worker status, and familial status).

Since both the pro- and against-vaccination reasons are formed by a categorical variable with 4 levels (missing/invalid, low 1/2/3 reasons, high 1 reason, high 2/3 reasons), we evaluated whether S-PEC and COVID-19 risk perception scores influenced the distribution of pro- and against-vaccination reasons employing two different multinomial regression models including all the previously mentioned variables (S-PEC, COVID-19 risk perception, and confounders). The overall significance of a variable in the model was tested using an analysis of the variance (ANOVA).

The second step in the analyses was taken to investigate whether the generation of pro- and/or against-vaccination reasons affected the willingness to be vaccinated or the vaccine acceptance. Each participant reported their willingness to get vaccinated on a 0–100 scale or, in case a COVID-19 vaccine had been already offered, their vaccination status (done, booked, or refused). For respondents who had not yet been contacted for booking/getting the vaccination, we evaluated whether pro- and/or against vaccination reasons influenced the willingness to be vaccinated by employing a beta regression model in which the respondent variable scale (0–100) was rescaled to be a relative frequency [ 40 ]. The full models included the semi-quantitative pro- and against-vaccination reasons variables and, even if non-statistically significant, all the confounders in order to adjust for age class, gender, educational level, occupational status, familial status, and key worker status. Beta regression coefficients were estimated using a maximum likelihood estimator (MLE). Results were presented in terms of Odds Ratios (ORs) by exponentiating the estimated coefficients and producing a relative 95% Confidence Interval (95% CI).

A further regression analysis was conducted through a logistic regression model to explain which factors influenced vaccine acceptance (done/booked vs. refused) among those who already received the vaccine offers. The full model included the same variables considered in the previous beta regression model, after recoding the variables related to pro- and against-vaccination reasons into a binary form (missing/invalid vs. presence of at least one valid reason) due to low sample size and the sparsity of the response variable. As a consequence, we tested a simplified version of Hypothesis 3, considering the presence (vs. missing/invalid) of pro- or against-vaccination reasons in order to test their influence on the probability of having accepted/booked the vaccination.

Results were reported employing ORs and relative 95% Confidence Interval (95% CI).

Both the beta regression and logistic regression were weighed using an IPTW scheme to take into account the presence of a different probability of a vaccine offer among respondents.

The presence of an interaction between pro- and against-vaccination reasons was tested by means of a likelihood ratio test. The regression models were estimated through the R 4.0 program (R Core Team, 2021), and for the beta regression we employed the betareg package [ 41 ].

Classification tree analysis

Two different classification tree analyses were carried out to characterize profiles with a low or high willingness to get vaccinated (respondents who had not yet been offered a vaccine) or with a low or high probability to accept/book the vaccine (respondents who had already received a vaccine offer).

Although the dependent variables were non-normally distributed (scale 0–100 or binary 0/1), we considered them continuously distributed adopting a splitting criterion based on the analysis of the variance (ANOVA). We tested the inclusion in the model considering the type of pro- or against-vaccination reasons. A tree pruning strategy was adopted to reduce classification tree overfitting considering the overall determination coefficient (R 2 ) as an indicator and fixing that at each classification step in the tree if the R 2 did not increase by 0.5% the tree should be stopped. Classification tree analysis was performed using the rpart package [ 42 ] on R environment [ 43 ].

The main characteristics of the respondents by vaccination status (received, booked, not yet, and refused) were reported in Table 1 . Among respondents, 23.3% were offered the vaccination and, among them, 13.8% refused it (Fig. S 1 ). Among those not yet eligible, willingness to be vaccinated showed a median value of 80 points (average: 68.7). The distribution of gender was almost equal (51% females, 49% male), and the median age was 47 years old (IQR: 34–57 years). Educational level was low in 41% of the sample, while the most represented employment status was not at work (39%) followed by employed (37%), and entrepreneur (9.8%). A quarter (26%) of respondents classified themselves as key workers during the COVID-19 pandemic. The predominance of respondents (63%) were married or living with a partner, while only 9% had had a COVID-19 infection.

COVID-19 risk perception and the S-PEC score (intra- and inter-personal) were categorized into three categories according to empirical tertiles (low:1 st tertile, medium: 2 nd tertile, high: 3 rd tertile). The level of COVID-19 risk perception differed across vaccination status ( p < 0.001). The reasons pro- and against-vaccination have a different distribution according to COVID-19 vaccination status (Table 2 ). The highest frequency of pro-vaccination reasons was reported by those who received the COVID-19 vaccination; conversely the lowest frequency of pro-vaccination reasons was generated by those who refused the vaccine, whereas, intermediate frequencies were shown by people who were not yet offered the vaccination and those who had booked the vaccine, who reported a comparable distribution of the number of pro-vaccination reasons. A reverse pattern was exhibited for against-vaccination reasons, which were generated with the highest percentage by respondents who refused the vaccine (in particular high and multiple reasons). Conversely those who have booked/done the COVID-19 vaccine showed the lowest frequency of reasons against vaccination, while respondents without a vaccine offer reported an intermediate frequency of reasons against vaccination.

The estimated results of the propensity score model for the vaccine offer are shown in Table S 3 . Respondents older than 65 years exhibited a nearly four-fold increase in the probability to be contacted for the vaccination with respect to the reference age-class (≤ 25 years). All non-health employees showed a high drop in the probability of having received the vaccination offer, while the probability increased as the educational level increased. Being a key worker during pandemic resulted in an increased probability of having received the vaccination proposal while no statistical significant influence was observed for the past COVID-19 contagion or for familial status. The distribution of the propensity score by vaccine status obtained by the model is reported in Fig. S 1 , in which it is shown that the distribution is different by vaccine offer, but the two density functions partially overlap. The discriminant power of the propensity score estimated was only discrete (ROC analysis, AUC: 71.8%).

The results of the multinomial regression models which investigated the effect of emotional competences and risk perception on the generation and the predictors of pro- and against-vaccination reasons with respect to missing/invalid level and the reference categories are presented in Table 3 (see also Fig. 1 ). Compared to the reference category (missing/invalid), high values of S-PEC-self were associated with a higher probability to report pro- and against-vaccination reasons (all ORs > 1.5), while high values of S-PEC-others were associated with a mild probability to report multiple pro-vaccination reasons (all ORs > 1.42). A high (vs. low) COVID-19 risk perception increased the frequency of one strong pro-vaccination reason while it had a null or low decremental effect on the frequency of against weak vaccination reasons. Further, medium (vs. low) COVID-19 risk perception only increased the strong pro-vaccination. Compared to the reference age-class (young), adults and elderly showed a higher probability to generate a strong unique pro-vaccination reason (adults vs. young OR: 1.72, 95%CI: 1.07–2.77); elderly vs. young OR: 2.24, 95%CI: 1.26–4.00), while lower probability to generate against vaccination reasons was observed for elderly compared to young respondents (OR: 0.48, 95%CI: 0.26–0.90). Female participants generated fewer strong pro-vaccination reasons (ORs < 0.73), and also fewer multiple weak against-vaccination reasons (OR: 0.68, 95%CI: 0.51–0.91) compared to male participants. Overall, the occupational status did not affect the generation of pro- and against-vaccination reasons (ANOVA test p > 0.05); however an increased frequency of low 1/2/3 against-vaccination reasons emerged among the category “Other—not health workers” compared to the reference group represented by health workers (OR: 2.52, 95%CI:1.09–5.86). Pro-vaccination reasons are more frequent as the educational level becomes higher, while the relation of the educational level with against- vaccination reasons appears weaker and significantly increased only for the presence of multiple weak reasons against vaccination (High vs. Low educational level, OR: 2.10, 95%CI: 1.45–3.03). Not being a key worker is related to a higher frequency of multiple strong both pro- and against vaccination reasons. The familiar status did not seem to be related to the frequency or the strength of the reasons, except for the status of divorced/separate/other that, with respect to the reference category single/in a relation, showed a twofold increase in the frequency of a strong unique against vaccination reason.

Through a beta regression model we investigated the predictors of willingness to be vaccinated for the participants who had not yet received the vaccination offer. As shown in Table 4 , the generation of pro- and against-vaccination reasons strongly influences the willingness to be vaccinated. The predicted probability from the combination of pro- and against-vaccination reasons is shown in Fig. 2 (and Table S 4 ): respondents who did not report any reasons had an average predicted probability above 60%, while the presence of at least one reason against vaccination decreased the willingness to be vaccinated, in particular in the case of strong multiple against vaccination reasons. On the other hand, the presence of at least one pro-vaccination reason strongly increased the probability. In the end, the presence of both strong multiple pro and against vaccination reasons resulted in a high probability of getting the vaccine. Regression models adjusted by propensity score weighting allowed us to comment the influence of potential confounders: males reported an increased willingness to be vaccinated (vs. females; OR: 1.26, 95%CI: 1.11–1.42), and so did those with a high educational level (vs. low; OR: 1.22, 95%CI: 1.04–1.44) while the opposite was true among no key workers (vs. key workers; OR: 0.85, 95%CI: 0.72–0.99).

Predicted willingness to get vaccinated by interaction between pro- and against-vaccination reasons

Finally, with a logistic model we investigated the predictors of vaccine acceptance\booking. As shown in Table 5 , people who accepted or booked the COVID-19 vaccine were more likely to show pro-vaccination reasons and less likely to show against-vaccination reasons. Interestingly, when both kinds of reasons were provided, the probability of getting/booking the vaccine remained nevertheless very high (Fig. 3 ). Compared to the age class [46-65], younger age classes reported a strong reduction in the probability to have accepted/booked the vaccine. Male participants (OR: 1.53, 95%CI: 1.10–2.12) and those with a high educational level (OR: 2.65, 95%CI: 1.60–4.54) showed an increased probability of vaccine acceptance/booking when compared to females and participants with medium educational level, respectively. Being a health worker had a strong and positive influence on the probability of getting/booking the vaccine with respect to those employed as no health workers (OR: 6.61, 95%CI: 2.10–30.9).

Predicted COVID-19 vaccine acceptance/booking probability by interaction between pro- and against-vaccination reasons

Two regression tree models were estimated separately on the willingness to be vaccinated for those who had not yet received the vaccine offer and on the booking/acceptance of the vaccination in case of vaccine offer. Results are shown in Fig. 4 . Considering the willingness to be vaccinated, the presence of distrust in the vaccination was the most discriminant variable; this latter in conjunction with reasons related to protection, herd immunity, and the absence of no clinical trials guided the willingness to be vaccinated. In particular, the combination of the absence of reasons related to distrust and the presence of protection reasons showed the highest values on the intention to get vaccinated (average value = 83 points, 22% of the sample). On the other side, the presence of at least one reason related to distrust without any positive reasons concerning protection, herd immunity, and trust predicted the lowest willingness to be vaccinated (average value = 29 points, 6% of the sample).

Regression tree for the willingness to be vaccinated (left) and for COVID-19 vaccine acceptance/booking (right) by selected type of pro- and against-vaccination reasons

The sense of protection given by the vaccine or the trust in the vaccination was the main reason for vaccination acceptance/booking (average probability = 0.96 and 1.00, 33% and 5% of the sample, respectively). The combination of the absence of protective reasons and the presence of doubts about the lack of clinical studies results in the lowest likelihood of accepting/booking the vaccination (average probability = 0.40, 3% of the sample). The presence of distrust and the belief in herd immunity were the other discriminant reasons with intermediate results in terms of the probability to accept/book the vaccination.

The frequency of each category of pro- and against-vaccination reasons by COVID-19 vaccine status is shown in Table S 5 .

In the present study we aimed to investigate the reasons behind the decision to get (or not) vaccinated against COVID-19 by asking participants to report up to three reasons in favor and three reasons against the COVID-19 vaccination and to indicate the weight these reasons had in their decision. Although some researchers discourage categorization, the sparsity of the responses related to the number of reasons and their weight implies a semi-quantitative solution since a simple variable multiplication between rating and frequency (recoding to zero in case of zero reasons) is not feasible. In this case, this approach was not satisfactory as such coding would not allow differences underlying identical scores to emerge. For example, only 1 strong motivation (rating 5) would be coded in the same way as three motivations with weights 1, 2, and 2. Instead, we decided to categorize the combination of frequency-weight reasons as categorical variables (missing/invalid, low 1/2/3 reasons, high 1 reason, high 2/3 reasons) in which rating and number of reasons are combined into a single variable. This categorization allows us not only to study the weight that different categories have on the decision to get vaccinated but also to overcome the risk of imputing a specific value for missing responses.

As shown in Fig. 1 , analyses were run in two steps. The first step aimed to assess how emotional competences and risk perception impacted the generation of reasons pro- and against-vaccination (Hypotheses 1A and 1B), whereas the second step investigated how different reasons affected the intention to get vaccinated (Hypotheses 2 and 3). The results support the hypotheses that emotional competences and risk perception play a significant role. Regarding emotional competence as measured by the S-PEC, the results show that high intra-personal emotional competence positively influences the production of stronger and more numerous pro-vaccination and against-vaccination reasons (confirming Hypothesis 1A). This result suggests that greater awareness of one's emotions and of what one is feeling promotes higher fluency in the production of reasons about the vaccination. Research has shown that people can be ambivalent about vaccines and hold both positive and negative reasons [ 2 , 44 ]. It is reasonable to assume that, compared to people with low intra-personal emotional competences, those with high intra-personal emotional competences are more likely to have higher awareness of these contrasting attitudes and to embrace them without suppressing one of the two stances. Furthermore, the results showed that only high inter-personal emotional competences influence the generation of multiple strong reasons in favor of vaccination, and this appears to be related to the perception of vaccines as a public good and a tool to protect others. As for risk perception, a moderate to high perception of risk associated with COVID-19 influences the generation of strong pro-vaccination reasons (confirming Hypothesis 1B). These results are in line with the literature showing that a high perception of risk associated with COVID-19 positively influences the decision to get vaccinated [ 30 , 31 , 45 , 46 , 47 ]. In particular, perceiving a medium/high risk leads to generating a high number of reasons strongly in favor of vaccination, while reducing the number and weight of the reasons against the vaccine. The main premise of the psychological literature examining the relationship between risk perception and affect is that one’s behaviors are affected by rapid and intuitive evaluations, either positive or negative, people make while assessing things happening around them [ 48 , 49 ]. Thus, an event is evaluated not only on the basis of objective information, but also on the basis of the experienced feelings. Emotional competence, which is clearly related to affect, also modulates how we perceive and process the emotional component underlying our judgments [ 36 ].

The results also show that, compared with younger people, those over 45 more frequently produce reasons in favor of vaccines while those over 65 produce fewer reasons against vaccination. These results are in line with the fact that younger people are at lower risk of severe consequences than older people [ 50 ], but can also be explained by considering that age was particularly salient during the period of the data collection, as the vaccination campaign was phased out by age groups, starting from the elderly. As for gender, women produced less strong pro-vaccine and weak-against vaccine reasons than men. These results are congruent with the general findings in the literature on vaccine hesitancy showing that females are more hesitant than males [ 5 , 51 , 52 ]. Furthermore, medium and high educational levels favored the production of both pro- and against-vaccination reasons, whereas not being in a relationship or being divorced/separated increased the generation of a strong reason against vaccination. Consistent with previous work [ 53 ], we confirmed that non-health professionals participants or non-key workers categories showed a lower intention to get vaccinated and a higher likelihood of having refused the vaccine compared to health care and key workers.

Once the role of demographics aspects and individual differences on the generation of reasons pro and/or against vaccination had been established, we ran two additional models to assess the role that those reasons have on the decision to accept the vaccination (see Fig. 1 ). More specifically, we tested the hypothesis that a higher number of pro- (vs. against-) vaccination reasons, connoted by a higher weight, corresponded to a stronger (vs. weaker) acceptance of vaccination (Hypothesis 2). Since data collection took place between March and April 2021, when the vaccination campaign had already started in Italy, we developed two different regression models, with the first investigating the willingness to be vaccinated in participants who were not yet offered the vaccine and the second investigating the likelihood of accepting/booking or refusing the vaccine in those who already received the offer. In particular, thanks to the propensity score weighting technique, we managed to reduce the estimates bias, especially for those factors (age, occupational status, and educational level) that influenced the vaccine offer the most [ 54 ]. The results of the two models are very similar, as the intention to get vaccinated and the likelihood of having accepted/booked the vaccine are predicted by the same factors. Specifically, the production of strong positive reasons increases either the intention to get vaccinated or having accepted/booked the vaccination. In contrast, generating strong negative reasons reduces vaccination intention and predicts the refusal of the vaccination. Hypothesis 2 is thus confirmed.

Results on the interactions between reasons, pro- and against-vaccination, and vaccination intention or vaccination choice are particularly worthy of attention. The third hypothesis was derived from the literature on prospect theory [ 25 , 26 ], suggesting that at equal intensity subjective losses are more important in determining a decision than subjective gains. We therefore expected that negative reasons would count more than positive reasons in deciding whether to get vaccinated or to accept the vaccine. However, in contrast to our hypothesis, the results showed that just the generation of a single positive reason with a strong weight was enough to shift behavior and attitude in favor of the vaccination, regardless of the number and weight of negative reasons. In other words, vaccine refusal is predicted by the absence of any positive strong reasons, while when people generate both positive and negative reasons, the positive ones seem to yield a particularly important role when having a strong weight. According to prospect theory, people evaluate their goals depending on the reference point they focus on. During the pandemic, the vaccination offered an opportunity to be safer, reduced the risk of infection, and more generally appeared as the best way to re-open and get back to life as it was before COVID-19. After a year of pandemic characterized by periods of lockdown and some re-opening attempts, people were likely feeling in a state of loss (e.g., the lost freedom to go out and meet with friends and family, the lost freedom of traveling) and were looking forward to whatever chance available to recover and return to their previous lifestyle and habits. Just as those who gamble are willing to do anything to make up for a loss, so probably those who were not entirely certain about the vaccine were more willing to take risks to recover the loss in quality of life. It follows that the pandemic emergency made people forgo some of their doubts about the vaccine when, at the same time, they had reasons to get their shot. In addition, several studies [ 19 , 55 , 56 ] have highlighted the relationship between anticipated regret and vaccination, showing that anticipated regret is associated with an increased likelihood of adhering, or having one's children adhere, to vaccine offerings. Trusting that the vaccine would work, focusing less on its potential side effects, made sense for people who were looking forward to recovering what was perceived (and was indeed) a loss of quality of life and freedom, because they desired to be back doing the things had ever enjoyed doing (e.g., going to restaurants, movies, etc.). This finding is also interesting from a communicative perspective: providing positive reasons that resonate well with people and have therefore a strong weight for them could offset their doubts, yielding to a greater acceptance of COVID-19 vaccination.

Therefore, it is crucial to consider what kind of reasons drive the decision toward or against vaccination. Allowing participants to openly report their reasons pro- or against- vaccination can facilitate a freer exploration of the concerns and reservations of the most hesitant individuals [ 24 ], thus providing valuable insights for shaping future vaccine-related communications. In fact, thanks to the regression tree on vaccination intention, it emerges that positive attitudes toward vaccines are strongly determined by "Protection" and "Community Protection" reasons. The fact that the sense of individual and collective protection is among the principal determinants of the decision with respect to COVID-19 vaccines suggests that in general vaccination is seen as a means of avoiding nefarious clinical consequences. The effect of the sense of communal protection as the reason favoring vaccination and of other-oriented S-PEC in determining the generation of multiple pro-vaccine motivations confirms previous results suggesting that people often are more willing to get vaccinated primarily to protect their loved ones [ 57 , 58 , 59 ], especially when they have a good understanding of how community immunity works [ 60 , 61 ]. However, it is worth mentioning that, at the time the study was conducted (March–April 2021), there was still uncertainty about whether COVID-19 vaccines could provide sterilizing immunity (i.e., could prevent the transmission of the infection) in addition to protecting the individual. To foster people's willingness to get vaccinated, it is crucial from a public health perspective that people understand that even when vaccines do not yield sterilizing immunity, vaccination can still increase protection of others by reducing the circulation of the virus.

The reasons that influenced the willingness to be vaccinated or the vaccination acceptance/booking were generally in line with the existing literature, although they differed depending on whether respondents had already been offered a vaccine or not: among those who did not received a vaccination offer, the main reasons promoting vaccination acceptance were protection against COVID-19 for oneself, one's family, friends, and community [ 23 ], while among the main reasons that reduced vaccination adherence for those who got the vaccine offer we found the lack of clinical trials [ 62 , 63 ], as well as the distrust of institutions and science [ 22 ]. This latter emerged as the most reported negative reason by those who have refused the vaccine and those who have not yet received the vaccine offer. Thus, effective communication aimed at defusing the perception of risk regarding vaccines themselves should focus on enhancing trust in the scientific process and experimental rigor. Indeed, these reasons were deemed as very important not only by those who refused the vaccination, but also by those who had not yet been offered the vaccine, and even by those who held mixed feelings but eventually chose to get vaccinated. While it is unlikely that individuals firmly against vaccination will be persuaded by simple interventions [ 64 ], we should keep in mind that vaccine hesitancy is a dynamic process. As such, reducing hesitancy or enhancing ambivalence, for example through motivational interviewing (e.g., [ 65 , 66 ]), could potentially lead to small shifts towards greater vaccine acceptance.

Our findings are also in line with the results of other international studies that have used a qualitative approach to examine reasons for and against vaccinations. For example, Hamilton and colleagues [ 67 ] employed a qualitative content analysis to extract the main motivations for and concerns about COVID-19 vaccination from medical records obtained by 102 consults in Australia. The study was conducted in June 2021, and revealed that most consults were driven by doubts about the vaccine available and recommended at that time (i.e., ChAdOx1-S, also known as Vaxzevria), followed by need for further information regarding vaccines and vaccination, also considering specific comorbidities. Notwithstanding the peculiarity of the Australian context in which a very low number of COVID-19 infections was observed, the analysis performed by Hamilton et al. [ 67 ] revealed a set of themes that largely overlaps with the reasons identified in our study. Indeed, among the reason to get vaccinated, 5 themes emerged: a) Protection, b) Occupational or facility responsibility or requirement, c) Trust in primary healthcare physician, d) Autonomy, and e) Civic duty, likewise, concerns about vaccination were mainly in terms of: a) Perceived vaccine risks, b) Perceived vaccine performance, c) Uncertainty, d) Autonomy, and e) Fairness in access. An aspect worth noting is that after the consultation, 81% of participants received the vaccination, 19% did not. Consistent results were observed in another study by Purvis and colleagues [ 68 ] conducted in the USA, which focused specifically on “hesitant adopters”, i.e. those who accepted vaccination but showed some level of hesitancy. To note that in this study the focus was on factors influencing the decision to get the COVID-19 vaccine, not on reasons against it. The authors interviewed 49 participants as a follow up of a larger study ( N = 2022) conducted from mid-September 2021 through mid-October 2021, to explore factors that influenced their decision-making process about COVID-19 vaccination [ 68 ]. Two main themes emerged, each with four subthemes: 1) sociocultural context (political, cultural, health professionals, employment, and media environment) and 2) individual and group influences (attitudes and beliefs related to vaccines, family and social networks, free to return to normal, and COVID-19 outcomes).

As for the Italian context, to the best of our knowledge, only one study (i.e., [ 69 ]) attempted to provide a qualitative examination of the concept associated with vaccination in general, through open-ended and closed questions. Notably, this study was conducted a year later than our own study (April–May 2022) and was administered to a non-representative sample of Italians. The authors used a combination of closed and open-ended questions to assess concepts associated with vaccination in general. Consistent with our findings, Boragno et al. reported that participants who had been vaccinated against COVID-19 (92% of the sample) frequently mentioned concepts related to protection and salvation, whereas those who were not vaccinated frequently mentioned mistrust and ambivalence as concepts associated with vaccination [ 69 ].

This study has some limitations. First, COVID-19 perceived risk score was obtained only with respect to the disease and a similar score should be of interest for the COVID-19 vaccine. Second, data were collected during a vaccine offer limited to a well-defined slice of the population and the investigation on the vaccine acceptance/booking has, as a consequence, a limited sample size. Finally, the lack of a longitudinal perspective does not allow us to evaluate how strong the association is between the willingness to get vaccinated, vaccine acceptance and potential changes in risk perception. Thus, we cannot generalize our results beyond the period of data collection and to other countries or health systems. Since the dynamics have now changed, results may not apply to the decision to get a booster shot or not or an annual shot, however it might be interesting to study what motivations are most relevant now. Likewise, it remains to be established whether our results are generalisable to other populations.

Future studies could consider how the interaction between perceived risk associated with the disease and perceived risk associated with the vaccine influences the choice to get the shot. Furthermore, it would be important to explore how we can harness the reasons that most hold back vaccination in a specific communication strategy for the most hesitant people. Moreover, at the time of data collection, the vaccination campaign was still at an early stage, and only a small portion of the population had already received their shot. Therefore, we believe that it might be of particular interest to know more in detail, with a larger sample, what are the reasons that to date, almost 2 years after the release of the vaccine, still make some people reject the vaccine. Only by knowing these reasons will it be possible to develop appropriate vaccination campaigns.

In conclusion, our work examined pro- and against-vaccination reasons and how these, and their interaction, influence the decision to get vaccinated or not. Specifically, high emotional competence and risk perception influence the generation of pro- and against-vaccination reasons and that the presence of a strong pro-vaccination reason shifts intention toward vaccination. We also highlighted the category of reasons that influence intention to vaccinate. That said, given that the discussion about the next doses is still open and that in any case the next pandemic is a matter of when and not if [ 70 ], it is of paramount importance to know the best way to counteract vaccine hesitancy, fostering more effective communication strategies.

Availability of data and materials

Raw data are available on https://osf.io/dpn2q/?view_only=af05427467634411b471af7a8475ffab .

European Centre for Disease Prevention and Control. Cumulative uptake (%) of the primary course among adults (+18) in EU/EEA countries as of 2023–09–07. https://vaccinetracker.ecdc.europa.eu/public/extensions/COVID-19/vaccine-tracker.html#uptake-tab . Accessed 12 Sept 2023.

MacDonald NE. Vaccine hesitancy: Definition, scope and determinants. Vaccine. 2015; https://doi.org/10.1016/j.vaccine.2015.04.036.

Bedford H, Attwell K, Danchin M, Marshall H, Corben P, Leask J. Vaccine hesitancy, refusal and access barriers: the need for clarity in terminology. Vaccine. 2018; https://doi.org/10.1016/j.vaccine.2017.08.004.

Paul KT, Zimmermann BM, Corsico P, Fiske A, Geiger S, Johnson S, Kuiper JM, Lievevrouw E, Marelli L, Prainsack B, Spahl W. Anticipating hopes, fears and expectations towards COVID-19 vaccines: a qualitative interview study in seven European countries. SSM-Qual Res Health. 2022; https://doi.org/10.1016/j.ssmqr.2021.100035.

Murphy J, Vallières F, Bentall RP, Shevlin M, McBride O, Hartman TK, McKay R, Bennett K, Mason L, Gibson-Miller J, Levita L. Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom. Nat Commun. 2021; https://doi.org/10.1038/s41467-020-20226-9.

Soares P, Rocha JV, Moniz M, Gama A, Laires PA, Pedro AR, Dias S, Leite A, Nunes C. Factors associated with COVID-19 vaccine hesitancy. Vaccines. 2021; https://doi.org/10.3390/vaccines9030300.

Fisher KA, Bloomstone SJ, Walder J, Crawford S, Fouayzi H, Mazor KM. Attitudes toward a potential SARS-CoV-2 vaccine: a survey of US adults. Ann Internal Med. 2020; https://doi.org/10.7326/M20-3569.

Robertson E, Reeve KS, Niedzwiedz CL, Moore J, Blake M, Green M, Katikireddi SV, Benzeval MJ. Predictors of COVID-19 vaccine hesitancy in the UK household longitudinal study. Brain Behav Immun. 2021; https://doi.org/10.1016/j.bbi.2021.03.008.

Caserotti M, Gavaruzzi T, Girardi P, Tasso A, Buizza C, Candini V, Zarbo C, Chiarotti F, Brescianini S, Calamandrei G, Starace F. Who is likely to vacillate in their COVID-19 vaccination decision? Free-riding intention and post-positive reluctance. Prev Med. 2022; https://doi.org/10.1016/j.ypmed.2021.106885.

Caserotti M, Girardi P, Tasso A, Rubaltelli E, Lotto L, Gavaruzzi T. Joint analysis of the intention to vaccinate and to use contact tracing app during the COVID-19 pandemic. Sci Rep. 2022; https://doi.org/10.1038/s41598-021-04765-9 .

Pereira B, Fehl AG, Finkelstein SR, Jiga‐Boy GM, Caserotti M. Scarcity in COVID‐19 vaccine supplies reduces perceived vaccination priority and increases vaccine hesitancy. Psychol Mark. 2022; https://doi.org/10.1002/mar.21629 .

Đorđević JM, Mari S, Vdović M, Milošević A. Links between conspiracy beliefs, vaccine knowledge, and trust: Anti-vaccine behavior of Serbian adults. Soc Sci Med. 2021; https://doi.org/10.1016/j.socscimed.2021.113930 .

Candini V, Brescianini S, Chiarotti F, Zarbo C, Zamparini M, Caserotti M, Gavaruzzi T, Girardi P, Lotto L, Tasso A, Starace F. Conspiracy mentality and health-related behaviour during the COVID-19 pandemic: a multi-wave survey in Italy. Public Health. 2023, https://doi.org/10.1016/j.puhe.2022.11.005 .

Asch DA, Baron J, Hershey JC, Kunreuther H, Meszaros J, Ritov I, Spranca M. Omission bias and pertussis vaccination. Medic Decis Mak. 1994; https://doi.org/10.1177/0272989X9401400204 .

Meszaros JR, Asch DA, Baron J, Hershey JC, Kunreuther H, Schwartz-Buzaglo J. Cognitive processes and the decisions of some parents to forego pertussis vaccination for their children. J Clin Epidemiol. 1996; https://doi.org/10.1016/0895-4356(96)00007-8 .

Bell RA, McGlone MS, Dragojevic M. Vicious viruses and vigilant vaccines: Effects of linguistic agency assignment in health policy advocacy. J Health Commun. 2014; https://doi.org/10.1080/10810730.2013.81133 .

Nan X, Madden K. HPV vaccine information in the blogosphere: how positive and negative blogs influence vaccine-related risk perceptions, attitudes, and behavioral intentions. Health Commun. 2012; https://doi.org/10.1080/10410236.2012.661348 .

Christy SM, Winger JG, Raffanello EW, Halpern LF, Danoff-Burg S, Mosher CE. The role of anticipated regret and health beliefs in HPV vaccination intentions among young adults. J Behav Med. 2016; https://doi.org/10.1007/s10865-016-9716-z .

Chapman GB, Coups EJ. Emotions and preventive health behavior: worry, regret, and influenza vaccination. Health Psychol. 2006; https://doi.org/10.1037/0278-6133.25.1.82 .

Klasko-Foster LB, Przybyla S, Orom H, Gage-Bouchard E, Kiviniemi MT. The influence of affect on HPV vaccine decision making in an HPV vaccine naïve college student population. Prev Med Rep. 2020; https://doi.org/10.1016/j.pmedr.2020.101195.

World Health Organization = Organisation mondiale de la Santé. Understanding the behavioural and social drivers of vaccine uptake WHO position paper – May 2022 – Comprendre les facteurs comportementaux et sociaux de l’adoption des vaccins Note de synthèse de l’OMS – mai 2022. Weekly Epidemiological Record = Relevé épidémiologique hebdomadaire, 97 (20), 209 - 224. World Health Organization = Organisation mondiale de la Santé. 2022; https://apps.who.int/iris/handle/10665/354460 .

Fieselmann J, Annac K, Erdsiek F, Yilmaz-Aslan Y, Brzoska P. What are the reasons for refusing a COVID-19 vaccine? A qualitative analysis of social media in Germany. BMC Public Health. 2022; https://doi.org/10.1186/s12889-022-13265-y .

Moore R, Purvis RS, Hallgren E, Willis DE, Hall S, Reece S, CarlLee S, Judkins H, McElfish PA. Motivations to vaccinate among hesitant adopters of the COVID-19 vaccine. J Commun Health. 2022; https://doi.org/10.1007/s10900-021-01037-5 .

Cassels TG, Birch SA. Comparisons of an open-ended vs. forced-choice ‘mind reading’task: Implications for measuring perspective-taking and emotion recognition. PLoS One. 2014; https://doi.org/10.1371/journal.pone.0093653 .

Kahneman D, & Tversky A. On the interpretation of intuitive probability: A reply to Jonathan Cohen. 1979; https://doi.org/10.1016/0010-0277(79)90024-6 .

Tversky A, Kahneman D. Advances in prospect theory: Cumulative representation of uncertainty. J Risk Uncertain. 1992; https://doi.org/10.1007/BF00122574 .

Baumeister RF, Bratslavsky E, Finkenauer C, Vohs KD. Bad is stronger than good. Review of general psychology. 2001; https://doi.org/10.1037/1089-2680.5.4.323 .

Chor JS, Ngai KL, Goggins WB, Wong MC, Wong SY, Lee N, Leung TF, Rainer TH, Griffiths S, Chan PK. Willingness of Hong Kong healthcare workers to accept pre-pandemic influenza vaccination at different WHO alert levels: two questionnaire surveys. BMJ. 2009; https://doi.org/10.1136/bmj.b3391 .

Pareek M, Clark T, Dillon H, Kumar R, Stephenson I. Willingness of healthcare workers to accept voluntary stockpiled H5N1 vaccine in advance of pandemic activity. Vaccine. 2009; https://doi.org/10.1016/j.vaccine.2008.12.006 .

Viswanath K, Bekalu M, Dhawan D, Pinnamaneni R, Lang J, McLoud R. Individual and social determinants of COVID-19 vaccine uptake. BMC Public Health. 2021; https://doi.org/10.1186/s12889-021-10862-1 .

Caserotti M, Girardi P, Rubaltelli E, Tasso A, Lotto L, Gavaruzzi T. Associations of COVID-19 risk perception with vaccine hesitancy over time for Italian residents. Soc Sci Med. 2021; https://doi.org/10.1016/j.socscimed.2021.113688 .

Finucane ML, Peters E, & Slovic P. (2003). Judgment and decision making: The dance of affect and reason. In: S. L. Schneider & J. Shanteau, editors. Emerging Perspectives on Judgment and Decision Research Cambridge. University Press; 2003. 327–364. https://doi.org/10.1017/CBO9780511609978.012 .

Pittarello A, Conte B, Caserotti M, Scrimin S, Rubaltelli E. Emotional intelligence buffers the effect of physiological arousal on dishonesty. Psychonomic Bull Rev. 2018; https://doi.org/10.3758/s13423-017-1285-9 .

Scrimin S, Rubaltelli E. Dehumanization after terrorism: the role of psychophysiological emotion regulation and trait emotional intelligence. Curr Psychol. 2021; https://doi.org/10.1007/s12144‐019‐00189‐x .

Tomljenovic H, Bubic A, Erceg N. It just doesn’t feel right–the relevance of emotions and intuition for parental vaccine conspiracy beliefs and vaccination uptake. Psychol Health. 2020; https://doi.org/10.1080/08870446.2019.1673894 .

Gavaruzzi T, Caserotti M, Leo I, Tasso A, Speri L, Ferro A, Fretti E, Sannino A, Rubaltelli E, Lotto L. The role of emotional competences in parents’ vaccine hesitancy. Vaccines. 2021; https://doi.org/10.3390/vaccines9030298 .

ISTAT. Resident population on 1st January: By age. http://dati.istat.it/?lang=en&SubSessionId=d7024c9e-239b-455d-924b-df19345a27b2 . Accessed Sept 25, 2023.

Mikolajczak M., Brasseur S, & Fantini-Hauwel C. Measuring intrapersonal and interpersonal EQ: The short profile of emotional competence (S-PEC). Pers Individ Differ. 2014; https://doi.org/10.1016/j.paid.2014.01.023 .

Olmos A, Govindasamy P. A practical guide for using propensity score weighting in R. Pract Assess Res Eval. 2015; https://doi.org/10.7275/jjtm-r398 .

Smithson M, Verkuilen J. A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychological methods. 2006; https://doi.org/10.1037/1082-989X.11.1.54 .

Ferrari S, Cribari-Neto F. Beta regression for modelling rates and proportions. Journal of applied statistics. 2004; https://doi.org/10.1080/0266476042000214501 .

Thernau T, Atkinson B, Ripley B. Rpart: Recursive Partitioning. R Package 4.1–0. http://CRAN.R-project.org/package=rpart .

RC Team. R Core Team R: A language and environment for statistical computing. R. . Foundation for Statistical Computing. 2014. https://www.r-project.org .

Freeman D, Loe BS, Chadwick A, Vaccari C, Waite F, Rosebrock L, ... & Lambe S. COVID-19 vaccine hesitancy in the UK: the Oxford coronavirus explanations, attitudes, and narratives survey (Oceans) II. Psychol Med. 2022; https://doi.org/10.1017/S0033291720005188 .

Caserotti M, Gavaruzzi T, Girardi P, Sellaro R, Rubaltelli E, Tasso A, Lotto L. People’s perspectives about COVID-19 vaccination certificate: Findings from a representative Italian sample. Vaccine. 2022; https://doi.org/10.1016/j.vaccine.2022.08.016 .

MacDonald NE, Comeau J, Dubé È, Graham J, Greenwood M, Harmon S, McElhaney J, Meghan McMurtry C, Middleton A, Steenbeek A, Taddio A. Royal society of Canada COVID-19 report: Enhancing COVID-19 vaccine acceptance in Canada. Facets. 2021; https://doi.org/10.1139/facets-2021-0037 .

Schwarzinger M, Watson V, Arwidson P, Alla F, Luchini S. COVID-19 vaccine hesitancy in a representative working-age population in France: a survey experiment based on vaccine characteristics. Lancet Public Health. 2021; https://doi.org/10.1016/S2468-2667(21)00012-8 .

Slovic P, Finucane M, Peters E, MacGregor DG. Rational actors or rational fools: Implications of the affect heuristic for behavioral economics. J Socio-Econ. 2002; https://doi.org/10.1016/S1053-5357(02)00174-9 .

Slovic P, Finucane ML, Peters E, MacGregor DG. Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk and rationality. In The feeling of risk 2013 Mar 7 (pp. 21–36). Routledge.

Bhopal SS, Bagaria J, Olabi B, Bhopal R. Children and young people remain at low risk of COVID-19 mortality. Lancet Child Adolesc Health. 2021; https://doi.org/10.1016/S2352-4642(21)00066-3 .

Lazarus JV, Wyka K, Rauh L, Rabin K, Ratzan S, Gostin LO, Larson HJ, El-Mohandes A. Hesitant or not? The association of age, gender, and education with potential acceptance of a COVID-19 vaccine: a country-level analysis. J Health Commun. 2020; https://doi.org/10.1080/10810730.2020.1868630 .

Seale H, Heywood AE, Leask J, Sheel M, Durrheim DN, Bolsewicz K, Kaur R. Examining Australian public perceptions and behaviors towards a future COVID-19 vaccine. BMC Infect Dis. 2021; https://doi.org/10.1186/s12879-021-05 .

Butter S, McGlinchey E, Berry E, Armour C. Psychological, social, and situational factors associated with COVID‐19 vaccination intentions: A study of UK key workers and non‐key workers. Br J Health Psychol. 2022; https://doi.org/10.1111/bjhp.12530 .

Freedman DA, Berk RA. Weighting regressions by propensity scores. Eval Rev. 2008; https://doi.org/10.1177/0193841X08317586 .

Lagoe C, Farrar KM. Are you willing to risk it? The relationship between risk, regret, and vaccination intent. Psychol Health Med. 2015; https://doi.org/10.1080/13548506.2014.911923 .

Ziarnowski KL, Brewer NT, Weber B. Present choices, future outcomes: anticipated regret and HPV vaccination. Prev Med. 2009; https://doi.org/10.1016/j.ypmed.2008.10.006 .

Betsch C, Böhm R, Korn L, Holtmann C. On the benefits of explaining herd immunity in vaccine advocacy. Nat Hum Behav. 2017; https://doi.org/10.1038/s41562-017-0056 .

Loomba S, de Figueiredo A, Piatek SJ, de Graaf K, Larson HJ. Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nat Hum Behav. 2021; https://doi.org/10.1038/s41562-021-01056-1 .

Pfattheicher S, Petersen MB, Böhm R. Information about herd immunity through vaccination and empathy promote COVID-19 vaccination intentions. Health Psychol. 2022;41(2):85.

Article PubMed Google Scholar

Hakim H, Provencher T, Chambers CT, Driedger SM, Dube E, Gavaruzzi T, ... & Witteman HO. Interventions to help people understand community immunity: a systematic review. Vaccine. 2019; https://doi.org/10.1016/j.vaccine.2018.11.016 .

Hakim H, Bettinger JA, Chambers CT, Driedger SM, Dubé E, Gavaruzzi T, Giguere AMC, Kavanagh É, Leask J, MacDonald SE, Orji R, Parent E, Paquette J, Roberge J, Sander B, Scherer AM, Tremblay-Breault M, Wilson K, Reinharz D, Witteman HO. A Web Application About Herd Immunity Using Personalized Avatars: Development Study. Journal of medical Internet research. 2020; https://doi.org/10.2196/20113 .

Callaghan T, Moghtaderi A, Lueck JA, Hotez P, Strych U, Dor A, Fowler EF, Motta M. Correlates and disparities of intention to vaccinate against COVID-19. Soc Sci Med (1982). 2021; https://doi.org/10.1016/j.socscimed.2020.113638 .

Griffith J, Marani H, Monkman H. COVID-19 vaccine hesitancy in Canada: Content analysis of tweets using the theoretical domains framework. Journal of medical Internet research. 2021; https://doi.org/10.2196/26874 .

Attwell K, Lake J, Sneddon J, Gerrans P, Blyth C, & Lee J. Converting the maybes: Crucial for a successful COVID-19 vaccination strategy. PLoS One. 2021; https://doi.org/10.1371/journal.pone.0245907 .

Breckenridge LA, Burns D, & Nye C. The use of motivational interviewing to overcome COVID‐19 vaccine hesitancy in primary care settings. Public Health Nurs. 2022; https://doi.org/10.1111/phn.13003 .

Gabarda A, & Butterworth SW. Using best practices to address COVID-19 vaccine hesitancy: The case for the motivational interviewing approach. Health Promot Pract, 2021; https://doi.org/10.1177/152483992110164 .

Hamilton EM, Oversby S, Ratsch A, & Kitchener S.COVID-19 vaccination: An exploratory study of the motivations and concerns detailed in the medical records of a regional Australian population. Vaccines. 2022; https://doi.org/10.3390/vaccines10050657 .

Purvis RS, Moore R, Willis DE, Hallgren E, & McElfish PA. Factors influencing COVID-19 vaccine decision-making among hesitant adopters in the United States. Human Vaccines Immunother. 2022; https://doi.org/10.1080/21645515.2022.2114701 .

Boragno P, Fiabane E, Taino I, Maffoni M, Sommovigo V, Setti I, Gabanelli P. Perceptions of COVID-19 Vaccines: Protective Shields or Threatening Risks? A Descriptive Exploratory Study among the Italian Population. Vaccines. 2023; https://doi.org/10.3390/vaccines11030642 .

Centers for Disease Control and Prevention. Why it matters: The pandemic threat. Retrieved December. 2020;1:2020.

Download references

Acknowledgements

Not applicable.

Open access funding provided by Università degli Studi di Padova. The project was developed thanks to institutional research funding of TG and AT.

Author information

Authors and affiliations.

Department of Developmental Psychology and Socialization, University of Padova, Padua, Italy

Marta Caserotti, Roberta Sellaro, Enrico Rubaltelli & Lorella Lotto

Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University of Venezia, Venice, Italy

Paolo Girardi

Department of Humanities, University of Ferrara, Ferrara, Italy

Alessandra Tasso

Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy

Teresa Gavaruzzi

You can also search for this author in PubMed Google Scholar

Contributions

MC: Conceptualization, Formal analysis, Visualization, Writing—original draft and Writing—review & editing. PG: Conceptualization, Formal analysis, Visualization, Writing—original draft. RS: Conceptualization, Writing—review & editing. ER: Conceptualization, Writing—review & editing. AT: Conceptualization, Writing—review & editing. LL: Conceptualization, Writing—review & editing. TG: Conceptualization, Visualization, Writing—review & editing.

Corresponding author

Correspondence to Marta Caserotti .

Ethics declarations

Ethics approval and consent to participate.

The project was approved by the ethical committee for Psychology Research of the University of Padova (Italy), with protocol number 3911/2020, and informed consent was obtained for all participants.

Consent for publication

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: appendix 1..

Scoring for pro- and against-vaccination reasons. Appendix 2. Structure of the questionnaire. Table S1. Selection criteria. Table S2. Number of items, internal consistency (Cronbach’s α), name of the items and their estimated loadings, total deviance explained by the loadings and proportion of variance explained by EFA for COVID-19 perceived risk. Table S3. Odds ratios (ORs) estimated by the logistic model for the propensity score weighting for the COVID-19 vaccine offer. Table S4 . Predicted willingness to get vaccinated by combination of pro- and against-vaccination reasons by category of reference. Table S5. Frequency of reported categories of pro- and against-vaccination reasons overall, and by COVID-19 vaccine status. Figure S1. Distribution of the propensity scores by vaccine offer.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Caserotti, M., Girardi, P., Sellaro, R. et al. To vaccinate or not to vaccinate? The interplay between pro- and against- vaccination reasons. BMC Public Health 23 , 2207 (2023). https://doi.org/10.1186/s12889-023-17112-6

Download citation

Received : 12 December 2022

Accepted : 30 October 2023

Published : 09 November 2023

DOI : https://doi.org/10.1186/s12889-023-17112-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Pro-and against-reasons
Vaccination intention
Risk perception
Emotional competences

BMC Public Health

ISSN: 1471-2458

General enquiries: [email protected]

REVIEW article

Impact of vaccines; health, economic and social perspectives.

$\r\nCharlene M. C. Rodrigues,$

1 Department of Zoology, University of Oxford, Oxford, United Kingdom
2 Department of Paediatric Infectious Diseases, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom
3 Department of Pediatrics, University of Pennsylvania, Philadelphia, PA, United States

In the 20th century, the development, licensing and implementation of vaccines as part of large, systematic immunization programs started to address health inequities that existed globally. However, at the time of writing, access to vaccines that prevent life-threatening infectious diseases remains unequal to all infants, children and adults in the world. This is a problem that many individuals and agencies are working hard to address globally. As clinicians and biomedical scientists we often focus on the health benefits that vaccines provide, in the prevention of ill-health and death from infectious pathogens. Here we discuss the health, economic and social benefits of vaccines that have been identified and studied in recent years, impacting all regions and all age groups. After learning of the emergence of SARS-CoV-2 virus in December 2019, and its potential for global dissemination to cause COVID-19 disease was realized, there was an urgent need to develop vaccines at an unprecedented rate and scale. As we appreciate and quantify the health, economic and social benefits of vaccines and immunization programs to individuals and society, we should endeavor to communicate this to the public and policy makers, for the benefit of endemic, epidemic, and pandemic diseases.

Introduction

“The impact of vaccination on the health of the world’s peoples is hard to exaggerate. With the exception of safe water, no other modality has had such a major effect on mortality reduction and population growth” ( Plotkin and Mortimer, 1988 ).

The development of safe and efficacious vaccination against diseases that cause substantial morbidity and mortality has been one of the foremost scientific advances of the 21st century. Vaccination, along with sanitation and clean drinking water, are public health interventions that are undeniably responsible for improved health outcomes globally. It is estimated that vaccines have prevented 6 million deaths from vaccine-preventable diseases annually ( Ehreth, 2003 ). By 2055, the earth’s population is estimated to reach almost 10 billion ( United Nations Department of Economic and Social Affairs, 2019 ), a feat that in part is due to effective vaccines that prevent disease and prolong life expectancy across all continents. That said, there is still much to be done to ensure the financing, provision, distribution, and administration of vaccines to all populations, in particular those which are difficult to reach, including those skeptical about their protective value and those living in civil disruption. Agencies including the World Health Organization (WHO), United Nations Children’s Fund (UNICEF), Gavi, the Vaccine Alliance, The Bill & Melinda Gates Foundation, and the Coalition for Epidemic Preparedness Initiative (CEPI), with their multiple funding streams have been instrumental in expanding vaccine benefits to all. These importance of these organizations in global co-operation and participation was essential in the setting of the 2019 global pandemic of SARS-CoV-2, in light of the health and economic impact of COVID-19 on societies in high-, middle- and low-income countries. This review will highlight the benefits of vaccinations to society from the perspectives of health, economy, and social fabric ( Figure 1 ), which need to be considered in the overall assessment of impact to ensure that vaccines are prioritized by those making funding decisions.

Figure 1. The impact of vaccines according to their health, economic or social benefit.

Brief History of Vaccine Development

Human use of preparations to prevent specific infections have been described since 1500 AD, beginning in China ( Needham, 2000 ) where smallpox was prevented by variolation, which is the introduction of material from scabs into the skin. In 1796 in the United Kingdom, Edward Jenner observed the immunity to smallpox of milkmaids having previously had natural infection with cowpox ( Jenner, 1798 ). He determined that inoculating small amounts of pus from the lesions of cowpox, presumably containing a virus related to vaccinia, into susceptible hosts rendered them immune to smallpox. The vaccine against smallpox was developed in 1798. The next phase of scientific developments involving the manipulation of infectious agents to extract suitable vaccine antigens took almost a century of research. Louis Pasteur’s work with attenuation by oxygen or heat led to live-attenuated chicken cholera, inactivated anthrax and live-attenuated rabies vaccines at the turn of the 20th century ( Pasteur, 1880 , 1881 , 1885 ). Alternative methods of attenuation using serial passage of Mycobacterium bovis led to the live Bacille Calmette-Guerin (BCG) ( Calmette, 1927 ) vaccine, still in use today for the prevention of tuberculosis. Serial passage was also used in the development of yellow fever vaccines ( Theiler and Smith, 1937a ) which are grown in chicken embryo tissues ( Theiler and Smith, 1937b ). Whole cell killed bacterial vaccines were developed when methods to treat and kill bacteria through heat or chemicals were established and whole cell typhoid, cholera and pertussis vaccines resulted at the end of the 19th Century. In 1923, Alexander Glenny and Barbara Hopkins developed methods to inactivate bacterial toxins with formaldehyde, leading to the diphtheria and tetanus toxoid vaccines ( Glenny and Hopkins, 1923 ).

Advances in virus culture in vitro allowed viral pathogens to be studied in greater detail and attenuation methods due to cultivation in artificial conditions led to the live oral polio, measles, rubella, mumps and varicella virus vaccines. In the 1960’s at the Walter Reed Army Institute of Research, vaccines were developed using capsular polysaccharides ( Gold and Artenstein, 1971 ; Artenstein, 1975 ), of encapsulated organisms including meningococci and later pneumococci ( Austrian, 1989 ) and Haemophilus influenzae type b (Hib) ( Anderson et al., 1972 ). To protect against multiple serotype variants of polysaccharide capsules, polyvalent vaccines were developed and later conjugated to carrier proteins to enhance their efficacy in infants in particular by recruiting T-cell mediated help to induce memory B-cells ( Schneerson et al., 1980 ). Vaccines made solely from proteins were rare, with the exception of the toxoid vaccines, but the acellular pertussis vaccine containing five protein antigens, was developed to mitigate the unwanted effects of the whole cell vaccine ( Sato and Sato, 1999 ).

The end of the 20th century marked a revolution in molecular biology and provided insights into microbiology and immunology allowing a greater understanding of pathogen epitopes and host responses to vaccination. Molecular genetics and genome sequencing has enabled the development of vaccines against RNA viruses possessing multiple variants of epitopes, such as the live and inactivated influenza vaccines ( Maassab and DeBorde, 1985 ) and live rotavirus vaccines ( Clark et al., 2006 ). DNA manipulation and excision allowed the use of surface antigen for hepatitis B viral vectors ( Plotkin, 2014 ). The human papilloma virus (HPV) vaccine benefits from enhanced immunogenicity due to the formation of virus-like particles by the L1 antigen of each virus contained in the vaccine ( Kirnbauer et al., 1992 ). Bacterial genome sequencing has provided in depth analysis of meningococcal antigens, to identify potential proteins for meningococcal B vaccines ( Serruto et al., 2012 ).

Vaccine development was tested in 2020 when a novel coronavirus, SARS-CoV-2, emerged from China causing a severe acute respiratory illness, which subsequently spread globally. Within 5 months of the discovery of this virus (7th January 2020) ( Zhu et al., 2020 ) and person-person transmission ( Chan et al., 2020 ), 5,697,334 cases had been identified, with orders of magnitude likely not measured and almost no country escaped the pandemic. Owing to the previous advances in vaccinology, by 8th April 2020, there were 73 vaccine candidates under pre-clinical investigation ( Thanh Le et al., 2020 ). Of these, six were in Phase 1 or 1/2 trials and one was in Phase 2/3 trials by 28th May 2020. The rapidity of this response demonstrated the ability to harness existing technologies including: RNA vaccine platforms (NCT04283461), DNA vaccine platforms (NCT04336410), recombinant vector vaccines (NCT04313127, NCT04324606) and adjuvants. The regulation, manufacturer and distribution of these vaccines will require expedition given the global public health need, from a period of many years to a matter of months. The efficacy and health impact of these vaccines is yet to be established, but if they are effective, then vaccines need to be made available for all global regions affected by SARS-CoV-2. The funding of this endeavor will prove challenging in a global context of national social and economic lockdown and massive government borrowing, but the justification for this provision will be through the multiple benefits to society that will need healthy citizens to rebuild economies in the decades post-COVID-19.

The history of vaccination is not complete without describing the public health intervention that led to the routine use of these vaccines for children globally. The Expanded Program of Immunization (EPI) was founded by WHO in 1974 with the aim of providing routine vaccines to all children by 1990 ( World Health Assembly, 1974 ). In 1977, global policies for immunization against diphtheria, pertussis, tetanus, measles, polio, and tuberculosis were set out. The EPI includes hepatitis B, Hib, and pneumococcal vaccines in many areas and by 2017, 85% of the world’s children (12–23 months of age) received diphtheria, pertussis, tetanus, and measles vaccines ( World Bank, 2019 ).

Health Benefits of Vaccination

Reduction in infectious diseases morbidity and mortality.

The most significant impact of vaccines has been to prevent morbidity and mortality from serious infections that disproportionately affect children. Vaccines are estimated to prevent almost six million deaths/year and to save 386 million life years and 96 million disability-adjusted life years (DALYs) globally ( Ehreth, 2003 ). The traditional measures of vaccine impact include: vaccine efficacy, the direct protection offered to a vaccinated group under optimal conditions e.g., trial settings; or vaccine effectiveness, the direct and indirect effect of vaccines on the population in a real-life setting ( Wilder-Smith et al., 2017 ). Providing a numerical measure of vaccine impact therefore involves estimating the extent of morbidity and mortality prevented. In the United States in 2009, amongst an annual birth cohort vaccinated against 13 diseases it was estimated that nearly 20 million cases of disease and ∼42,000 deaths were prevented ( Zhou et al., 2009 ). Infectious diseases that accounted for major mortality and morbidity in the early 20th century in the United States all showed over a 90% decline in incidence by 2017 from the pre-vaccine peak incidence ( Roush and Murphy, 2007 ), due to high vaccine uptake of over 90% for the DTaP (diphtheria, tetanus, and acellular pertussis), MMR (measles, mumps, and rubella) and polio vaccines ( World Health Organisation, 2019a ; Table 1 ). A similar pattern of infectious diseases reduction was seen across other high-income countries, demonstrating the efficacy of vaccines when available and accessible.

Table 1. Vaccine impact in United States comparing the incidence of diseases prior to the implementation of vaccine ( Roush and Murphy, 2007 ), described as the pre-vaccine era and the vaccine coverage ( Hill et al., 2017 ) and disease incidence ( Centers for Disease Control and Prevention, 2017 ) in 2017, as reported by the Centers for Disease Control and Prevention.

Globally, the provision of vaccines is more challenging in many low- and middle- income countries (LMIC), as evidenced by the failure to make the EPI vaccines available to every child by 1990, irrespective of setting ( Keja et al., 1988 ). Central to this is limited financial resources, but other barriers to vaccine introduction include: underappreciation of the value of vaccines locally/regionally though insufficient relevant data on disease burden, vaccine efficacy, or cost-effectiveness; inadequate healthcare infrastructure for vaccine handling, storage, programmatic management, and disease surveillance; and lack of global, regional or local policy-making and leadership ( Munira and Fritzen, 2007 ; Hajjeh, 2011 ). In 2018, the global uptake of three doses of DTaP reached 86% which corresponded to 116,300,000 infants ( World Health Organisation, 2019a ). The vaccine coverage is, however, variable between low-, middle- and high-income countries because of a combination of economic and political circumstances as well as variable access to non-governmental support from Gavi, the Vaccine Alliance ( Turner et al., 2018 ; Figure 2 ). Nevertheless, there has been a decrease in the global burden of diseases caused by vaccine-preventable pathogens ( Figure 3 ) enabling healthier lives for many millions of children. A further benefit following vaccination, is the evidence that although vaccines may not always prevent an infection, for example VZV or pertussis, a milder disease course may follow ( Andre et al., 2008 ; Bonanni et al., 2015 ).

Figure 2. Vaccine uptake across different regions defined by economic status by the World Bank into high- (solid line), middle- (dashed line), and low-income countries (dotted line) for the past 20 years. Data from the World Health Organization and UNICEF dataset “Coverage Estimates Series” ( World Health Organization [WHO] and United Nations Children’s Fund [UNICEF], 2019 ).

Figure 3. Reduction in infectious diseases globally. Across all world regions, data from the WHO, for the last 20 years showing the control of diphtheria and tetanus and the decline in rubella and congenital rubella syndrome (data not shown). Data from the World Health Organization dataset “Reported cases of vaccine-preventable diseases” ( World Health Organisation, 2019c ).

Eradication of Infectious Diseases

Global disease eradication can be achieved for pathogens that are restricted to human reservoirs. For eradication of infectious diseases, high levels of population immunity are required globally, to ensure no ongoing transmission in our well-connected world ( Andre et al., 2008 ). Furthermore, surveillance systems must be in place to monitor the decline in disease, with accurate and reliable diagnostic testing to monitor ongoing cases. At the time of writing, the only infectious disease that has been eradicated in humans by vaccination is smallpox. This disease had afflicted humans for millenia, with the earliest evidence found in Egyptian mummies from 1000 BC ( Geddes, 2006 ). Jenner’s successful development of the smallpox vaccine using vaccinia virus ( Jenner, 1798 ) led to the ultimate eradication of the disease through ring vaccination as announced by the World Health Assembly in 1980 ( Strassburg, 1982 ), which was an historic public health achievement. The second example of eradication was of the rinderpest virus in livestock, an infection that indirectly led to human loss of life through loss of agriculture leading to humanitarian crises through famine and poverty. Rinderpest virus infects cattle, buffalo and numerous other domestic species, with widespread disease affecting large parts of Africa and Europe in the 19th century ( Roeder et al., 2013 ). The Plowright tissue culture rinderpest vaccine, developed during the 1950s, was used for mass vaccination campaigns, alongside other public health measures, leading to eradication in 2011 ( Morens et al., 2011 ).

The next infection targeted for eradication is wild polio virus. This devastating paralytic disease routinely afflicted children and adults in both industrialized and developing settings, prior to the development of vaccines. Two polio vaccines, the inactivated polio vaccine (IPV) and the live-attenuated oral polio vaccine (OPV) became available in 1955 and 1963, respectively ( Plotkin, 2014 ), both able to protect against all three wild types of polio virus. Both vaccines have been used globally, with live-attenuated OPV much cheaper and easier to administer but carrying the risk of causing circulating vaccine-derived poliovirus (cVDPV) owing to back-mutation and re-acquisition of neurovirulence. Hence, due to its safety IPV was preferred in industrialized regions and those where the polio incidence was low. In 1998, the Global Polio Eradication Initiative, the largest public-private partnership led by national governments in partnership with the WHO, Rotary International, United States Centers for Disease Control and Prevention (CDC), and UNICEF was launched with the aim of global polio eradication by 2000. Although this target was not met due to lack of funding, political will, and competing health initiatives, there was a 99% reduction in polio incidence by 2000 ( Lien and Heymann, 2013 ). By 2003, there were only six endemic countries with new cases: Egypt, Niger, India, Nigeria, Afghanistan, and Pakistan, of which only the latter four had new cases by 2005. Eradication in India was problematic due to the high birth rates and poor sanitation amongst densely populated regions with marginalized communities and high population mobility ( Thacker et al., 2016 ). India was declared polio free in 2014. Wild polio virus type 2 was eradicated in 2015, the last case of wild type 3 was in 2012 and eradication announced in 2019, with wild type 1 virus remaining in two countries, Pakistan and Afghanistan ( World Health Organisation, 2019b ). In 2019, Nigeria was declared 3 years free of wild polio, the last country in Africa to declare any cases. In the first 6 months of 2020, there were 51 and 17 cases of wild type 1 polio reported in Pakistan and Afghanistan respectively ( Global Polio Eradication Initiative, 2019 ). Ongoing programs to roll out universal vaccination in both countries remain hindered by armed conflict, political instability, remote communities and underdeveloped infrastructure. The risk of the OPV recipients developing cVDPV disease, with transmission through the faeco-oral route to cause outbreaks of vaccine-derived paralytic poliomyelitis remains a concerning obstacle in the eradication process, requiring intensive surveillance.

Herd Immunity

The overriding health benefit perceived by most vaccine recipients is their personal, direct, protection. The added value of vaccination, on a population level, is the potential to generate herd immunity. Where a sufficiently high proportion of the population are vaccinated, transmission of the infecting agent is halted thereby protecting the unvaccinated, who may be those too young, too vulnerable, or too immunosuppressed to receive vaccines. Highly successful vaccination programs have been in place as part of the routine EPI, against encapsulated bacteria that are carried asymptomatically in the oropharynx but that can invade and cause septicemia and meningitis in all age groups. Vaccines against Neisseria meningitidis ( Gold and Artenstein, 1971 ), Streptococcus pneumoniae ( Austrian, 1989 ), and Hib ( Anderson et al., 1972 ) were developed in the 1960s, 1970s, and 1980s, respectively, using their polysaccharide capsules as vaccine antigens, which successfully induced protective immunity (direct protection). Conjugation of these polysaccharides to carrier proteins in the 1990s improved their efficacy by not only ensuring a T cell response and immune memory, but by reducing acquisition of pharyngeal carriage of these organisms, thus providing indirect protection and thereby preventing ongoing transmission ( Pollard et al., 2009 ). This was first observed in national carriage studies in the United Kingdom in 1999–2001 during a mass vaccination campaign against serogroup C N. meningitidis ( Maiden et al., 2008 ) and was a major contributing factor to the declining disease thereafter.

Herd (population) immunity requires high levels of vaccine uptake, to limit the number of unvaccinated people and the opportunity for pathogen transmission between them. The proportion of a given population required to induce herd immunity through vaccination is lower for the bacterial infections and conjugate polysaccharide vaccines, as their basic reproductive number (R 0 ) is lower than viral infections like measles, varicella or polio ( Table 2 ). Measles virus can cause devastating disease ranging from acute presentations with pneumonia or encephalitis, to immune amnesia and long-term complications such as subacute sclerosing panencephalitis ( Mina et al., 2015 , 2019 ; Moss, 2017 ; Petrova et al., 2019 ). The live-attenuated measles vaccine is highly efficacious and the first dose is recommended at 9–12 months of age. To protect those who cannot receive live vaccines (younger infants, pregnant women, the immunosuppressed) from acquiring measles in the community, at least 93–95% of the population is required to be vaccinated with two doses in order to interrupt measles virus transmission. In many countries in Europe and in the United States, this level of vaccination uptake is falling ( Wise, 2018 ), due to a combination of reduced accessibility to health services and vaccine misinformation. As a result, some countries, including the United Kingdom and United States, where elimination of measles had been declared have had a resurgence of disease ( Wise, 2019 ). For high-risk individuals who are unable to be vaccinated, herd immunity represents a life-saving protection strategy against many infections. An alternative strategy, cocooning, has been employed with limited success for pertussis and influenza ( Grizas et al., 2012 ), where their close/household contacts are vaccinated to prevent transmission.

Table 2. Vaccines with the potential to induce herd immunity, with the infectious agent, vaccine type, and thresholds of population vaccination needed for herd immunity ( Peltola et al., 1999 ; Whitney et al., 2003 ; Donaghy et al., 2006 ; Fine and Griffiths, 2007 ; Maiden et al., 2008 ; Curns et al., 2010 ; Paulke-Korinek et al., 2011 ; Plans-Rubio, 2012 ; Daugla et al., 2014 ; Tabrizi et al., 2014 ; Funk et al., 2019 ; Palmer et al., 2019 ).

Herd immunity has been observed for gastrointestinal infections with vaccines against cholera (oral cholera vaccine) and rotavirus (oral rotavirus vaccines). Early adopters of rotavirus vaccines included the United States (2006) and Austria (2007) where there were dramatic reductions in disease observed in the vaccinated infant cohort, and also in the older age groups of children and adults ( Curns et al., 2010 ; Paulke-Korinek et al., 2011 ), suggesting that the reduction in disease and shedding of virus in the stool stopped transmission to healthy household contacts. For the OPV, herd protection may also be induced through vaccine virus shedding and spread to unvaccinated people ( Fine and Griffiths, 2007 ).

Reduction in Secondary Infections That Complicate Vaccine-Preventable Diseases

Vaccines can prevent diseases beyond the specific infection they are designed to target. Infections with pathogens, in particular viruses, can predispose to the acquisition of other bacterial infections. For example, influenza virus infection, both seasonal and pandemic, is frequently complicated by bacterial pneumonia and acute otitis media (OM), and infrequently Aspergillus pneumonia/pneumonitis. During the influenza pandemic of 1918–19, secondary bacterial bronchopneumonia with S. pneumoniae, Streptococcus pyogenes , H. influenzae , and Staphylococcus aureus identified at autopsy, likely contributed to the excess mortality observed amongst healthy children and adults ( Morens and Fauci, 2007 ). Influenza vaccinations can be beneficial in preventing these complications and also morbidity including acute OM in children; a systematic review demonstrated influenza vaccine efficacy against OM of 51% (21–70%) ( Manzoli et al., 2007 ). Further, there is evidence that inactivated influenza vaccines administered to pregnant women can reduce the hospital admission with acute respiratory illnesses in their infants up to 6 months of age ( Regan et al., 2016 ). Amongst pregnant, HIV-negative women in South Africa, infants (<3 months) were protected against hospitalization with all-cause lower respiratory tract infections with a vaccine efficacy of 43% ( p = 0.05), including primary viral and secondary bacterial causes ( Nunes et al., 2017 ). Additionally, in children pneumococcal conjugate vaccines were observed to reduce the incidence of influenza-associated hospital admissions in United States ( Simonsen et al., 2011 ), Spain ( Dominguez et al., 2013 ), and South Africa ( Madhi et al., 2004 ; Abadom et al., 2016 ), through the prevention of secondary bacterial infections following primary influenza infection.

The introduction of the live-attenuated measles vaccine in the 1970s was observed to reduce both measles and non-measles mortality in children ( Aaby et al., 2003 ). Measles causes severe pneumonia, encephalitis, and the long-term sequel of subacute sclerosing panencephalitis ( Moss, 2017 ), but the decline in mortality was not limited to preventing these alone ( Aaby et al., 2003 ). Mathematical modeling of vaccination and immunological research demonstrated that measles causes an immunological amnesia, eliminating B cell populations and thus immune memory, leaving measles survivors susceptible to all the infective agents they had previously developed immunity against; it is estimated to take 3 years for immune recovery to occur ( Mina et al., 2015 ).

Prevention of Cancer

Historically, vaccines were developed against very severe infections with major morbidity and mortality from acute disease. As non-communicable diseases, including cancer, become the most frequent causes of death in industrialized countries and some developing countries, vaccines are being used to prevent these too, when the infectious agents are involved in carcinogenesis. Hepatitis B prevalence is high in regions of East Asia, sub-Saharan Africa, and the Pacific Islands. Chronic hepatitis B infection can lead to liver cirrhosis and hepatocellular carcinoma ( Bogler et al., 2018 ). Vertical transmission of hepatitis B is problematic as 70–90% of babies born to HbsAg and HbeAg positive mothers will become infected without prophylaxis administered to babies; with ∼90% of infants developing chronic hepatitis ( Borgia et al., 2012 ; Gentile and Borgia, 2014 ). The chronic hepatitis B carriage status of mothers is routinely checked at the start of pregnancy, in order to assess the need to vaccinate the infant after birth. The use of both hepatitis B vaccine, containing hepatitis B surface antigen, and immunoglobulin containing hepatitis B antibody can be used to minimize vertical transmission, with evidence from a 20-year-long study in Thailand demonstrating 100% prevention of transmission ( Poovorawan et al., 2011 ).

The sexually transmitted HPV is responsible for genital tract and oropharyngeal infections as a precursor to causing oncological disease affecting the cervix, vagina, vulva, penis, anal tract, and pharynx in both men and women. Cervical cancer is the fourth most common cancer globally, with 528,000 new cases annually and peak incidence in young women aged 25–34 years ( Ferlay et al., 2012 ). The HPV serotypes 16 and 18 carry a high-risk for cervical cancer ( Wang et al., 2018 ) and vaccination against these specific serotypes has been available since 2006 through bivalent (16 and 18), quadrivalent (6, 11, 16, and 18), and nonavalent (6, 11, 16, 18, 31, 33, 45, 52, 58) vaccines, which are now available to individuals from the age of 9 years ( Gupta et al., 2017 ). A vaccination program started in the United Kingdom in 2008, and at the time of writing over 10.5 million doses had been given to girls ( Public Health England, 2018 ), with the aim of preventing primary infection with HPV. The vaccine coverage was 83.8% for 13–14 year old girls in England in 2017/18 ( Public Health England, 2019 ). In July 2018, the vaccine was approved for use in boys ( Public Health England, 2019 ). After a decade of use, there has been an observed decline in the genital infections caused by serotypes 16 and 18 ( Public Health England, 2018 ), with further time needed to observe the fall in cervical cancer incidence. However, the incidence of pre-invasive cervical diseases has been reduced by 79–89% in Scottish women over 20 who were vaccinated with bivalent HPV vaccine when aged 12–13 years, with evidence of herd protection ( Palmer et al., 2019 ), offering a promising outlook for the reduction of cervical cancer in the future. An additional benefit of HPV vaccines, is their impact on neonatal morbidity and mortality, through the reduction in surgical treatment of cervical neoplasias, and the related preterm births and complications ( Soergel et al., 2012 ).

Preventing Antibiotic Resistance

The rise in antimicrobial resistance (AMR) is a universal threat. The use of antibiotics in humans, exposes the bacteria that reside in our microbiota to selection pressures resulting in the development of AMR. As the bacteria constituting the host microbiota are frequently responsible for invasive diseases such as: meningitis, pneumonia, urinary tract, or abdominal infections, the risk of developing infections that are difficult or eventually impossible to treat is fast becoming a reality ( Brinkac et al., 2017 ). In regions where resistant pathogens are circulating at high frequency, such as India or regions of Europe ( Logan and Weinstein, 2017 ), patients will be faced with choosing between having elective surgical procedures or chemotherapy for malignancy, and the risk of acquiring potentially untreatable, multi-drug resistant bacterial infections ( Liu et al., 2016 ). Vaccination is crucial in mitigating this risk, by preventing people from developing viral and bacterial infections in the first instance, and therefore reducing the antibiotic burden to which their microbiota are exposed. The development of AMR in bacteria is a cumulative process with frequent, repeated exposure to broad spectrum antibiotics as a major driver. Children and the elderly who are at particular risk of infection can benefit from vaccines against common primary and secondary infections such as: pneumonia (prevented by PCV, PPSV, influenza, and measles vaccines), OM (PCV, Hib, and measles vaccines), cellulitis secondary to VZV (VZV vaccine), and typhoid fever (typhoid vaccine) which alleviates the need for antibiotics being prescribed or bought ( Kyaw et al., 2006 ; Palmu et al., 2014 ). The extent to which vaccination contributes to antimicrobial stewardship was highlighted by its inclusion in vaccine cost-effectiveness analyses as part of national United Kingdom policy ( Bonanni et al., 2015 ).

Economic Benefits

Cost savings.

Vaccines are highly beneficial on a population level and also cost-effective ( Shearley, 1999 ) in comparison to other public health interventions ( Bloom et al., 2005 ). Government departments are required to perform systematic economic analyses of vaccines and vaccine programs to justify their purchase in view of pressure on public and private finances globally, this was exacerbated by the 2008 financial crash. A vaccination program has clear direct costs including: vaccine purchase, infrastructure to run the program and maintain the cold chain, and healthcare/administration personnel. Governments, sometimes supported by charities and non-governmental organizations, invest in these with the intention of improving health. The reduction in morbidity and mortality associated with successful vaccine programs, through a combination of direct and indirect protection, has led to reduced incidence of diseases and their associated treatments and healthcare costs ( Deogaonkar et al., 2012 ). This potentially leads to economic growth, with less money spent owing to the costs averted through fewer medical tests, procedures, treatments and less time off work by patients/parents. Additionally, the use of combination vaccines e.g., DTaP/IPV/Hib/HepB provides protection against an increased number of diseases, with no additional infrastructure costs i.e. the same number of injections per child within existing immunization programs.

The cost-effectiveness analyses of vaccination programs demonstrate that they are overwhelmingly worth the investment, with most programs costing less than $50 per life gained, orders of magnitude less than prevention of diseases like hypertension ( Ehreth, 2003 ; Bloom et al., 2005 ). The returns on investment in vaccines, given their increasing provision through Gavi, have been estimated at 12–18% ( Bloom et al., 2005 ), but this is likely an underestimate. The monetary advantages of vaccination programs are important both to industrialized nations, such as the United States which obtains a net economic benefit of $69 billion, but also in 94 LMIC where investment of $34 billion, resulted in savings of $586 billion from the direct illness costs ( Ozawa et al., 2016 ; Orenstein and Ahmed, 2017 ). The net economic impact of eradication of disease has been estimated for both smallpox and polio. For smallpox, the eradication costs were over 100 million USD, but there are cost savings of 1.35 billion USD annually, with elimination of polio estimated to save 1.5 billion USD annually ( Barrett, 2004 ; Bloom et al., 2005 ). A less well-considered economic saving, not captured in cost-effectiveness or cost-benefit analyses, is from the prevention of long-term morbidity following acute infections ( Bloom et al., 2005 ), for example hearing impairment following pneumococcal meningitis or limb amputation following meningococcal disease, along with broader productivity gains ( Deogaonkar et al., 2012 ), which could have a major impact on LMIC adoption of vaccine programs.

Productivity Gains

The relationship between health and the economy is bidirectional, whereby economic growth enables funding in investments that improve health; and a healthy population contributes to and enhances an economy. These benefits of vaccinations and other public health interventions including sanitation, clean water, and antibiotics, are important for social as well as economic reasons. It has been suggested that the economic impact of vaccines should be considered more broadly than just the averted healthcare costs from prevented illness episodes and associated carer costs ( Deogaonkar et al., 2012 ; Barnighausen et al., 2014 ; Bonanni et al., 2015 ; Gessner et al., 2017 ; Wilder-Smith et al., 2017 ). Bärnighausen et al. (2011) , set out a framework to consider productivity gains measured by: outcome and behavior; community health and economic externalities; risk reduction; and health gains. Healthy children demonstrate improved educational attainment at school through better attendance and better cognitive performance ( Barham and Calimeria, 2008 ; Bloom et al., 2011 ; Deogaonkar et al., 2012 ). The impact of hearing loss from mumps, rubella or pneumococcal infections, or visual impairment from measles may require specific educational support, whereas the cognitive deficits from those childhood infections may require substantial remedial input. As more children survive to adulthood, a larger adult workforce is available, who when healthy can work for longer and more productively both physically and mentally ( Bloom and Canning, 2000 ; Bloom et al., 2005 ); though to date this has been observed largely following other health improvements, not vaccination specifically ( Jit et al., 2015 ). As a result of vaccination healthy and economically successful populations have lower fertility rates and smaller families ( Sah, 1991 ; Andre et al., 2008 ). With improved health and therefore life expectancy, there is a wider effect on families who may choose to invest more money in their future, for example to enhance their education or through savings ( Jit et al., 2015 ). Overall, vaccine programs should be viewed as an investment in human capital, providing enduring impact on economies worldwide.

Minimizing the Impact on Family

The economic impact of adult illness is evident from loss of productivity and pay for the duration of the illness and recovery period. The impact of childhood illness falls primarily on their adult carers, generally parents. In most industrialized regions, two-parent families are reliant on both parents undertaking at least part-time or full-time work. Therefore, when a child is unwell with childhood illnesses, which may or may not necessitate admission to hospital, the parent will invariably have to forego their paid employment to care for the child. In seven European countries one parent or carer required time off work in 39–91% of rotavirus gastroenteritis cases ( Van der Wielen et al., 2010 ). This loss of productivity in the parental workforce tends to disproportionately affect women, but loss of either parental attendance at work reduces overall employer productivity and in the short-term is rarely replaced. This argument was made for the impact of chicken pox on children, whereby the exclusion from school mandates parental caring at home for a period until the lesions are crusted over. VZV vaccines are estimated to have had a similar impact as rotavirus vaccine in United States studies ( Lieu et al., 1994 ). In many regions, mothers are still the primary carers, spending their days at home caring for children and maintaining the household; in these settings, the impact on this unpaid work is harder to determine.

It is of paramount importance to quantify and include productivity gains and the wider effects in analyses of impact for vaccines with only moderate efficacy, as calculated using traditional metrics. Vaccines such as the RTS,S/AS01 malaria vaccine, CYD-TDV dengue vaccine and rotavirus vaccine used in LMIC all have limited ability to broadly protect populations over a long duration but the public health benefits were important in vaccine implementation decisions in those countries ( Wilder-Smith et al., 2017 ). This suggests a paradigm for alternative regulatory requirements with a focus on public health outcomes ( Gessner et al., 2017 ).

Cost-Effective Preparedness for Outbreaks

As human populations grow and their use of the finite land resources increases, we are in increasingly close association with other living creatures, voluntarily or involuntarily. This interaction with natural reservoirs of potential infectious diseases increases the risk of zoonotic transmission of new infectious pathogens e.g., SARS, MERS-CoV, or known infectious pathogens with increased virulence e.g., influenza. Emerging infectious diseases disproportionately affect developing regions, where health infrastructure and surveillance are likely to be less well-established and robust. There were 1,307 epidemics of infectious diseases between 2011 and 2017, which cumulatively cost $60 billion annually to manage ( GHRF Commission, 2016 ). The unpredictability of outbreaks was highlighted by the Ebola epidemic in Western African countries of Liberia, Sierra Leone, and Guinea in 2014, which occurred in a period when public health was supposedly at its most advanced in recent history. However, a catalog of areas including: outbreak planning infrastructure; disease surveillance; local health services; escalation to international agencies were found to be lacking ( GHRF Commission, 2016 ). Although the WHO received criticism for its lack of escalation, in reality the global and interconnected infrastructure to prevent such epidemics taking lives and devastating societies is insufficient at the present time. The Zika virus epidemic in Latin America in 2015, first observed through an unexpectedly high incidence of microcephaly amongst newborns in Brazil’s northern regions ( Heukelbach et al., 2016 ), provide another example of how epidemics can have lasting impact, with the virus causing significant neurological damage to surviving infants ( Russo et al., 2017 ). The SARS-CoV-2 pandemic which began in 2019, was, at the time of writing, the largest infectious disease pandemic since the influenza pandemic of 1918/9. This global public health crisis highlighted stark societal inequalities persistent in many high-, middle- and low-income countries with direct and indirect impact on health outcomes from this infection. The cost-effectiveness of a vaccine in this setting was unquestionable, with economies and societies shut down for months in early 2020 and likely again in future. As it is not feasible or practical to be able to predict the location or nature of the next emerging threat, investment of an estimated $4.5 billion/year in healthcare systems could help speed up responses to infectious epidemics by prompt identification of the agent and effective control measures to limit the spread and consequences of disease ( GHRF Commission, 2016 ). The importance of this planning within the political landscape and the ongoing threat that infectious disease pose, may be appreciated more widely after 2020.

Establishing Programs for Vaccine Development

One effective infection control method is the use of vaccines in the course of an epidemic to halt transmission and to induce immunity to those as yet unaffected. The cost of vaccine development is a major challenge as there is little incentive for industry to invest in the design, testing and manufacture of vaccines that may never be needed, have a limited market, and, as previously eluded to, may be required in LMIC which cannot afford the upfront costs as an epidemic unfolds. The estimated costs for funding the development of infectious diseases vaccines for epidemics through phase 2a clinical trials are a minimum of $2.8-3.7 billion ( Gouglas et al., 2018 ). The CEPI alliance was established at the Davos World Economic Forum in 2017 as a global partnership between public, private and philanthropic organizations. In response to the conclusion that “a coordinated, international, and intergovernmental plan was needed to develop and deploy new vaccines to prevent future epidemics,” CEPI have identified the most important known global infectious threats and invested in the development of vaccines, stockpiling, and policies to allow equitable access to these ( Plotkin, 2017 ). Further, the establishment of research and development infrastructure pipelines will allow production of suitable vaccine candidates within 16 weeks of identification of a new pathogen antigen. The broader aims including: improving global epidemic responses; capacity building; and global regulation of outbreak management strategies are also within the remit of CEPI’s work. It is these types of preparedness plans that assisted vaccine development and global health collaborations to address the COVID-19 pandemic, though many regions of high-, middle-, and low-income countries alike were slow or resistant to pre-empt and prepare for this type of infectious disease threat.

Social Benefits

Equity of healthcare.

As a result of the combined effects of poverty, malnutrition, poor hygiene and sanitation, overcrowding, discrimination and poorer access to health-care, the underprivileged in society are disproportionately afflicted by infectious diseases. Over the 20th century, it has become a moral standpoint and a human right for every individual to be provided with access to safe vaccines. The provision of vaccination as part of the EPI on a national and international scale ( World Health Assembly, 1974 ) acted as a great leveler to start reducing the impact of infectious diseases to all, regardless of other disadvantages. Over the 15 years of the EPI, the vaccine coverage in developing countries increased from 5% to ∼80% ( Levine and Robins-Browne, 2009 ). The EPI was revolutionary for its time, an ambitious public health program that aimed to improve children’s life chances despite the country and situation in which they were born. The administration of vaccines by UNICEF was deemed so important that there have been at least seven ceasefires in civil conflicts to allow this to happen ( Hotez, 2001 ).

The impact of vaccines on the inequity of those living in poverty is marked. A study of over 16,000 children during the phased introduction of the measles vaccine in Bangladesh in 1982, demonstrated improved health outcome equity when measured by under-5 mortality ( Bishai et al., 2003 ). Further, modeling of the impact of the rotavirus vaccine in India across social strata, which are closely aligned to wealth, suggested that the vaccine program would provide the poor with both health and financial benefits ( Verguet et al., 2013 ). Including such equity impact in the health economic modeling of vaccines would allow policy decisions to be targeted to the most vulnerable in society ( Riumallo-Herl et al., 2018 ). Additional cost-effective benefits observed after the implementation of combined public health initiatives ( Deogaonkar et al., 2012 ; Gessner et al., 2017 ) include provision of vaccines, facilitation of healthcare, reduction of indoor air pollution and improvement of nutrition to prevent childhood pneumonia ( Niessen et al., 2009 ).

Strengthening Health and Social Care Infrastructure

To provide the EPI universally to infants and children, a significant degree of healthcare infrastructure is required ranging from primary care to public health. An example of the multiple facets of a successful vaccine program were outlined in the Mission Indradhanush in India, which planned to make life-saving vaccines available to all children and pregnant women by 2020 through programs with (i) national, (ii) state, (iii) district, and (iv) block/urban level input ( Hinman and McKinlay, 2015 ). National programs require governments to provide financial resources and set out policy for implementation. States needed to obtain the vaccines and to store them appropriately whilst eligible children were identified through public health messaging and outreach. Districts and urban areas recruited staff trained in vaccine delivery and communication to administer vaccines and to provide the aftercare where required. Establishing this degree of nationwide infrastructure to reach those in urban and rural areas, provides the basis for the provision of other health and social care services for all members of the community, in particular improving maternal and infant mortality in developing regions and in the elderly in industrialized regions ( Shearley, 1999 ). Public health infrastructure and personnel could be used to promote other important messages and health education ( Shearley, 1999 ), relating to malnutrition, hygiene and sanitation and preventable diseases such as malaria and HIV infection. Global drivers are also key, as demonstrated by the establishment of the EPI in 1974, when all countries were directed to provide these vaccines, thereby developing their primary- and public health-care infrastructure, with benefit beyond the vaccine program. Vaccination contributes to the UN Millennium Development Goals and later Sustainable Development Goals for achievement by 2030. Gavi, the Vaccine Alliance, has been an important provider of funds, vaccines and support for countries whose gross national income per capita was <£1000/year ( Hinman and McKinlay, 2015 ). The partnerships forged through the development of vaccine programs in LMIC, can be long-lasting and beneficial through other health and social care endeavors ( Shearley, 1999 ).

Impact of Life Expectancy and Opportunity

Vaccination programs provide a degree of social mobility, as poverty and the associated ill-health and mortality from infectious diseases are no longer the determinants of one’s life chances. Vaccine recipients have the potential for improved life-expectancy largely demonstrated by, but not confined to, infants and children ( Andre et al., 2008 ). It has become increasingly recognized that an aging population goes through the process of immunosenescence ( Fulop et al., 2017 ), and increased incidence and severity of infectious diseases. In many countries, therefore, older people are offered vaccines to prevent infections with high mortality and morbidity, including the influenza, pneumococcal, herpes zoster, and pertussis vaccines ( Bonanni et al., 2015 ). These prevent the development of pneumonia, admission to hospital and the subsequent associated risks of death from cardiac failure, as observed in Sweden ( Christenson et al., 2004 ).

The global and interconnected world of the 21st century provides opportunity to discover new cultures, new environments and their resident microbes. The safety of global travel has been greatly enhanced by the availability of vaccines that provide protection against organisms that are different to those in a person’s home setting. Movement of people may be through necessity when fleeing war and conflict, in the search of better life opportunities, or for leisure purposes. For mass movements of refugees vaccines are crucial to the aid and relief efforts to support these individuals ( Hermans et al., 2017 ), as measles and cholera can be highly problematic in refugee camps. Global mass cultural or religious gatherings, such as the Hajj pilgrimage ( Yezli et al., 2018 ) or the Chinese New Year ( Chen et al., 2018 ) have been implicated in the spread of meningococcal disease outbreaks. Pre-travel vaccines offer the optimal level of protection for those with scheduled travel plans and include protection against: yellow fever, hepatitis A and B, rabies, Japanese encephalitis, tick-borne encephalitis, typhoid, and cholera.

Empowerment of Women

The empowerment of women is both a driver and effect of vaccination programs. The degree of education, literacy and independence of girls and women varies considerably across the world and within countries. Where women have the information and autonomy to make health-related decision for their children, childhood immunization rates improve. In a study in Bihar State in rural India involving an empowerment program, where participating women were educated about health and hygiene, there was a higher rate of DTP, measles and BCG vaccination in their children compared to the non-participants in the villages running the program ( Janssens, 2011 ). Further, this information and autonomy served to improve the rates of vaccination in children of non-participants in the villages running the program compared to control villages not running the education program, through social or formal ongoing dialogue within the village community. A separate public health initiative in Haryana, India conducted between 2005 and 2012 to reduce maternal and child health inequalities, involved improving access and provision of health resources to rural areas, the poor in society, women and children. One significant outcome of this initiative was the equitable provision of immunizations to girls and boys, despite the male-favored disparity prior to starting the public health initiative ( Gupta et al., 2016 ).

By improving infant and childhood mortality from infection, more children will survive to adulthood with the potential to have productive and healthy lives. This has led to healthy and economically secure women having fewer children and less peripartum morbidity and mortality ( Sah, 1991 ; Shearley, 1999 ). Thus, women are able to spend more time with their children and on their development ( Shearley, 1999 ) as well as their own education and contribution to the workforce. The strategy of maternal vaccination has demonstrated great success at preventing diseases that afflict infants too young to be vaccinated against pertussis, influenza and tetanus ( Marchant et al., 2017 ). Factors influencing the uptake of maternal vaccination include women’s previous experiences with healthcare and vaccines, so it is crucial to provide the access and support required to enable them to make informed choices during their pregnancy ( Wilson et al., 2019 ).

The impact of vaccines is broad and far-reaching, though not consistently quantifiable, analyzed or communicated. Traditionally, the perceived benefits of vaccination were to reduce morbidity and mortality from infections, and those remain the drivers for the innovation of new vaccines, in particular in preparation for outbreaks or against infections that afflict the most disadvantaged in society. However, an increasing appreciation for the economic and social effects of vaccines is being included in the development and assessment of vaccine programs, potentially realizing a greater benefit to society and resulting in wider implementation. There remain challenges to delivering vaccines to all children and vulnerable people worldwide, in particular those in communities that are difficult to reach geographically, politically and culturally and these challenges can only be overcome with the continued commitment and dedication to this endeavor on an international, national and individual scale.

Author Contributions

SP conceptualized and designed the study. CR prepared the manuscript and figures. CR and SP contributed to literature search and revision and review of the final manuscript. Both authors contributed to the article and approved the submitted version.

Conflict of Interest

SP consults for many major vaccine manufacturers and biotechnology companies but this article was unfunded.

The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Aaby, P., Bhuiya, A., Nahar, L., Knudsen, K., de Francisco, A., and Strong, M. (2003). The survival benefit of measles immunization may not be explained entirely by the prevention of measles disease: a community study from rural Bangladesh. Intern. J. Epidemiol. 32, 106–116.

Google Scholar

Abadom, T. R., Smith, A. D., Tempia, S., Madhi, S. A., Cohen, C., and Cohen, A. L. (2016). Risk factors associated with hospitalisation for influenza-associated severe acute respiratory illness in South Africa: a case-population study. Vaccine 34, 5649–5655.

Anderson, P., Peter, G., Johnston, R. B. Jr., Wetterlow, L. H., and Smith, D. H. (1972). Immunization of humans with polyribophosphate, the capsular antigen of Hemophilus influenzae , type b. J. Clin. Invest. 51, 39–44.

Andre, F. E., Booy, R., Bock, H. L., Clemens, J., Datta, S. K., John, T. J., et al. (2008). Vaccination greatly reduces disease, disability, death and inequity worldwide. Bull. World Health Organ. 86, 140–146.

Artenstein, M. S. (1975). Control of meningococcal meningitis with meningococcal vaccines. Yale J. Biol. Med. 48, 197–200.

Austrian, R. (1989). Pneumococcal polysaccharide vaccines. Rev. Infect. Dis. 11, (Suppl. 3), S598–S602.

Barham, T., and Calimeria, L. (2008). Long-term Effects of Family Planning and Child Health Interventions on Adolescent Cognition: Evidence from Matlab in Bangladesh. Boulder, CO: Univeristy of Colorado.

Barnighausen, T., Bloom, D. E., Cafiero-Fonseca, E. T., and O’Brien, J. C. (2014). Valuing vaccination. Proc. Nat. Acad. Sci. U.S.A. 111, 12313–12319.

Bärnighausen, T., Bloom, D. E., Canning, D., Friedman, A., Levine, O. S., O’Brien, J., et al. (2011). Rethinking the benefits and costs of childhood vaccination: the example of the Haemophilus influenzae type b vaccine. Vaccine 29, 2371–2380.

Barrett, S. (2004). Eradication versus control: the economics of global infectious disease policies. Bull. World Health Organ. 82, 683–688.

Bishai, D., Koenig, M., and Ali Khan, M. (2003). Measles vaccination improves the equity of health outcomes: evidence from Bangladesh. Health Econ. 12, 415–419.

Bloom, D. E., and Canning, D. (2000). Policy forum: public health. The health and wealth of nations. Science 287:1207.

Bloom, D. E., Canning, D., and Seiguer, E. (2011). The Effect of Vaccination on Children’s Physical and Cognitive Development in the Philippines. Boston, MA: Harvard School of Public Health.

Bloom, D. E., Canning, D., and Weston, M. (2005). The value of vaccination. World Econ. 6, 15–16.

Bogler, Y., Wong, R. J., and Gish, R. G. (2018). “Epidemiology and natural history of chronic hepatitis B virus infection,” in Hepatitis B Virus and Liver Disease , eds J.-H. Kao and D.-S. Chen (Berlin: Springer), 63–89.

Bonanni, P., Picazo, J. J., and Remy, V. (2015). The intangible benefits of vaccination - what is the true economic value of vaccination? J. Mark. Access Health Policy 3:10.3402/jmahv3.26964.

Borgia, G., Carleo, M. A., Gaeta, G. B., and Gentile, I. (2012). Hepatitis B in pregnancy. World J. Gastroenterol. 18, 4677–4683.

Brinkac, L., Voorhies, A., Gomez, A., and Nelson, K. E. (2017). The threat of antimicrobial resistance on the human microbiome. Microb. Ecol. 74, 1001–1008.

Calmette, A. (1927). La Vaccination Preìventive Contre La Tuberculose par le “BCG,”. Paris: Masson.

Centers for Disease Control and Prevention (2017). Reported Cases Of Notifiable Diseases And Rates Per 100,000, Excluding U.S. Territories, United States, 2017. Atlanta: Centers for Disease Control and Prevention.

Chan, J. F., Yuan, S., Kok, K. H., To, K. K., Chu, H., Yang, J., et al. (2020). A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 395, 514–523.

Chen, M., Rodrigues, C. M. C., Harrison, O. B., Zhang, C., Tan, T., Chen, J., et al. (2018). Invasive meningococcal disease in Shanghai, China from 1950 to 2016: implications for serogroup B vaccine implementation. Sci. Rep. 8:12334.

Christenson, B., Hedlund, J., Lundbergh, P., and Ortqvist, A. (2004). Additive preventive effect of influenza and pneumococcal vaccines in elderly persons. Eur. Resp. J. 23, 363–368.

Clark, H. F., Offit, P. A., Plotkin, S. A., and Heaton, P. M. (2006). The new pentavalent rotavirus vaccine composed of bovine (strain WC3) -human rotavirus reassortants. Pediatr. Infect. Dis. J. 25, 577–583.

Curns, A. T., Steiner, C. A., Barrett, M., Hunter, K., Wilson, E., and Parashar, U. D. (2010). Reduction in acute gastroenteritis hospitalizations among US children after introduction of rotavirus vaccine: analysis of hospital discharge data from 18 US states. J. Infect. Dis. 201, 1617–1624.

Daugla, D. M., Gami, J. P., Gamougam, K., Naibei, N., Mbainadji, L., Narbe, M., et al. (2014). Effect of a serogroup A meningococcal conjugate vaccine (PsA-TT) on serogroup A meningococcal meningitis and carriage in Chad: a community study [corrected]. Lancet 383, 40–47.

Deogaonkar, R., Hutubessy, R., van der Putten, I., Evers, S., and Jit, M. (2012). Systematic review of studies evaluating the broader economic impact of vaccination in low and middle income countries. BMC Public Health 12:878. doi: 10.1186/s12916-017-0911-878

CrossRef Full Text | Google Scholar

Dominguez, A., Castilla, J., Godoy, P., Delgado-Rodriguez, M., Saez, M., Soldevila, N., et al. (2013). Benefit of conjugate pneumococcal vaccination in preventing influenza hospitalization in children: a case-control study. Pediatr. Infect. Dis. J. 32, 330–334.

Donaghy, M., Cameron, J. C., and Friederichs, V. (2006). Increasing incidence of mumps in Scotland: options for reducing transmission. J. Clin. Virol. 35, 121–129.

Ehreth, J. (2003). The global value of vaccination. Vaccine 21, 596–600.

Ferlay, J., Soerjomataram, I., Dikshit, R., Eser, S., Mathers, C., Rebelo, M., et al. (2012). Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN. Int. J. Cancer 136, E359–E386.

Fine, P. E., and Griffiths, U. K. (2007). Global poliomyelitis eradication: status and implications. Lancet 369, 1321–1322.

Fulop, T., Larbi, A., Dupuis, G., Le Page, A., Frost, E. H., Cohen, A. A., et al. (2017). Immunosenescence and inflamm-aging as two sides of the same coin: friends or foes? Front. Immunol. 8:1960. doi: 10.3389/fmicb.2018.01960

PubMed Abstract | CrossRef Full Text | Google Scholar

Funk, S., Knapp, J. K., Lebo, E., Reef, S. E., Dabbagh, A. J., Kretsinger, K., et al. (2019). Combining serological and contact data to derive target immunity levels for achieving and maintaining measles elimination. BMC Med. 17:180. doi: 10.1186/s12889-019-6655-180

Geddes, A. M. (2006). The history of smallpox. Clin. Dermatol. 24, 152–157.

Gentile, I., and Borgia, G. (2014). Vertical transmission of hepatitis B virus: challenges and solutions. Intern. J. Women Health 6, 605–611.

Gessner, B. D., Kaslow, D., Louis, J., Neuzil, K., O’Brien, K. L., Picot, V., et al. (2017). Estimating the full public health value of vaccination. Vaccine 35, 6255–6263.

GHRF Commission (2016). Commission on a Global Health Risk Framework for the Future). The Neglected Dimension of Global Security A Framework to Counter Infectious Disease Crises. Commission on Global Health Risk Framework for the Future. Available online at: https://nam.edu/wp-content/uploads/2016/01/Neglected-Dimension-of-Global-Security.pdf (September 24, 2019).

Glenny, A. T., and Hopkins, B. E. (1923). Diphtheria toxoid as an immunising agent. Br. J. Exp. Pathol. 4, 283–288.

Global Polio Eradication Initiative (2019). Polio this Week, Wild Poliovirus Type 1 And Circulating Vaccine-Derived Poliovirus Cases. Available online at: http://polioeradication.org/polio-today/polio-now/this-week/ (accessed June 25, 2020).

Gold, R., and Artenstein, M. S. (1971). Meningococcal infections. 2. Field trial of group C meningococcal polysaccharide vaccine in 1969-70. Bull. World Health Organ. 45, 279–282.

Gouglas, D., Thanh, Le, T., Henderson, K., Kaloudis, A., Danielsen, T., et al. (2018). Estimating the cost of vaccine development against epidemic infectious diseases: a cost minimisation study. Lancet Glob. Health 6:e001386-96.

Grizas, A. P., Camenga, D., and Vazquez, M. (2012). Cocooning: a concept to protect young children from infectious diseases. Curr. Opin. Pediatr. 24, 92–97.

Gupta, G., Glueck, R., and Patel, P. R. (2017). HPV vaccines: global perspectives. Hum. Vacc. Immunotherap. 13, 1–4.

Gupta, M., Angeli, F., Bosma, H., Rana, M., Prinja, S., Kumar, R., et al. (2016). Effectiveness of multiple-strategy community intervention in reducing geographical, socioeconomic and gender based inequalities in maternal and child health outcomes in Haryana, India. PLoS One 11:e0150537. doi: 10.1371/journal.pone.0150537

Hajjeh, R. (2011). Accelerating introduction of new vaccines: barriers to introduction and lessons learned from the recent Haemophilus influenzae type B vaccine experience. Philos. Trans. R. Soc. B. 366, 2827–2832.

Hermans, M. P. J., Kooistra, J., Cannegieter, S. C., Rosendaal, F. R., Mook-Kanamori, D. O., and Nemeth, B. (2017). Healthcare and disease burden among refugees in long-stay refugee camps at Lesbos. Greece. Eur. J. Epidemiol. 32, 851–854.

Heukelbach, J., Alencar, C. H., Kelvin, A. A., de Oliveira, W. K., and Pamplona de Goes, C. L. (2016). Zika virus outbreak in Brazil. J. Infect. Dev. Countr. 10, 116–120.

Hill, H. A., Elam-Evans, L. D., Yankey, D., Singleton, J. A., and Kang, Y. (2017). Vaccination coverage among children aged 19-35 Months - United States, 2016. MMWR Morb. Mort. Wkly Rep. 66, 1171–1177.

Hinman, A. R., and McKinlay, M. A. (2015). Immunization equity. Vaccine 33, (Suppl. 4), D72–D77.

Hotez, P. J. (2001). Vaccines as instruments of foreign policy. The new vaccines for tropical infectious diseases may have unanticipated uses beyond fighting diseases. EMBO Rep. 2, 862–868.

Janssens, W. (2011). Externalities in program evaluation: the impact of a Women’s empowerment program on immunization. J. Eur. Econ. Assoc. 9, 1082–1113.

Jenner, E. (1798). An Inquiry Into The Causes And Effects Of The Variolæ Vaccinæ, A Disease Discovered In Some Of The Western Counties Of England, Particularly Gloucestershire, And Known By The Name Of The Cow Pox. London: Sampson Low.

Jit, M., Hutubessy, R., Png, M. E., Sundaram, N., Audimulam, J., Salim, S., et al. (2015). The broader economic impact of vaccination: reviewing and appraising the strength of evidence. BMC Med. 13:209. doi: 10.1186/s12916-017-0911-209

Keja, K., Chan, C., Hayden, G., and Henderson, R. H. (1988). Expanded programme on immunization. World Health Stat. Q. 41, 59–63.

Kirnbauer, R., Booy, F., Cheng, N., Lowy, D. R., and Schiller, J. T. (1992). Papillomavirus L1 major capsid protein self-assembles into virus-like particles that are highly immunogenic. Proc. Nat. Acad. Sci. U.S.A. 89, 12180–12184.

Kyaw, M. H., Lynfield, R., Schaffner, W., Craig, A. S., Hadler, J., Reingold, A., et al. (2006). Effect of introduction of the pneumococcal conjugate vaccine on drug-resistant Streptococcus pneumoniae . New Engl. J. Med. 354, 1455–1463.

Levine, M. M., and Robins-Browne, R. (2009). Vaccines, global health and social equity. Immunol. Cell Biol. 87, 274–278.

Lien, G., and Heymann, D. L. (2013). The problems with polio: toward eradication. Infect. Dis. Ther. 2, 167–174.

Lieu, T. A., Cochi, S. L., Black, S. B., Halloran, M. E., Shinefield, H. R., Holmes, S. J., et al. (1994). Cost-effectiveness of a routine varicella vaccination program for US children. JAMA 271, 375–381.

Liu, Y. Y., Wang, Y., Walsh, T. R., Yi, L. X., Zhang, R., Spencer, J., et al. (2016). Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect. Dis. 16, 161–168.

Logan, L. K., and Weinstein, R. A. (2017). The epidemiology of carbapenem-resistant Enterobacteriaceae : the impact and evolution of a global menace. J. Infect. Dis. 215(Suppl._1), S28–S36.

Maassab, H. F., and DeBorde, D. C. (1985). Development and characterization of cold-adapted viruses for use as live virus vaccines. Vaccine 3, 355–369.

Madhi, S. A., Klugman, K. P., and Vaccine Trialist, G. (2004). A role for Streptococcus pneumoniae in virus-associated pneumonia. Nat. Med. 10, 811–813.

Maiden, M. C., Ibarz-Pavon, A. B., Urwin, R., Gray, S. J., Andrews, N. J., Clarke, S. C., et al. (2008). Impact of meningococcal serogroup C conjugate vaccines on carriage and herd immunity. J. Infect. Dis. 197, 737–743.

Manzoli, L., Schioppa, F., Boccia, A., and Villari, P. (2007). The efficacy of influenza vaccine for healthy children: a meta-analysis evaluating potential sources of variation in efficacy estimates including study quality. Pediatr. Infect. Dis. J. 26, 97–106.

Marchant, A., Sadarangani, M., Garand, M., Dauby, N., Verhasselt, V., Pereira, L., et al. (2017). Maternal immunisation: collaborating with mother nature. Lancet. Infect. Dis. 17, e197–e208. doi: 10.1016/S1473-3099(17)30229-3

Mina, M. J., Kula, T., Leng, Y., Li, M., de Vries, R. D., Knip, M., et al. (2019). Measles virus infection diminishes preexisting antibodies that offer protection from other pathogens. Science 366, 599–606.

Mina, M. J., Metcalf, C. J., de Swart, R. L., Osterhaus, A. D., and Grenfell, B. T. (2015). Long-term measles-induced immunomodulation increases overall childhood infectious disease mortality. Science 348, 694–699.

Morens, D. M., and Fauci, A. S. (2007). The 1918 influenza pandemic: insights for the 21st century. J. Infect. Dis. 195, 1018–1028.

Morens, D. M., Holmes, E. C., Davis, A. S., and Taubenberger, J. K. (2011). Global rinderpest eradication: lessons learned and why humans should celebrate too. J. Infect. Dis. 204, 502–505.

Moss, W. J. (2017). Measles. Lancet 390, 2490–2502.

Munira, S. L., and Fritzen, S. A. (2007). What influences government adoption of vaccines in developing countries? A policy process analysis. Soc. Sci. Med. 65, 1751–1764.

Needham, J. (2000). Science and Civilisation in China: Volume 6, Biology and Biological Technology. Cambridge: Cambridge University Press.

Niessen, L. W., ten Hove, A., Hilderink, H., Weber, M., Mulholland, K., and Ezzati, M. (2009). Comparative impact assessment of child pneumonia interventions. Bull. World Health Organ. 87, 472–480.

Nunes, M. C., Cutland, C. L., Jones, S., Downs, S., Weinberg, A., Ortiz, J. R., et al. (2017). Efficacy of maternal influenza vaccination against all-cause lower respiratory tract infection hospitalizations in young infants: results from a randomized controlled trial. Clin. Infect. Dis. 65, 1066–1071.

Orenstein, W. A., and Ahmed, R. (2017). Simply put: vaccination saves lives. Proc. Nat. Acad. Sci. U.S.A. 114, 4031–4033.

Ozawa, S., Clark, S., Portnoy, A., Grewal, S., Brenzel, L., and Walker, D. G. (2016). Return On investment from childhood immunization in low- and middle-income countries, 2011-20. Health Aff. 35, 199–207.

Palmer, T., Wallace, L., Pollock, K. G., Cuschieri, K., Robertson, C., Kavanagh, K., et al. (2019). Prevalence of cervical disease at age 20 after immunisation with bivalent HPV vaccine at age 12-13 in Scotland: retrospective population study. BMJ 365:l1161.

Palmu, A. A., Jokinen, J., Nieminen, H., Rinta-Kokko, H., Ruokokoski, E., Puumalainen, T., et al. (2014). Effect of pneumococcal Haemophilus influenzae protein D conjugate vaccine (PHiD-CV10) on outpatient antimicrobial purchases: a double-blind, cluster randomised phase 3-4 trial. Lancet Infect. Dis. 14, 205–212.

Pasteur, L. (1880). De l’attenuation du virus du choléra des poules. Comptes Rendus De l’Acad. Sci. 91, 673–680.

Pasteur, L. (1881). Sur la vaccination charbonneuse. Comptes Rendus De l’Acad. Sci. 92, 1378–1383.

Pasteur, L. (1885). Mèthode pour prévenir la rage apres morsure. Comptes Rendus De l’Acad. Sci. 101, 765–772.

Paulke-Korinek, M., Kundi, M., Rendi-Wagner, P., de Martin, A., Eder, G., Schmidle-Loss, B., et al. (2011). Herd immunity after two years of the universal mass vaccination program against rotavirus gastroenteritis in Austria. Vaccine 29, 2791–2796.

Peltola, H., Aavitsland, P., Hansen, K. G., Jonsdottir, K. E., Nokleby, H., and Romanus, V. (1999). Perspective: a five-country analysis of the impact of four different Haemophilus influenzae type b conjugates and vaccination strategies in Scandinavia. J. Infect. Dis. 179, 223–229.

Petrova, V. N., Sawatsky, B., Han, A. X., Laksono, B. M., Walz, L., Parker, E., et al. (2019). Incomplete genetic reconstitution of B cell pools contributes to prolonged immunosuppression after measles. Sci. Immunol. 4:eaay6125.

Plans-Rubio, P. (2012). Evaluation of the establishment of herd immunity in the population by means of serological surveys and vaccination coverage. Hum. Vacc. Immunotherap. 8, 184–188.

Plotkin, S. (2014). History of vaccination. Proc. Natl. Acad. Sci. U.S.A. 111, 12283–12287.

Plotkin, S. A. (2017). Vaccines for epidemic infections and the role of CEPI. Hum. Vacc. Immunotherap. 13, 2755–2762.

Plotkin, S. A., and Mortimer, E. A. (1988). Vaccines. Philadelphia, PA: Saunders.

Pollard, A. J., Perrett, K. P., and Beverley, P. C. (2009). Maintaining protection against invasive bacteria with protein-polysaccharide conjugate vaccines. Nat. Rev. Immunol. 9, 213–220.

Poovorawan, Y., Chongsrisawat, V., Theamboonlers, A., Leroux-Roels, G., Kuriyakose, S., Leyssen, M., et al. (2011). Evidence of protection against clinical and chronic hepatitis B infection 20 years after infant vaccination in a high endemicity region. J. Viral Hepat. 18, 369–375.

Public Health England (2018). Public Health Matters Ten Years On Since The Start Of The HPV Vaccine Programme – What Impact Is It Having? London: Public Health England.

Public Health England (2019). Human Papillomavirus (HPV) Vaccination Coverage In Adolescent Females In England: 2017/18. London: Public Health England.

Regan, A. K., de Klerk, N., Moore, H. C., Omer, S. B., Shellam, G., and Effler, P. V. (2016). Effect of maternal influenza vaccination on hospitalization for respiratory infections in newborns: a retrospective cohort study. Pediatr. Infect. Dis. J. 35, 1097–1103.

Riumallo-Herl, C., Chang, A. Y., Clark, S., Constenla, D., Clark, A., Brenzel, L., et al. (2018). Poverty reduction and equity benefits of introducing or scaling up measles, rotavirus and pneumococcal vaccines in low-income and middle-income countries: a modelling study. BMJ Glob. Health 3:e000613.

Roeder, P., Mariner, J., and Kock, R. (2013). Rinderpest: the veterinary perspective on eradication. Philos. Trans. R. Soc. B 368:20120139.

Roush, S. W., and Murphy, T. V. (2007). Vaccine-preventable disease table working G. historical comparisons of morbidity and mortality for vaccine-preventable diseases in the United States. JAMA 298, 2155–2163.

Russo, F. B., Jungmann, P., and Beltrao-Braga, P. C. B. (2017). Zika infection and the development of neurological defects. Cell. Microbiol. 19: 12744.

Sah, R. K. (1991). The effects of child-mortality changes on fertility choice and parental welfare. J. Polit. Econ. 99, 582–606.

Sato, Y., and Sato, H. (1999). Development of acellular pertussis vaccines. Biologicals 27, 61–69.

Schneerson, R., Barrera, O., Sutton, A., and Robbins, J. B. (1980). Preparation, characterization, and immunogenicity of Haemophilus influenzae type b polysaccharide-protein conjugates. J. Exp. Med. 152, 361–376.

Serruto, D., Bottomley, M. J., Ram, S., Giuliani, M. M., and Rappuoli, R. (2012). The new multicomponent vaccine against meningococcal serogroup B, 4CMenB: immunological, functional and structural characterization of the antigens. Vaccine 30, (Suppl. 2), B87–B97.

Shearley, A. E. (1999). The societal value of vaccination in developing countries. Vaccine 17, (Suppl. 3), S109–S112.

Simonsen, L., Taylor, R. J., Young-Xu, Y., Haber, M., May, L., and Klugman, K. P. (2011). Impact of pneumococcal conjugate vaccination of infants on pneumonia and influenza hospitalization and mortality in all age groups in the United States. mBio 2:e00309-10.

Soergel, P., Makowski, L., Schippert, C., Staboulidou, I., Hille, U., and Hillemanns, P. (2012). The cost efficiency of HPV vaccines is significantly underestimated due to omission of conisation-associated prematurity with neonatal mortality and morbidity. Hum. Vacc. Immunother. 8, 243–251.

Strassburg, M. A. (1982). The global eradication of smallpox. Am. J. Infect. Control 10, 53–59.

Tabrizi, S. N., Brotherton, J. M., Kaldor, J. M., Skinner, S. R., Liu, B., Bateson, D., et al. (2014). Assessment of herd immunity and cross-protection after a human papillomavirus vaccination programme in Australia: a repeat cross-sectional study. Lancet Infect.ous Dis. 14, 958–966.

Thacker, N., Vashishtha, V. M., and Thacker, D. (2016). Polio eradication in India: the lessons learned. Pediatrics 138:e20160461.

Thanh Le, T., Andreadakis, Z., Kumar, A., Gomez Roman, R., Tollefsen, S., Saville, M., et al. (2020). The COVID-19 vaccine development landscape. Nat. Rev. Drug Discov. 19, 305–306.

Theiler, M., and Smith, H. H. (1937a). The effect of prolonged cultivation in vitro upon the pathogenicity of yellow fever virus. J. Exp. Med. 65, 767–786.

Theiler, M., and Smith, H. H. (1937b). The use of yellow fever virus modified by in vitro cultivation for human immunization. J. Exp. Med. 65, 787–800.

Turner, H. C., Thwaites, G. E., and Clapham, H. E. (2018). Vaccine-preventable diseases in lower-middle-income countries. Lancet Infect. Dis. 18, 937–939.

United Nations Department of Economic and Social Affairs (2019). Population Division. World Population Prospects 2019. New York, NY: United Nations Department of Economic and Social Affairs.

Van der Wielen, M., Giaquinto, C., Gothefors, L., Huelsse, C., Huet, F., Littmann, M., et al. (2010). Impact of community-acquired paediatric rotavirus gastroenteritis on family life: data from the REVEAL study. BMC Fam. Pract. 11:22. doi: 10.1186/s12916-017-0911-22

Verguet, S., Murphy, S., Anderson, B., Johansson, K. A., Glass, R., and Rheingans, R. (2013). Public finance of rotavirus vaccination in India and Ethiopia: an extended cost-effectiveness analysis. Vaccine 31, 4902–4910.

Wang, X., Huang, X., and Zhang, Y. (2018). Involvement of human papillomaviruses in cervical cancer. Front. Microbiol. 9:2896. doi: 10.3389/fmicb.2018.02896

Whitney, C. G., Farley, M. M., Hadler, J., Harrison, L. H., Bennett, N. M., Lynfield, R., et al. (2003). Decline in invasive pneumococcal disease after the introduction of protein-polysaccharide conjugate vaccine. New Engl. J. Med. 348, 1737–1746.

Wilder-Smith, A., Longini, I., Zuber, P. L., Barnighausen, T., Edmunds, W. J., Dean, N., et al. (2017). The public health value of vaccines beyond efficacy: methods, measures and outcomes. BMC Med. 15:138. doi: 10.1186/s12916-017-0911-8

Wilson, R., Paterson, P., and Larson, H. J. (2019). Strategies to improve maternal vaccination acceptance. BMC Public Health 19:342. doi: 10.1186/s12889-019-6655-y

Wise, J. (2018). Child vaccination rates drop in England as MMR uptake falls for fourth year. BMJ 362:k3967.

Wise, J. (2019). MMR vaccine: johnson urges new impetus to increase uptake as UK loses measles-free status. BMJ 366:l5219.

World Bank (2019). Immunization, DPT (% of Children Ages 12-23 Months). Washington, DC: World Bank.

World Health Assembly (1974). The expanded programme on immunization: the 1974 resolution by the world health assembly. Assign. Child. 1985, 87–88.

World Health Organisation (2019a). Immunization Coverage. Geneva: World Health Organisation.

World Health Organisation (2019b). Polio Eradication. Geneva: World Health Organisation.

World Health Organisation (2019c). Reported Cases of Selected Vaccine Preventable Diseases (VPDs). Geneva: World Health Organisation.

World Health Organization [WHO], United Nations Children’s Fund [UNICEF] (2019). WHO/UNICEF Estimates of National Immunization Coverage (WUENIC) 1980-2018. Geneva: WHO.

Yezli, S., Gautret, P., Assiri, A. M., Gessner, B. D., and Alotaibi, B. (2018). Prevention of meningococcal disease at mass gatherings: lessons from the Hajj and Umrah. Vaccine 36, 4603–4609.

Zhou, F., Shefer, A., Wenger, J., Messonnier, M., Wang, L. Y., Lopez, A., et al. (2009). Economic evaluation of the routine childhood immunization program in the United States. Pediatrics 133, 577–585.

Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., et al. (2020). A novel coronavirus from patients with pneumonia in China, 2019. New Engl. J. Med. 382, 727–733.

Keywords : immunization, vaccines, infectious diseases, infection, children, health economics

Citation: Rodrigues CMC and Plotkin SA (2020) Impact of Vaccines; Health, Economic and Social Perspectives. Front. Microbiol. 11:1526. doi: 10.3389/fmicb.2020.01526

Received: 09 April 2020; Accepted: 12 June 2020; Published: 14 July 2020.

Reviewed by:

Copyright © 2020 Rodrigues and Plotkin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Stanley A. Plotkin, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

français
español
português

View Statistics

Description, document number, collections.

Technical documents

Show Statistical Information

5. Regional Office for Europe

Greater Good Science Center • Magazine • In Action • In Education

11 Questions to Ask About COVID-19 Research

Debates have raged on social media, around dinner tables, on TV, and in Congress about the science of COVID-19. Is it really worse than the flu? How necessary are lockdowns? Do masks work to prevent infection? What kinds of masks work best? Is the new vaccine safe?

You might see friends, relatives, and coworkers offer competing answers, often brandishing studies or citing individual doctors and scientists to support their positions. With so much disagreement—and with such high stakes—how can we use science to make the best decisions?

Here at Greater Good , we cover research into social and emotional well-being, and we try to help people apply findings to their personal and professional lives. We are well aware that our business is a tricky one.

Summarizing scientific studies and distilling the key insights that people can apply to their lives isn’t just difficult for the obvious reasons, like understanding and then explaining formal science terms or rigorous empirical and analytic methods to non-specialists. It’s also the case that context gets lost when we translate findings into stories, tips, and tools, especially when we push it all through the nuance-squashing machine of the Internet. Many people rarely read past the headlines, which intrinsically aim to be relatable and provoke interest in as many people as possible. Because our articles can never be as comprehensive as the original studies, they almost always omit some crucial caveats, such as limitations acknowledged by the researchers. To get those, you need access to the studies themselves.

And it’s very common for findings and scientists to seem to contradict each other. For example, there were many contradictory findings and recommendations about the use of masks, especially at the beginning of the pandemic—though as we’ll discuss, it’s important to understand that a scientific consensus did emerge.

Given the complexities and ambiguities of the scientific endeavor, is it possible for a non-scientist to strike a balance between wholesale dismissal and uncritical belief? Are there red flags to look for when you read about a study on a site like Greater Good or hear about one on a Fox News program? If you do read an original source study, how should you, as a non-scientist, gauge its credibility?

Here are 11 questions you might ask when you read about the latest scientific findings about the pandemic, based on our own work here at Greater Good.

1. Did the study appear in a peer-reviewed journal?

In peer review, submitted articles are sent to other experts for detailed critical input that often must be addressed in a revision prior to being accepted and published. This remains one of the best ways we have for ascertaining the rigor of the study and rationale for its conclusions. Many scientists describe peer review as a truly humbling crucible. If a study didn’t go through this process, for whatever reason, it should be taken with a much bigger grain of salt.

“When thinking about the coronavirus studies, it is important to note that things were happening so fast that in the beginning people were releasing non-peer reviewed, observational studies,” says Dr. Leif Hass, a family medicine doctor and hospitalist at Sutter Health’s Alta Bates Summit Medical Center in Oakland, California. “This is what we typically do as hypothesis-generating but given the crisis, we started acting on them.”

In a confusing, time-pressed, fluid situation like the one COVID-19 presented, people without medical training have often been forced to simply defer to expertise in making individual and collective decisions, turning to culturally vetted institutions like the Centers for Disease Control (CDC). Is that wise? Read on.

2. Who conducted the study, and where did it appear?

“I try to listen to the opinion of people who are deep in the field being addressed and assess their response to the study at hand,” says Hass. “With the MRNA coronavirus vaccines, I heard Paul Offit from UPenn at a UCSF Grand Rounds talk about it. He literally wrote the book on vaccines. He reviewed what we know and gave the vaccine a big thumbs up. I was sold.”

From a scientific perspective, individual expertise and accomplishment matters—but so does institutional affiliation.

Why? Because institutions provide a framework for individual accountability as well as safety guidelines. At UC Berkeley, for example , research involving human subjects during COVID-19 must submit a Human Subjects Proposal Supplement Form , and follow a standard protocol and rigorous guidelines . Is this process perfect? No. It’s run by humans and humans are imperfect. However, the conclusions are far more reliable than opinions offered by someone’s favorite YouTuber .

Recommendations coming from institutions like the CDC should not be accepted uncritically. At the same time, however, all of us—including individuals sporting a “Ph.D.” or “M.D.” after their names—must be humble in the face of them. The CDC represents a formidable concentration of scientific talent and knowledge that dwarfs the perspective of any one individual. In a crisis like COVID-19, we need to defer to that expertise, at least conditionally.

“If we look at social media, things could look frightening,” says Hass. When hundreds of millions of people are vaccinated, millions of them will be afflicted anyway, in the course of life, by conditions like strokes, anaphylaxis, and Bell’s palsy. “We have to have faith that people collecting the data will let us know if we are seeing those things above the baseline rate.”

3. Who was studied, and where?

Animal experiments tell scientists a lot, but their applicability to our daily human lives will be limited. Similarly, if researchers only studied men, the conclusions might not be relevant to women, and vice versa.

Many psychology studies rely on WEIRD (Western, educated, industrialized, rich and democratic) participants, mainly college students, which creates an in-built bias in the discipline’s conclusions. Historically, biomedical studies also bias toward gathering measures from white male study participants, which again, limits generalizability of findings. Does that mean you should dismiss Western science? Of course not. It’s just the equivalent of a “Caution,” “Yield,” or “Roadwork Ahead” sign on the road to understanding.

This applies to the coronavirus vaccines now being distributed and administered around the world. The vaccines will have side effects; all medicines do. Those side effects will be worse for some people than others, depending on their genetic inheritance, medical status, age, upbringing, current living conditions, and other factors.

For Hass, it amounts to this question: Will those side effects be worse, on balance, than COVID-19, for most people?

“When I hear that four in 100,000 [of people in the vaccine trials] had Bell’s palsy, I know that it would have been a heck of a lot worse if 100,000 people had COVID. Three hundred people would have died and many others been stuck with chronic health problems.”

4. How big was the sample?

In general, the more participants in a study, the more valid its results. That said, a large sample is sometimes impossible or even undesirable for certain kinds of studies. During COVID-19, limited time has constrained the sample sizes.

However, that acknowledged, it’s still the case that some studies have been much larger than others—and the sample sizes of the vaccine trials can still provide us with enough information to make informed decisions. Doctors and nurses on the front lines of COVID-19—who are now the very first people being injected with the vaccine—think in terms of “biological plausibility,” as Hass says.

Did the admittedly rushed FDA approval of the Pfizer-BioNTech vaccine make sense, given what we already know? Tens of thousands of doctors who have been grappling with COVID-19 are voting with their arms, in effect volunteering to be a sample for their patients. If they didn’t think the vaccine was safe, you can bet they’d resist it. When the vaccine becomes available to ordinary people, we’ll know a lot more about its effects than we do today, thanks to health care providers paving the way.

5. Did the researchers control for key differences, and do those differences apply to you?

Diversity or gender balance aren’t necessarily virtues in experimental research, though ideally a study sample is as representative of the overall population as possible. However, many studies use intentionally homogenous groups, because this allows the researchers to limit the number of different factors that might affect the result.

While good researchers try to compare apples to apples, and control for as many differences as possible in their analyses, running a study always involves trade-offs between what can be accomplished as a function of study design, and how generalizable the findings can be.

The Science of Happiness

What does it take to live a happier life? Learn research-tested strategies that you can put into practice today. Hosted by award-winning psychologist Dacher Keltner. Co-produced by PRX and UC Berkeley’s Greater Good Science Center.

Apple Podcasts
Google Podcasts

You also need to ask if the specific population studied even applies to you. For example, when one study found that cloth masks didn’t work in “high-risk situations,” it was sometimes used as evidence against mask mandates.

However, a look beyond the headlines revealed that the study was of health care workers treating COVID-19 patients, which is a vastly more dangerous situation than, say, going to the grocery store. Doctors who must intubate patients can end up being splattered with saliva. In that circumstance, one cloth mask won’t cut it. They also need an N95, a face shield, two layers of gloves, and two layers of gown. For the rest of us in ordinary life, masks do greatly reduce community spread, if as many people as possible are wearing them.

6. Was there a control group?

One of the first things to look for in methodology is whether the population tested was randomly selected, whether there was a control group, and whether people were randomly assigned to either group without knowing which one they were in. This is especially important if a study aims to suggest that a certain experience or treatment might actually cause a specific outcome, rather than just reporting a correlation between two variables (see next point).

For example, were some people randomly assigned a specific meditation practice while others engaged in a comparable activity or exercise? If the sample is large enough, randomized trials can produce solid conclusions. But, sometimes, a study will not have a control group because it’s ethically impossible. We can’t, for example, let sick people go untreated just to see what would happen. Biomedical research often makes use of standard “treatment as usual” or placebos in control groups. They also follow careful ethical guidelines to protect patients from both maltreatment and being deprived necessary treatment. When you’re reading about studies of masks, social distancing, and treatments during the COVID-19, you can partially gauge the reliability and validity of the study by first checking if it had a control group. If it didn’t, the findings should be taken as preliminary.

7. Did the researchers establish causality, correlation, dependence, or some other kind of relationship?

We often hear “Correlation is not causation” shouted as a kind of battle cry, to try to discredit a study. But correlation—the degree to which two or more measurements seem connected—is important, and can be a step toward eventually finding causation—that is, establishing a change in one variable directly triggers a change in another. Until then, however, there is no way to ascertain the direction of a correlational relationship (does A change B, or does B change A), or to eliminate the possibility that a third, unmeasured factor is behind the pattern of both variables without further analysis.

In the end, the important thing is to accurately identify the relationship. This has been crucial in understanding steps to counter the spread of COVID-19 like shelter-in-place orders. Just showing that greater compliance with shelter-in-place mandates was associated with lower hospitalization rates is not as conclusive as showing that one community that enacted shelter-in-place mandates had lower hospitalization rates than a different community of similar size and population density that elected not to do so.

We are not the first people to face an infection without understanding the relationships between factors that would lead to more of it. During the bubonic plague, cities would order rodents killed to control infection. They were onto something: Fleas that lived on rodents were indeed responsible. But then human cases would skyrocket.

Why? Because the fleas would migrate off the rodent corpses onto humans, which would worsen infection. Rodent control only reduces bubonic plague if it’s done proactively; once the outbreak starts, killing rats can actually make it worse. Similarly, we can’t jump to conclusions during the COVID-19 pandemic when we see correlations.

8. Are journalists and politicians, or even scientists, overstating the result?

Language that suggests a fact is “proven” by one study or which promotes one solution for all people is most likely overstating the case. Sweeping generalizations of any kind often indicate a lack of humility that should be a red flag to readers. A study may very well “suggest” a certain conclusion but it rarely, if ever, “proves” it.

This is why we use a lot of cautious, hedging language in Greater Good , like “might” or “implies.” This applies to COVID-19 as well. In fact, this understanding could save your life.

When President Trump touted the advantages of hydroxychloroquine as a way to prevent and treat COVID-19, he was dramatically overstating the results of one observational study. Later studies with control groups showed that it did not work—and, in fact, it didn’t work as a preventative for President Trump and others in the White House who contracted COVID-19. Most survived that outbreak, but hydroxychloroquine was not one of the treatments that saved their lives. This example demonstrates how misleading and even harmful overstated results can be, in a global pandemic.

9. Is there any conflict of interest suggested by the funding or the researchers’ affiliations?

A 2015 study found that you could drink lots of sugary beverages without fear of getting fat, as long as you exercised. The funder? Coca Cola, which eagerly promoted the results. This doesn’t mean the results are wrong. But it does suggest you should seek a second opinion : Has anyone else studied the effects of sugary drinks on obesity? What did they find?

It’s possible to take this insight too far. Conspiracy theorists have suggested that “Big Pharma” invented COVID-19 for the purpose of selling vaccines. Thus, we should not trust their own trials showing that the vaccine is safe and effective.

But, in addition to the fact that there is no compelling investigative evidence that pharmaceutical companies created the virus, we need to bear in mind that their trials didn’t unfold in a vacuum. Clinical trials were rigorously monitored and independently reviewed by third-party entities like the World Health Organization and government organizations around the world, like the FDA in the United States.

Does that completely eliminate any risk? Absolutely not. It does mean, however, that conflicts of interest are being very closely monitored by many, many expert eyes. This greatly reduces the probability and potential corruptive influence of conflicts of interest.

10. Do the authors reference preceding findings and original sources?

The scientific method is based on iterative progress, and grounded in coordinating discoveries over time. Researchers study what others have done and use prior findings to guide their own study approaches; every study builds on generations of precedent, and every scientist expects their own discoveries to be usurped by more sophisticated future work. In the study you are reading, do the researchers adequately describe and acknowledge earlier findings, or other key contributions from other fields or disciplines that inform aspects of the research, or the way that they interpret their results?

Greater Good’s Guide to Well-Being During Coronavirus

Practices, resources, and articles for individuals, parents, and educators facing COVID-19

This was crucial for the debates that have raged around mask mandates and social distancing. We already knew quite a bit about the efficacy of both in preventing infections, informed by centuries of practical experience and research.

When COVID-19 hit American shores, researchers and doctors did not question the necessity of masks in clinical settings. Here’s what we didn’t know: What kinds of masks would work best for the general public, who should wear them, when should we wear them, were there enough masks to go around, and could we get enough people to adopt best mask practices to make a difference in the specific context of COVID-19 ?

Over time, after a period of confusion and contradictory evidence, those questions have been answered . The very few studies that have suggested masks don’t work in stopping COVID-19 have almost all failed to account for other work on preventing the disease, and had results that simply didn’t hold up. Some were even retracted .

So, when someone shares a coronavirus study with you, it’s important to check the date. The implications of studies published early in the pandemic might be more limited and less conclusive than those published later, because the later studies could lean on and learn from previously published work. Which leads us to the next question you should ask in hearing about coronavirus research…

11. Do researchers, journalists, and politicians acknowledge limitations and entertain alternative explanations?

Is the study focused on only one side of the story or one interpretation of the data? Has it failed to consider or refute alternative explanations? Do they demonstrate awareness of which questions are answered and which aren’t by their methods? Do the journalists and politicians communicating the study know and understand these limitations?

When the Annals of Internal Medicine published a Danish study last month on the efficacy of cloth masks, some suggested that it showed masks “make no difference” against COVID-19.

The study was a good one by the standards spelled out in this article. The researchers and the journal were both credible, the study was randomized and controlled, and the sample size (4,862 people) was fairly large. Even better, the scientists went out of their way to acknowledge the limits of their work: “Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others.”

Unfortunately, their scientific integrity was not reflected in the ways the study was used by some journalists, politicians, and people on social media. The study did not show that masks were useless. What it did show—and what it was designed to find out—was how much protection masks offered to the wearer under the conditions at the time in Denmark. In fact, the amount of protection for the wearer was not large, but that’s not the whole picture: We don’t wear masks mainly to protect ourselves, but to protect others from infection. Public-health recommendations have stressed that everyone needs to wear a mask to slow the spread of infection.

“We get vaccinated for the greater good, not just to protect ourselves ”

As the authors write in the paper, we need to look to other research to understand the context for their narrow results. In an editorial accompanying the paper in Annals of Internal Medicine , the editors argue that the results, together with existing data in support of masks, “should motivate widespread mask wearing to protect our communities and thereby ourselves.”

Something similar can be said of the new vaccine. “We get vaccinated for the greater good, not just to protect ourselves,” says Hass. “Being vaccinated prevents other people from getting sick. We get vaccinated for the more vulnerable in our community in addition for ourselves.”

Ultimately, the approach we should take to all new studies is a curious but skeptical one. We should take it all seriously and we should take it all with a grain of salt. You can judge a study against your experience, but you need to remember that your experience creates bias. You should try to cultivate humility, doubt, and patience. You might not always succeed; when you fail, try to admit fault and forgive yourself.

Above all, we need to try to remember that science is a process, and that conclusions always raise more questions for us to answer. That doesn’t mean we never have answers; we do. As the pandemic rages and the scientific process unfolds, we as individuals need to make the best decisions we can, with the information we have.

This article was revised and updated from a piece published by Greater Good in 2015, “ 10 Questions to Ask About Scientific Studies .”

About the Authors

Jeremy Adam Smith

Uc berkeley.

Jeremy Adam Smith edits the GGSC’s online magazine, Greater Good . He is also the author or coeditor of five books, including The Daddy Shift , Are We Born Racist? , and (most recently) The Gratitude Project: How the Science of Thankfulness Can Rewire Our Brains for Resilience, Optimism, and the Greater Good . Before joining the GGSC, Jeremy was a John S. Knight Journalism Fellow at Stanford University.

Emiliana R. Simon-Thomas

Emiliana R. Simon-Thomas, Ph.D. , is the science director of the Greater Good Science Center, where she directs the GGSC’s research fellowship program and serves as a co-instructor of its Science of Happiness and Science of Happiness at Work online courses.

You May Also Enjoy

Why Is COVID-19 Killing So Many Black Americans?

How Does COVID-19 Affect Trust in Government?

Why Your Sacrifices Matter During the Pandemic

How to Form a Pandemic Pod

In a Pandemic, Elbow Touches Might Keep Us Going

How to Keep the Greater Good in Mind During the Coronavirus Outbreak

Disclaimer » Advertising

HealthyChildren.org

Prevaccine and Vaccine-Era Disease Estimates

Hepatitis a, hepatitis b, haemophilus influenzae type b, measles, mumps, and rubella, streptococcus pneumoniae, conclusions, acknowledgments, impact of routine childhood immunization in reducing vaccine-preventable diseases in the united states.

Split-Screen
Article contents
Figures & tables
Supplementary Data
Peer Review
CME Quiz Close Quiz
Open the PDF for in another window
Get Permissions
Cite Icon Cite
Search Site

Sandra E. Talbird , Justin Carrico , Elizabeth M. La , Cristina Carias , Gary S. Marshall , Craig S. Roberts , Ya-Ting Chen , Mawuli K. Nyaku; Impact of Routine Childhood Immunization in Reducing Vaccine-Preventable Diseases in the United States. Pediatrics August 2022; 150 (3): e2021056013. 10.1542/peds.2021-056013

Download citation file:

Ris (Zotero)
Reference Manager

Current routine immunizations for children aged ≤10 years in the United States in 2019 cover 14 vaccine-preventable diseases. We characterize the public-health impact of vaccination by providing updated estimates of disease incidence with and without universally recommended pediatric vaccines.

Prevaccine disease incidence was obtained from published data or calculated using annual case estimates from the prevaccine period and United States population estimates during the same period. Vaccine-era incidence was calculated as the average incidence over the most recent 5 years of available surveillance data or obtained from published estimates (if surveillance data were not available). We adjusted for underreporting and calculated the percent reduction in overall and age-specific incidence for each disease. We multiplied prevaccine and vaccine-era incidence rates by 2019 United States population estimates to calculate annual number of cases averted by vaccination.

Routine immunization reduced the incidence of all targeted diseases, leading to reductions in incidence ranging from 17% (influenza) to 100% (diphtheria, Haemophilus influenzae type b, measles, mumps, polio, and rubella). For the 2019 United States population of 328 million people, these reductions equate to >24 million cases of vaccine-preventable disease averted. Vaccine-era disease incidence estimates remained highest for influenza (13 412 per 100 000) and Streptococcus pneumoniae -related acute otitis media (2756 per 100 000).

Routine childhood immunization in the United States continues to yield considerable sustained reductions in incidence across all targeted diseases. Efforts to maintain and improve vaccination coverage are necessary to continue experiencing low incidence levels of vaccine-preventable diseases.

The United States childhood vaccination program has dramatically reduced morbidity, mortality, and disability for targeted diseases. Updated estimates of disease incidence and cases averted, reflecting changes in disease epidemiology, vaccine utilization, and vaccine recommendations (based on the 2017 to 2021 schedule), are needed.

The childhood vaccination program reduced the incidence of all targeted diseases—with reductions ranging from 17% (influenza) to 100% (diphtheria, Haemophilus influenzae type b, measles, mumps, polio, and rubella)—and averted >24 million disease cases for the 2019 United States population.

Childhood vaccination has dramatically reduced morbidity, mortality, and disability caused by vaccine-preventable diseases, with ∼21 million hospitalizations, 732 000 deaths, and 322 million cases of disease averted in the United States between 1994 and 2013. 1 Among diseases targeted by vaccines recommended before 1980, 3—polio, measles, and rubella—have achieved elimination status as defined by the World Health Organization 2 and 1—smallpox—has been eradicated. 3 Diphtheria and tetanus have declined markedly in incidence with routine immunization and are well controlled, 2 whereas the incidence of pertussis and mumps has declined when compared with prevaccine levels but still fluctuates given periodic outbreaks since vaccination was introduced. 3 The public health burden of diseases targeted in the childhood immunization program between 1980 and 2005, including hepatitis A, hepatitis B, invasive Haemophilus influenzae type b (Hib), varicella, and invasive pneumococcal disease (IPD), has decreased by more than 80% 3 ; reductions in related nontargeted diseases (eg, acute otitis media caused by Streptococcus pneumoniae ) have also been observed. 4 After 2005, the routine immunization schedule 5 for United States children ≤10 years of age targeted additional pathogens, such as rotavirus and further pneumococcal serotypes. 5

This study updates estimates of the reduction in overall and age-specific disease incidence associated with the routine childhood immunization program in the United States (based on the 2017 to 2021 vaccination schedule). This update incorporates changes in vaccine utilization rates and observed incidence of the targeted vaccine-preventable diseases since previous evaluations. 3 , 6 The present analysis will be of interest to policy makers, public health decision makers, and modelers concerned with public health interventions to minimize the burden of vaccine-preventable diseases. A companion study evaluated the value of the childhood immunization program for the 2017 United States birth cohort. 7

We estimated the epidemiologic impact of the United States routine childhood immunization program (ages ≤10 years) by calculating the percent reduction in overall and age-specific disease incidence rates for each disease targeted by the program. We multiplied the prevaccine and vaccine-era incidence rates (using age-specific data, where available) by 2019 United States population estimates, 8 accounting for underreporting where necessary, to calculate the 2019 clinical disease burden with and without childhood immunization and to estimate the cases averted by vaccination. As in previous studies, we assumed that the difference between incidence rates during these periods was entirely attributable to the childhood immunization program. 3 , 6

For the prevaccine period, we estimated disease incidence using published incidence estimates or calculated incidence using published annual case estimates and United States population data from the same period. For the vaccine era, we calculated incidence as the average incidence over the most recent 5 years of available surveillance data; we used published incidence estimates if surveillance data were not available. For both periods, we accounted for underreporting where necessary.

Table 1 summarizes the prevaccine and vaccine-era disease incidence sources. Age-specific incidence data were used for all diseases except diphtheria, polio, tetanus, and rotavirus. Incidence of Hib and rotavirus was limited to ages <5 years and diphtheria to ages ≤10 years, given lack of data in older age groups in the prevaccine period and the fact that clinical burden was largely limited to those age groups in both periods. Incidence of measles, mumps, and rubella was included only up to age 40 years, as prevaccine incidence data in ages ≥40 years was unavailable. For pneumococcal pneumonia, pneumococcal acute otitis media (AOM), and rotavirus, resource use estimates (ie, hospitalizations, emergency department [ED] visits, and outpatient visits) are reported instead of incidence and disease cases because of limitations in the source data.

Summary of Prevaccine and Vaccine-Era Disease Incidence Sources

Disease .	Dates of Vaccination Program Initiation .	Prevaccine Source .	Vaccine-Era Source .
Diphtheria	1928–1943	Zhou et al citing Ekwueme et al	2014–2018 NNDSS –
Hepatitis A	1995	1990–1994 NNDSS –	2014–2018 NNDSS –
Hepatitis B	1981, 1986	1976–1980 NNDSS –	2014–2018 NNDSS –
type b	1985, 1987, 1990	Zhou et al based on incidence data from 1976–1984	2013–2017 ABC surveillance reports –
Influenza	1945	Calculated based on CDC estimated cases and cases averted for seasons 2014–2015 through 2018–2019 – and US population size for ages <5 and 5–10 y	Calculated based on CDC estimated cases for seasons 2014–2015 through 2018–2019 – and US population size for ages <5 and 5–10 y
Measles	1963, 1967, 1968	Zhou et al	2014–2018 NNDSS –
Mumps	1940s, 1967	Zhou et al	2014–2018 NNDSS –
Pertussis	1914–1941	Age <11 y: Zhou et al citing Ekwueme et al ; Age ≥11 y: Roush and Murphy and Cherry , ,	2014–2018 NNDSS –
	2000
IPD		1997–1999 ABC surveillance reports –	2013–2017 ABC surveillance reports –
All-cause pneumonia hospitalizations		Griffin et al based on data from 1997–1999	Tong et al based on data from 2014
All-cause pneumonia outpatient visits		Age <18 y: Kronman et al based on data from 1998–1999; Age ≥18 y: Nelson et al based on data from 1998–2000	Tong et al based on data from 2014
Pneumococcal pneumonia (inpatient and outpatient)		Percent caused by pneumococcus: Age <18 y: 34% from Wahl et al ; Age ≥18 y: 27% from Said et al	Percent caused by pneumococcus: Age <18 y: 4% from Jain et al ; Age ≥18 y: 7% from Isturiz et al
All-cause AOM outpatient visits		Kawai et al based on data from 1997–1999	Kawai et al based on data from 2012–2014
Pneumococcal AOM outpatient visits		Percent caused by pneumococcus (44%) from Kaur et al based on data from 1995–2001	Percent caused by pneumococcus (21%) from Kaur et al based on data from 2010–2016
Polio	1955, 1961–1963, 1987	Calculated based on 1951–1954 cases from Roush and Murphy ,	2014–2018 NNDSS –
Rotavirus	1998 (first licensed but withdrawn); 2006	Calculated based on 1993–2002 cumulative risk of event (hospitalization, ED visit, outpatient visit) by age 59 mo without vaccine from Widdowson et al	Calculated based on prevaccine incidence from Widdowson et al and % reduction in events with vaccine from Getachew et al and Krishnarajah et al
Rubella	1969	Zhou et al	2014–2018 NNDSS –
Tetanus	1933–1949	Calculated based on 1947–1949 cases from Roush and Murphy	2014–2018 NNDSS –
Varicella	1995	1990–1994 NNDSS – ,	2014–2018 NNDSS –

Disease .	Dates of Vaccination Program Initiation .	Prevaccine Source .	Vaccine-Era Source .
Diphtheria	1928–1943	Zhou et al citing Ekwueme et al	2014–2018 NNDSS –
Hepatitis A	1995	1990–1994 NNDSS –	2014–2018 NNDSS –
Hepatitis B	1981, 1986	1976–1980 NNDSS –	2014–2018 NNDSS –
type b	1985, 1987, 1990	Zhou et al based on incidence data from 1976–1984	2013–2017 ABC surveillance reports –
Influenza	1945	Calculated based on CDC estimated cases and cases averted for seasons 2014–2015 through 2018–2019 – and US population size for ages <5 and 5–10 y	Calculated based on CDC estimated cases for seasons 2014–2015 through 2018–2019 – and US population size for ages <5 and 5–10 y
Measles	1963, 1967, 1968	Zhou et al	2014–2018 NNDSS –
Mumps	1940s, 1967	Zhou et al	2014–2018 NNDSS –
Pertussis	1914–1941	Age <11 y: Zhou et al citing Ekwueme et al ; Age ≥11 y: Roush and Murphy and Cherry , ,	2014–2018 NNDSS –
	2000
IPD		1997–1999 ABC surveillance reports –	2013–2017 ABC surveillance reports –
All-cause pneumonia hospitalizations		Griffin et al based on data from 1997–1999	Tong et al based on data from 2014
All-cause pneumonia outpatient visits		Age <18 y: Kronman et al based on data from 1998–1999; Age ≥18 y: Nelson et al based on data from 1998–2000	Tong et al based on data from 2014
Pneumococcal pneumonia (inpatient and outpatient)		Percent caused by pneumococcus: Age <18 y: 34% from Wahl et al ; Age ≥18 y: 27% from Said et al	Percent caused by pneumococcus: Age <18 y: 4% from Jain et al ; Age ≥18 y: 7% from Isturiz et al
All-cause AOM outpatient visits		Kawai et al based on data from 1997–1999	Kawai et al based on data from 2012–2014
Pneumococcal AOM outpatient visits		Percent caused by pneumococcus (44%) from Kaur et al based on data from 1995–2001	Percent caused by pneumococcus (21%) from Kaur et al based on data from 2010–2016
Polio	1955, 1961–1963, 1987	Calculated based on 1951–1954 cases from Roush and Murphy ,	2014–2018 NNDSS –
Rotavirus	1998 (first licensed but withdrawn); 2006	Calculated based on 1993–2002 cumulative risk of event (hospitalization, ED visit, outpatient visit) by age 59 mo without vaccine from Widdowson et al	Calculated based on prevaccine incidence from Widdowson et al and % reduction in events with vaccine from Getachew et al and Krishnarajah et al
Rubella	1969	Zhou et al	2014–2018 NNDSS –
Tetanus	1933–1949	Calculated based on 1947–1949 cases from Roush and Murphy	2014–2018 NNDSS –
Varicella	1995	1990–1994 NNDSS – ,	2014–2018 NNDSS –

ABC, Active Bacterial Core; AOM, acute otitis media; CDC, Centers for Disease Control and Prevention; ED, emergency department; IPD, invasive pneumococcal disease; NNDSS, National Notifiable Diseases Surveillance System.

Dates of immunization program initiation correspond to dates of vaccine licensure and/or routine recommended use. 3 , 96 For additional details on vaccines with multiple dates listed, please see Roush and Murphy 3 and Widdowson et al. 76

Prevaccine pertussis incidence estimates for ages >10 y were estimated from all cases reported by Roush and Murphy, 3 adjusted to account for the estimate from Cherry 95 that approximately 93% of pertussis infections in the first half of the 20th century were among ages <10 y.

An underreporting factor of 10 was taken from economic evaluations and burden-of-illness studies 53 – 55 and was multiplied by prevaccine pertussis incidence in ages >10 y and vaccine-era pertussis incidence for all ages; prevaccine incidence from birth to age 10 y (taken from Zhou et al) already accounted for underreporting. 9 This underreporting factor is conservative compared with previous studies that have tested underreporting of pertussis up to 100 to 200 times reported cases among adolescents and adults. 53 , 55 , 56

A prevaccine underreporting factor was calculated based on an estimated 48% of notifiable polio cases being paralytic in 1954. 74 This implied underreporting factor (1 of 0.48 = 2.1 cases per reported case) was used to calculate the estimated total number of notifiable polio cases (both paralytic and nonparalytic) based on the incidence of paralytic polio reported by Baicus. 75

The prevaccine underreporting factor (22.2) was calculated from the 1994 NNDSS report, 20 which reported that approximately 3.7 million cases of varicella occurred annually prevaccine, with 4% to 5% of cases reported. 11 – 15

Because cases of varicella were not reported by age in 2014 and 2015, the total cases were distributed by age using the same age distribution of cases from 2016 when calculating the age-specific 5-year incidence rate. The vaccine-era underreporting factor (10.4) was calculated based on the underreporting factor used by Roush and Murphy 3 (12.7 = 612 768 cases estimated of 48 445 cases reported by 33 states in 2006), adjusted for 40 states reporting varicella cases in 2015 versus 33 states in 2006 (12.7 × 33/40 = 10.4).

We obtained prevaccine diphtheria disease incidence for children aged ≤10 years from an economic evaluation by Zhou et al, 9 which estimated incidence from a 1916 to 1919 survey of childhood vaccine-preventable diseases in 31 353 United States children and physician-reported data. 10 We assumed the incidence reported by Zhou et al 9 for ages 5 to 9 years uniformly applied to all children ≤10 years. We calculated vaccine-era incidence among children aged ≤10 years as the average value over the most recent 5 years (2014 to 2018) of available data from the Centers for Disease Control and Prevention (CDC) National Notifiable Disease Surveillance System (NNDSS) reports. 11 – 15

We calculated prevaccine hepatitis A incidence using the average number of reported cases between 1990 and 1994 from the NNDSS 16 – 20 divided by the 1994 United States population for each respective age group. 21 We calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15 A systematic review and meta-analysis of underreporting of hepatitis A in nonendemic countries found that reported hepatitis A cases ranged from 4% to 97% of total estimated cases across 8 included studies, with a pooled proportion of 59%. 22 As a result, an underreporting factor of 1.7 (1/59% = 1.7) was applied for prevaccine and vaccine-era estimates, 22 which is similar to underreporting factors found in other studies. 23

We estimated prevaccine hepatitis B incidence as the average number of reported cases between 1976 and 1980 from the NNDSS 24 – 28 and calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15 The underreporting factor for hepatitis B (6.5) was obtained from a probabilistic model estimating underreporting of hepatitis A, B, and C. 23

We obtained prevaccine disease incidence for Hib for children aged <5 years for 1976 to 1984 from an economic analysis by Zhou et al. 29 We calculated overall incidence by summing the incidence values reported separately for Hib-related meningitis, epiglottitis, bacteremia, pneumonia, cellulitis, arthritis, and other invasive diseases reported in Zhou et al. 29 We calculated vaccine-era incidence among children aged <5 years as the average value over the most recent 5 years (2013–2017) of available data from CDC Active Bacterial Core (ABC) surveillance reports. 30 – 34

For influenza, instead of using data from the period before influenza vaccines were routinely recommended, we estimated prevaccine incidence among children aged ≤10 years by using the number of cases and averted cases estimated by the CDC, assuming all averted cases would have occurred without vaccination. 35 – 42 Specifically, we summed the number of reported cases to the cases averted by vaccination among children <5 years and children aged 5 to 10 years for 5 recent influenza seasons (2014–2015 to 2018–2019) and then divided the total number of cases by the number of children in the United States in each respective age group for the same period. 8 An average incidence across the 5 years was then calculated for both age groups. For vaccine-era incidence, we used the same source and calculated the average incidence over the same 5 recent seasons (2014–2015 to 2018–2019). Our analyses did not account for the impact of adolescent and adult influenza vaccination or herd immunity in older age groups; therefore, incidence of influenza was restricted to ages ≤10 years, and we attributed all changes in incidence to vaccination in this age cohort.

For measles, mumps, and rubella, we obtained prevaccine disease incidence from Zhou et al. 43 – 47 For the vaccine era, we calculated incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15

We estimated prevaccine pertussis incidence for birth to 10 years from 2 economic evaluations of diphtheria, tetanus, and acellular pertussis vaccine, which derived age-specific risk of pertussis from United States data in the 1920s and from Sweden in the 1980s. 9 , 48 Prevaccine incidence for ages >10 years was calculated using the number of reported pertussis cases estimated by Roush and Murphy 3 for ages >10 years during 1934 to 1943 (before the start of routine pertussis vaccination in the late 1940s) divided by the size of the United States population >10 years old over the same period. 49 , 50 We calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15 An underreporting factor of 10 was applied in the prevaccine and vaccine eras ( Table 1 ). 51 – 56

For IPD, we calculated prevaccine disease incidence as the average value from the 1997 to 1999 ABC surveillance reports 57 – 59 and calculated vaccine-era incidence as the average value from the 2013 to 2017 ABC surveillance reports. 60 – 64

For pneumococcal pneumonia, we obtained prevaccine, age-specific, all-cause pneumonia hospitalization rates per 100 000 for the period 1997 to 1999 65 and all-cause outpatient visit rates per 100 000 for the period 1998 to 2000 66 , 67 ( Table 1 ). For the vaccine era, we used the incidence of all-cause pneumonia from 2014 based on an analysis of a large convenience insurance claims dataset (MarketScan) multiplied by the percentage hospitalized or treated in an outpatient or ED setting taken from the same study. 68 We multiplied the all-cause rates by the prevaccine 69 , 70 and postvaccine 71 , 72 percentage of all-cause pneumonia caused by pneumococcus ( Table 1 ).

For pneumococcal AOM, we used prevaccine, age-specific incidence from 1997 to 1999 and vaccine-era incidence from 2012 to 2014 from a retrospective analysis of the National Ambulatory Medical Care Survey comparing ambulatory visit rates before the introduction of 7-valent and following 13-valent pneumococcal conjugate vaccine. 4 We summed annual rates of physician office, hospital outpatient, and hospital ED visits to calculate a total annual ambulatory visit rate per 1000 children. To calculate pneumococcal AOM burden for each period, we multiplied all-cause rates by the percentage of AOM caused by pneumococcus in the prevaccine period (1995 to 2001) (44%) and vaccine era (2010 to 2016) (21%). 73

For polio, we obtained the average number of paralytic poliomyelitis cases for the period 1951 to 1954 (before the introduction of the first polio vaccine in 1955) from Roush and Murphy 3 . We divided the total number of cases by the average United States population size from 1951 to 1954 to estimate an overall incidence rate. 49 Age-specific data were not available in the prevaccine period; therefore, the same incidence rate was used for all ages. A prevaccine underreporting factor of 2.1 was applied ( Table 1 ). 74 , 75 We calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15

We calculated prevaccine estimates of rotavirus-related burden among children aged <5 years using 1993 to 2002 data on the cumulative individual risk of event by age 59 months for events including hospitalizations, ED visits, and hospital or ambulatory outpatient visits. 76 The median values were used to calculate annual probabilities of each type of rotavirus-related resource use. We further assumed rotavirus events were uniformly distributed from birth to age 5 years ( Supplemental Table 3 ). In the vaccine era, we calculated rotavirus-related burden by multiplying prevaccine event rates by the estimated reduction in hospitalizations 77 and reduction in ED and outpatient visits. 78

We calculated prevaccine tetanus incidence based on the number of cases reported during 1947 to 1949 (before routine vaccination began in the late 1940s 3 ) divided by the average size of the United States population during that same period. 49 Data were not available by age in the prevaccine period; therefore, the same incidence rate was used across all ages in the model. We calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15

We calculated prevaccine varicella incidence using the average number of reported varicella cases between 1990 and 1994 (before vaccine introduction in 1995) from the NNDSS 16 – 20 divided by the 1994 United States population for each respective age group. 20 , 21 We calculated vaccine-era incidence as the average value over the most recent 5 years (2014 to 2018) of available data from the NNDSS. 11 – 15 Underreporting factors of 22.2 and 10.4 were applied to prevaccine and vaccine-era incidence, respectively ( Table 1 ). 3 , 20

We report calculated incidence overall and by age for both the prevaccine and 2019 vaccine-era periods. We calculated the percent reduction in incidence overall and by age group for each disease by comparing the 2 periods. Using 2019 United States population estimates from the United States Census Bureau, we calculated the number of cases of each disease that would be expected in 2019 without and with the routine childhood immunization program and the number of cases of disease averted.

For infants (<1 year), prevaccine annual incidence per 100 000 was highest for pneumococcal AOM (49 324), influenza (18 903), measles (9200), and pertussis (4720) ( Supplemental Tables 3 – 5 ). For young children (ages 1 to 4 years), as for infants, incidence in the prevaccine period was highest for pneumococcal AOM (15 004–49 324), influenza (18 903), measles (10 641–11 503), and pertussis (4720), as well as for varicella (4519). For school-aged children (ages 5–18 years), prevaccine incidence varied by age group but was highest for influenza (14 066), varicella (389–6480), pneumococcal AOM (4840), and pertussis (131–4720). For adults, prevaccine incidence was highest for pneumococcal pneumonia (29–1553), rubella (300), mumps (99–256), and pertussis (131).

After vaccines were introduced, incidence decreased for all diseases evaluated ( Fig 1 ; Table 2 ). Incidence was reduced to less than 1 per 100 000 for 6 of the diseases: diphtheria, Hib, measles, polio, rubella, and tetanus. The incidence of mumps was reduced by >99% and varicella by 98%. The incidence of rotavirus-related hospitalizations among children aged <5 years was reduced by 91%; a lower reduction was observed for rotavirus-related ED visits (61%) and outpatient visits (45%). The incidence of pertussis was reduced by 91%, hepatitis A by 87%, hepatitis B by 86%, and IPD by 60%. Pneumococcal pneumonia hospitalization rates and outpatient visit rates decreased by 84% and 69%, respectively, and incidence of pneumococcal AOM decreased by 75%. The incidence of influenza among people aged <11 years was reduced by 17%.

Percentage reduction in disease incidence in the vaccine era by disease. Percentage reduction for rotavirus is hospitalizations. IPD does not include pneumococcal pneumonia or acute otitis media. Percentage reductions in disease incidence round up to 100% for several diseases, although there are still some cases in the vaccine era ( Table 2 ). IPD, invasive pneumococcal disease.

Prevaccine and Vaccine-Era Disease Incidence Estimates, Annual Cases, and 2019 Cases Averted in the United States by Disease

Disease .	Without Immunization .		With Immunization .		Cases Averted (2019) .
Disease .	Prevaccine Disease Incidence per 100 000 .	Annual Cases (2019) .	Vaccine-Era Disease Incidence per 100 000 .	Annual Cases (2019) .	Cases Averted (2019) .
Diphtheria	600	263 000	<1	<1	263 000
Hepatitis A	17	56 000	2	7000	49 000
Hepatitis B	46	150 000	7	22 000	128 000
type b	92	18 000	<1	<100	18 000
Influenza	1 232	7 115 000	13 412	5 879 000	1 236 000
Measles	2129	3 639 000	<1	<1000	3 639 000
Mumps	1312	2 243 000	2	3000	2 240 000
Pertussis	744	2 442 000	66	217 000	2 225 000

IPD	24	79 000	10	31 000	48 000
Pneumonia hospitalizations	152	500 000	24	78 000	422 000
Pneumonia outpatient visits	282	927 000	88	289 000	638 000
AOM	11 141	8 138 000	2756	2 013 000	6 124 000
Polio	21	70 000	0	0	70 000
Rotavirus
Hospitalizations	340	67 000	29	6000	61 000
ED visits	1072	210 000	420	82 000	128 000
Outpatient visits	2228	436 000	1222	239 000	197 000
Rubella	1124	1 921 000	<1	<10	1 921 000
Tetanus	<1	1000	<1	<100	1000
Varicella	1328	4 359 000	30	97 000	4 262 000

Disease .	Without Immunization .		With Immunization .		Cases Averted (2019) .
Disease .	Prevaccine Disease Incidence per 100 000 .	Annual Cases (2019) .	Vaccine-Era Disease Incidence per 100 000 .	Annual Cases (2019) .	Cases Averted (2019) .
Diphtheria	600	263 000	<1	<1	263 000
Hepatitis A	17	56 000	2	7000	49 000
Hepatitis B	46	150 000	7	22 000	128 000
type b	92	18 000	<1	<100	18 000
Influenza	1 232	7 115 000	13 412	5 879 000	1 236 000
Measles	2129	3 639 000	<1	<1000	3 639 000
Mumps	1312	2 243 000	2	3000	2 240 000
Pertussis	744	2 442 000	66	217 000	2 225 000

IPD	24	79 000	10	31 000	48 000
Pneumonia hospitalizations	152	500 000	24	78 000	422 000
Pneumonia outpatient visits	282	927 000	88	289 000	638 000
AOM	11 141	8 138 000	2756	2 013 000	6 124 000
Polio	21	70 000	0	0	70 000
Rotavirus
Hospitalizations	340	67 000	29	6000	61 000
ED visits	1072	210 000	420	82 000	128 000
Outpatient visits	2228	436 000	1222	239 000	197 000
Rubella	1124	1 921 000	<1	<10	1 921 000
Tetanus	<1	1000	<1	<100	1000
Varicella	1328	4 359 000	30	97 000	4 262 000

Annual cases are rounded to the nearest thousand. AOM, acute otitis media; ED, emergency department; IPD, invasive pneumococcal disease.

Incidence estimates are adjusted by underreporting factors of 1.7 for hepatitis A, 6.5 for hepatitis B, 10.0 for pertussis (in ages 11 y and older prevaccine and all ages in the vaccine era), 2.1 for polio prevaccine (to capture paralytic and nonparalytic cases), 22.2 for varicella prevaccine, and 10.4 for varicella in the vaccine era (with all other diseases assumed fully reported and/or already adjusted to account for underreporting from the source data).

Prevaccine and vaccine-era case estimates are calculated using 2019 United States population estimates and are rounded to the nearest thousand. For Haemophilus influenzae type b and rotavirus, the population size for ages <5 y ( n = 19 576 683) was used to calculate annual cases. Annual cases for diphtheria and influenza were calculated using the population size for ages ≤10 y ( n = 43 833 518). The population size for ages <40 y ( n = 170 936 198) was used to calculate annual cases for measles, mumps, and rubella. For all other diseases, the total United States population size ( n = 328 239 523) was used to calculate annual prevaccine and vaccine-era cases.

Rotavirus and pneumococcal disease results are shown separately by healthcare resource use because of a lack of incidence data.

The calculated value for cases averted may not precisely equal the difference between the number of cases in the “with immunization” and “without immunization” period because of rounding.

For the 2019 United States population of 328 million people, the number of cases of each disease without and with the childhood immunization program and the estimated number of cases averted are shown in Table 2 . In the vaccine era with routine immunization, the annual number of cases of disease was 0 for polio, <10 cases per year for diphtheria and rubella, and <100 cases per year for Hib and tetanus. Pneumococcal AOM and influenza represented the largest clinical burden annually (>1 000 000 cases per year), followed by pertussis, pneumococcal pneumonia, outpatient rotavirus gastroenteritis, and outpatient varicella (between 100 000 and 1 million cases per year).

Routine immunization was estimated to avert over 24 million cases of vaccine-preventable disease in 2019 across all age groups, ranging from approximately 1000 cases of tetanus averted to more than 4.2 million varicella cases averted ( Table 2 ). Cases averted were greatest (>1 000 000) for influenza, measles, mumps, rubella, pertussis, varicella, and outpatient visits for pneumococcal AOM.

This analysis found that routine childhood immunization in the United States has continued to reduce the incidence of all targeted diseases. Landmark achievements have been the reduction in incidence of diphtheria, Hib, measles, polio, rubella, and tetanus to negligible levels (<1 case per 100 000 population annually); and >90% reduction in incidence for 10 diseases targeted by the routine childhood immunization program for children ≤10 years of age. These reductions equate to the prevention of over 24 million cases of disease for the 2019 US population.

Roush and Murphy 3 evaluated the impact of routine childhood immunization on vaccine-preventable diseases for which recommendations were in place before 2005, using 2006 disease data. Our estimates were generally consistent with the previous results and other published studies, 79 although we estimated a greater reduction in incidence of IPD (60% versus 34%) and of varicella (98% versus 85%). A potential explanation for these differences may be that our analysis used vaccine-era incidence from 2013 to 2017 for pneumococcal disease and from 2014 to 2018 for varicella, capturing the greater impact of the 13-valent pneumococcal conjugate vaccine (recommended in 2010 for infants) compared with the 7-valent pneumococcal conjugate vaccine and capturing the greater impact of 2-dose varicella vaccine compared with 1 dose (second dose added to recommendations in 2007). 80

With sustained vaccine coverage at levels greater than 80% for most pediatric vaccines (with the exception of hepatitis A, rotavirus, and annual influenza vaccine), many vaccine-preventable diseases are now controlled as a public health problem or eliminated in the United States. However, despite significant impact of vaccines, continued risk from these vaccine-preventable diseases remains. When whole-cell pertussis vaccine was withdrawn in Sweden in 1979 because of concerns about safety and efficacy, incidence rates of pertussis similar to those observed in the prevaccine era returned in Sweden within a few years; after introduction of the diphtheria, tetanus, and acellular pertussis vaccine in 1996, incidence rates decreased markedly compared with the 1986 to 1995 10-year period. 81 , 82 Similarly, despite elimination status being declared for measles in 2000, under-vaccination has led to continued measles outbreaks in the United States, jeopardizing elimination status for the disease. 83 – 85 Diphtheria outbreaks continue to occur where vaccination rates are low, particularly in areas of social disruption, and are often associated with high rates of mortality. 86 , 87 The most recent large outbreak occurred in Russia from 1990 to 1997, resulting in ∼115 000 cases and 3000 deaths across the population. 88 These experiences underscore the importance of continued immunization in sustaining reductions in incidence of infectious diseases.

This analysis includes some limitations. First, consistent with previous studies, 3 , 6 the analysis does not directly account for other public health measures (eg, better sanitation, healthcare access, and improved standards of care) that have been introduced over the past 70 years and likely contributed to the reduction in vaccine-preventable diseases. Furthermore, this analysis did not account for random error in the parameter estimates or account for the proportion of disease incidence reduction that may be attributed to adolescent and adult vaccines or to booster doses. As a result, the analysis may overestimate reductions in burden directly attributable to childhood immunization. Future analyses could address these methodological limitations using time-series analysis to identify and adjust for trends to explore the extent to which adolescent and adult vaccination programs, which have expanded since 2005, 80 , 89 , 90 contribute to reduction in disease incidence.

Second, owing to limited data on differences among racial and ethnic groups, this analysis did not account for racial or ethnic disparities in vaccine coverage and incidence of vaccine-preventable diseases. Evaluating the public health impact of routine immunization among racial and ethnic groups is an important direction for future research. Moreover, this analysis was limited in scope to vaccine-preventable disease for vaccines included in the United States routine childhood immunization program for children ages ≤10 years. Expansion of this analysis to include vaccine-preventable diseases, such as meningococcus and human papillomavirus targeted by routine adolescent vaccines, is another potential area of future research.

Third, because annual incidence varies substantially from year to year for many vaccine-preventable diseases, we have calculated prevaccine and vaccine-era incidence as averages across multiple years, where data allowed. Despite our efforts to estimate average incidence values in both periods, significant epidemics or outbreaks occurred for some diseases that may not be reflected in the annual averages used in this analysis. 91 For the vaccine era, data used to derive disease incidence were for years preceding the coronavirus disease 2019 (COVID-19) pandemic. There are multiple factors that may influence the impact of COVID-19 on the incidence of vaccine-preventable diseases. For example, behavior changes caused by nonpharmaceutical interventions, including lockdowns, face-covering use, and other social distancing measures may reduce the transmission of some diseases, while simultaneously causing disruptions to vaccine uptake and coverage for the pediatric population that may adversely impact the prevention of vaccine-preventable diseases. 92 – 94 Future surveillance and survey data will help to understand the impact of the COVID-19 pandemic and other potential “shocks” to the immunization program on the transmission of other vaccine-preventable diseases.

Routine childhood immunization in the United States has continued to reduce the incidence of all targeted vaccine-preventable diseases. In the vaccine era, the incidence of diphtheria, Hib, measles, polio, rubella, and tetanus has been reduced to <1 per 100 000; across all targeted diseases, ∼24 million cases have been averted because of vaccination for the 2019 United States population. Routine immunization remains an effective public health intervention to avert disease; maintenance of high rates of vaccination coverage is necessary for sustained impact.

We thank Kate Lothman of RTI Health Solutions, who provided medical writing support for the development of this manuscript and whose services were funded by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co, Inc, Rahway, NJ, USA.

Ms Talbird, Mr Carrico, and Dr La conceptualized and designed the study, reviewed the literature, interpreted the results, and drafted the initial manuscript; Drs Chen, Nyaku, Carias, and Roberts conceptualized the study and provided input on the study design, secured funding, and interpreted the results; Dr Marshall interpreted the results; and all authors reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

COMPANION PAPERS: companions to this article can be found online at http://www.pediatrics.org/cgi/doi/10.1542/peds.2021-056007 and http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-057831 .

Dr La’s current affiliation is GSK, Philadelphia, Pennsylvania.

FUNDING: This study was funded by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co, Inc, Rahway, NJ, USA.

CONFLICT OF INTEREST DISCLOSURES: Ms Talbird and Mr Carrico are employed by RTI Health Solutions, which received funding for the conduct of this study. Dr La was an employee of RTI Health Solutions when this study was conducted and is now an employee and shareholder in the GSK group of companies. Drs Chen, Carias, and Roberts are employees of Merck Sharp and Dohme LLC, a subsidiary of Merck & Co, Inc, Rahway, NJ, and are shareholders in Merck & Co, Inc. Rahway, NJ. Dr Nyaku was an employee of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co, Inc, Rahway, NJ and a shareholder in Merck & Co, Inc, Rahway, NJ when this study was conducted. Dr Marshall has been an investigator on clinical trials funded by GlaxoSmithKline, Merck, Pfizer, Sanofi Pasteur, and Seqirus, and he has received honoraria from these companies for service on advisory boards and/or nonbranded presentations.

active bacterial core

acute otitis media

Centers for Disease Control and Prevention

coronavirus disease 2019

emergency department

Haemophilus influenzae type b

invasive pneumococcal disease

National Notifiable Disease Surveillance System

Supplementary data

Advertising Disclaimer »

Citing articles via

Email alerts.

Affiliations

Editorial Board
Editorial Policies
Journal Blogs
Pediatrics On Call
Online ISSN 1098-4275
Print ISSN 0031-4005
Pediatrics Open Science
Hospital Pediatrics
Pediatrics in Review
AAP Grand Rounds
Latest News
Pediatric Care Online
Red Book Online
Pediatric Patient Education
AAP Toolkits
AAP Pediatric Coding Newsletter

First 1,000 Days Knowledge Center

Institutions/librarians, group practices, licensing/permissions, integrations, advertising.

Privacy Statement | Accessibility Statement | Terms of Use | Support Center | Contact Us
© Copyright American Academy of Pediatrics

This Feature Is Available To Subscribers Only

Organization Menu

Additional organization links, search and explore, primary menu.

Vaccine FAQ

Our most frequently asked questions. Expand for detailed answers from experts.

Vaccines work to prime your immune system against future “attacks” by a particular disease. There are vaccines against both viral and bacterial pathogens, or disease-causing agents.

When a pathogen enters your body, your immune system generates antibodies to try to fight it off. Depending on the strength of your immune response and how effectively the antibodies fight off the pathogen, you may or may not get sick.

If you do fall ill, however, some of the antibodies that are created will remain in your body playing watchdog after you’re no longer sick. If you’re exposed to the same pathogen in the future, the antibodies will “recognize” it and fight it off.

Vaccines work because of this function of the immune system. They’re made from a killed, weakened, or partial version of a pathogen. When you get a vaccine, whatever version of the pathogen it contains isn’t strong or plentiful enough to make you sick, but it’s enough for your immune system to generate antibodies against it. As a result, you gain future immunity against the disease without having gotten sick: if you’re exposed to the pathogen again, your immune system will recognize it and be able to fight it off.

Some vaccines against bacteria are made with a form of the bacteria itself. In other cases, they may be made with a modified form of a toxin generated by the bacteria. Tetanus, for example, is not directly caused by the Clostridium tetani bacteria. Instead, its symptoms are primarily caused by tetanospasmin, a toxin generated by that bacterium. Some bacterial vaccines are therefore made with a weakened or inactivated version of the toxin that actually produces symptoms of illness. This weakened or inactivated toxin is called a toxoid. A tetanus immunization, for example, is made with tetanospasmin toxoid.

Vaccines are designed to generate an immune response that will protect the vaccinated individual during future exposures to the disease. Individual immune systems, however, are different enough that in some cases, a person’s immune system will not generate an adequate response. Therefore, he or she will not be effectively protected after immunization.

That said, the effectiveness of most vaccines is high. After receiving the second dose of the MMR vaccine (measles, mumps and rubella) or the standalone measles vaccine, 99.7% of vaccinated individuals are immune to measles. The inactivated polio vaccine offers 99% effectiveness after three doses. The varicella (chickenpox) vaccine is between 85% and 90% effective in preventing all varicella infections, but 100% effective in preventing moderate and severe chicken pox.

Currently, the U.S. childhood vaccination schedule for children between birth and six years of age recommends immunizations for 14 different diseases. Some parents worry this number seems high, particularly since some vaccine-preventable diseases are now extremely rare in the United States.

Each disease for which vaccinations are recommended can cause serious illness or death in unvaccinated populations, and could quickly begin to appear again if vaccination rates dropped. The United States has seen mumps outbreaks in recent years, since vaccination rates have dropped, with severe complications and hospitalizations required for some patients. And before the introduction of the Hib (Haemophilus Influenzae Type b) vaccine, Hib meningitis affected more than 12,000 American children annually, killing 600 and leaving many others with seizures, deafness, and developmental disabilities. After the vaccine was introduced, the number of deaths from Hib dropped to fewer than 10 per year.

Each vaccine on the schedule continues to be recommended because of the risks posed by wild infection.

In some cases, natural immunity is longer-lasting than the immunity gained from vaccination. The risks of natural infection, however, outweigh the risks of immunization for every recommended vaccine. For example, wild measles infection causes encephalitis (inflammation of the brain) for one in 1,000 infected individuals. Overall, measles infection kills two of every 1,000 infected individuals. In contrast, the combination MMR (measles, mumps and rubella) vaccine results in a severe allergic reaction only once in every million vaccinated individuals, while preventing measles infection. The benefits of vaccine-acquired immunity extraordinarily outweigh the serious risks of natural infection. (For more on this topic, see our .)

Additionally, the Hib ( Haemophilus influenzae type b) and tetanus vaccines actually provide more effective immunity than natural infection.

It is unclear why the length of acquired immunity varies with different vaccines. Some offer lifelong immunity with only one dose, while others require boosters to maintain immunity. Recent research has suggested that the persistence of immunity against a particular disease may depend on the speed with which that disease typically progresses through the body. If a disease progresses rapidly, the immune system’s memory response (that is, the “watchdog antibodies” generated after a previous infection or vaccination) may not respond quickly enough to prevent infection—unless they’ve been “reminded” about the disease fairly recently and are already watching for it. Boosters serve as a “reminder” to your immune system.

Research continues on the persistence of immunity generated by vaccines.

The idea of “pox parties” is generally tied to the perception of chickenpox as a harmless illness. Before the varicella vaccine became available, however, chickenpox infections required 10,000 hospitalizations and caused more than 100 deaths each year in the United States. Exposing a child to wild chickenpox puts him at risk for a severe case of the disease.

Even uncomplicated cases of chickenpox cause children to miss a week or more of school, with a caregiver missing work to care for the sick child. Natural infection also means a risk of infecting others: while successful vaccination protects a child against chickenpox without this risk, children infected with chickenpox naturally are contagious. They can spread the disease to other people—not just other children, but also adults, who have a higher risk of complications from the disease.

Meanwhile, vaccination for chickenpox typically prevents future infection with the disease. In rare cases where individuals do not develop adequate protection from vaccination to prevent future infection, chickenpox infection is typically mild, results in fewer symptoms, and ends more quickly than natural infection. (People with this mild form are contagious, however, and should take care not to expose others to the virus.)

Vaccines made with killed versions of pathogens—or with only a part of the pathogen—are not able to cause illness. When a person receives these vaccines, it is impossible for him or her to become ill with the disease.

Live, attenuated (or weakened) vaccines are theoretically capable of causing illness: because they can still replicate (though not well), mutation is possible, which can lead to a virulent form of the pathogen. However, they are designed with this in mind, and attenuated to minimize this possibility. Reversion to virulent form is a problem with some forms of the oral polio vaccine (OPV), which is why only the inactivated form (IPV) is now used in the United States.

It is important to note that attenuated vaccines can cause serious problems for individuals with weakened immune systems, such as cancer patients. These individuals may receive a killed form of the vaccine if one is available. If not, their doctors may recommend against vaccination. In such cases, individuals rely on herd immunity for protection.

Why some vaccines contain live pathogens and others contain killed pathogens, the reasons vary by illness. However, live, attenuated vaccines generally generate longer-lasting immunity than killed vaccines. Thus, killed vaccines are more likely to require boosters to maintain immunity. Killed vaccines, however, tend to be more stable for storage purposes, and can’t cause illness. The medical community must weigh these trade-offs in deciding which approach to use against a particular disease.

Yes. Studies demonstrate that infants’ immune systems can handle receiving many vaccines simultaneously—more than the number currently recommended. The immunization schedule is based on infants’ ability to generate immune responses, as well as when they are at risk of certain illnesses. For example, the immunity passed from mother to child at birth is only temporary, and typically does not include immunity against polio, hepatitis B, Haemophilus influenzae type b, and other diseases that can be prevented by vaccination.

Unlike most vaccines, which contain the most common strains of a given pathogen (if more than one exists) and are rarely changed, the seasonal flu vaccine changes frequently, though one or more flu strains in the vaccine may be retained from one year to the next. This is because the strains of influenza viruses that circulate are constantly changing. Each year, researchers choose viruses for the vaccine based on which ones are likely to circulate over the coming flu season, providing protection against the most prevalent strains. So when you get a seasonal flu vaccine, you’re usually not getting another “dose” of the same flu vaccine you were given before. Instead, you’re usually getting protection against a whole new batch of flu viruses.

Herd immunity, also known as community immunity, refers to the protection offered to everyone in a community by high vaccination rates. With enough people immunized against a given disease, it’s difficult for the disease to gain a foothold in the community. This offers some protection to those who are unable to receive vaccinations—including newborns and individuals with chronic illnesses—by reducing the likelihood of an outbreak that could expose them to the disease.

Some vaccines, including most vaccines against influenza, are cultured in chicken eggs. During the process of creating the vaccine, most egg protein is removed, but there is some concern that these vaccines could generate an allergic reaction in individuals with an egg allergy.

A recent report found that most children with egg allergies who were given a flu shot had no adverse reactions. About 5% of children in the studied group developed relatively minor reactions, such as hives, which resolved without treatment. Additional research is underway to study this issue further.

In most cases, only people with a severe (life-threatening) allergy to eggs are recommended against receiving egg-based vaccines. Your doctor can provide specific information.

No. Vaccines do not cause autism. This possibility was publicized after a 1998 paper by a British physician who claimed to have evidence that the MMR (measles, mumps and rubella) vaccine was linked to autism. The potential link has been thoroughly explored; study after study has found no such link, and , which had originally published it. Studies were also done regarding the possibility of a link between the preservative thimerosal, which is used in some vaccines, and autism; again, no such link was found.

It’s likely that this misconception persists because of the coincidence of timing between early childhood vaccinations and the first appearance of symptoms of autism.

All vaccines have possible side effects. Most, however, are mild and temporary. Adverse effects from vaccines are thoroughly monitored via multiple reporting systems, and there is no evidence from these systems to support these claims.

Every vaccine has potential side effects. Typically they are mild: soreness at the injection site (for a vaccine delivered via a shot), headaches, and low-grade fevers are examples of common vaccine side effects. Serious side effects are possible, including severe allergic reactions. However, these side effects are rare. (Your doctor can explain the risks for individual vaccines in detail; .)

When considering possible side effects from vaccination, it’s important to do so in context. While some possible side effects are serious, they are rare. It’s important to remember that choosing not to vaccinate also has serious risks. Vaccines protect against potentially fatal infectious diseases. Avoiding vaccination raises the risk of contracting those diseases and spreading them to others.

Vaccines are tested repeatedly before being approved, and continue to be monitored for adverse reactions after their release. See our article on vaccine testing and safety for more information and details about this topic.

No. The rubella vaccine virus included in the MMR (measles, mumps and rubella) shot is cultured using human cell lines. The vaccine material is carefully separated from the cells in which it was grown before being used.

Some of these cell lines were generated from fetal tissue obtained in the 1960s from legal abortions. No new fetal tissue is required to generate the rubella vaccine.

Improved hygiene and nutrition, among other factors, can certainly lower the incidence of some diseases. Data documenting the number of cases of a disease before and after the introduction of a vaccine, however, demonstrate that vaccines are responsible for the largest drops in disease rates. Measles cases, for example, numbered anywhere from 300,000 to 800,000 a year in the United States between 1950 and 1963, when a newly licensed measles vaccine went into widespread use. By 1965, U.S. measles cases were beginning a dramatic drop. In 1968, about 22,000 cases were reported (a drop of 97.25% from the height of 800,000 cases in just three years). By 1998, the number of cases averaged about 100 per year or less. A similar post-vaccination drop occurred with most diseases for which vaccines are available.

Perhaps the best evidence that vaccines, not hygiene and nutrition, are responsible for the sharp drop in disease and death rates is chickenpox. If hygiene and nutrition alone were enough to prevent infectious diseases, chickenpox rates would have dropped long before the introduction of the varicella vaccine, which was not available until the mid-1990s. Instead, the number of chickenpox cases in the United States in the early 1990s, before the vaccine was introduced in 1995, was about four million a year. By 2004, the disease incidence had dropped by about 85%.

In theory, nearly any infectious disease for which an effective vaccine exists should be eradicable. With sufficient vaccination levels and coordination between public health organizations, a disease can be prevented from gaining a foothold anywhere. Without anyone to infect, it must die off. (A notable exception is tetanus, which is infectious but not contagious: it’s caused by a bacterium commonly found in animal feces, among other places. Thus, tetanus could not be eradicated without completely removing the Clostridium tetani bacterium from the planet.)

Smallpox is unusual, however, in the characteristics that made it susceptible to eradication. Unlike many other infectious diseases, smallpox has no animal reservoir. That is, it can’t “hide” in an animal population and re-emerge to infect humans, while some diseases can do exactly that (yellow fever, for example, can infect some primates; if a mosquito bites an infected primate, it can transmit the virus back to humans).

Another obstacle to eradication for many infectious diseases is visibility. People with smallpox were highly visible: the smallpox rash was easily recognizable, so that new cases could be detected quickly. Vaccination efforts could be focused on the location of the cases and potential exposure to other individuals. Polio, by contrast, causes no visible symptoms in about 90% of the people it infects. As a result, tracking the spread of the polio virus is extremely difficult, making it a difficult eradication target.

Perhaps most importantly, smallpox patients generally did not reach their highest level of infectivity (that is, their ability to infect others) until after the appearance of the smallpox rash. As a result, quick action to quarantine infected individuals upon the eruption of the rash usually left enough time to vaccinate anyone already exposed, and prevent additional exposures. Many infectious diseases do not allow for this type of reaction time. Measles patients, for example, can become infectious up to four days before the appearance of the measles rash. As a result, they can pass the virus on to many, many other people before anyone even knows they are infected.

Many people still think eradication is possible for certain diseases. Efforts are ongoing to eradicate polio and Guinea worm disease (Dracunculiasis), with both eliminated in many regions, but remaining endemic in several countries. Meanwhile, the Carter Center International Task Force for Disease Eradication has declared additional diseases potentially eradicable: lymphatic filariasis (Elephantiasis), mumps, pork tapeworm, and yaws.

[For more about this topic, see our article on .]

The polio vaccines developed by Jonas Salk and Albert Sabin in the mid-20th century were made with monkey cells. Years later, microbiologist Maurice Hilleman found a monkey virus in both vaccines—the 40th monkey virus to be discovered, which he called Simian Virus 40 (SV40). (Salk’s killed vaccine, which was treated with formaldehyde, had very small amounts of the virus; Sabin’s live vaccine was heavily contaminated.) Worried about the potential effects the virus could have on humans, Hilleman injected it into hamsters, finding that nearly all of them developed massive cancerous tumors. But the initial panic this caused gave way in the face of future studies.

First, hamsters that ingested SV40 instead of being injected with it didn’t get cancer. Sabin’s live vaccine (which contained more SV40 than Salk’s) was given orally. Additional studies showed that children given Sabin’s vaccine did not develop antibodies to SV40; it simply passed through their digestive system, never causing infection.

That left only Salk’s vaccine, which contained very little SV40, but was given by injection. Studies performed eight years, fifteen years, and thirty years after SV40-contaminated vaccines were given to children found they had the same cancer incidence as unvaccinated groups. No credible evidence suggests SV40 has ever caused cancer in humans.

For a discussion on why the polio vaccine is not associated with HIV, read our article discussing this proposed association:

The mRNA vaccines developed in response to the COVID-19 pandemic caused concern among many people who claimed the mRNA technology was “too new” to be considered safe, or that it would be a while before we would know all the risks.

First, the clinical trials to show the vaccine safety and efficacy were carried out in the same manner as other clinical trials for vaccines. They had the same number of participants, same steps, and same oversight. The only aspect of those trials that was different was the timeframe in which they were done. Because of the need for new vaccines to counter to the COVID-19 pandemic, the studies and vaccine development/manufacturing were done simultaneously, not subsequently. Those clinical trials showed that the mRNA vaccines were safe and effective in preventing severe disease.

Second, mRNA technology has been around since the 1990s. So why have they not been used in vaccines? Two reasons: Lack of funding to use them as vaccines against infectious agents, and lack of interest, since the existing licensed vaccines worked well. In 2020, the Trump Administration authorized the use of funds for “Operation Warp Speed” to fund the rapid development of vaccines, taking care of the funding part. Once the mRNA vaccines were shown to be safe and effective against COVID-19, other infectious diseases were targeted for mRNA vaccine development.

Gever, J. . MedPage Today. (2010) Accessed 01/25/2018.
Carroll-Pankhurst, C., Engels, E.A., Strickler, H.D., Goedert, J.J., Wagner, J., Mortimer Jr, E.A. . British Journal of Cancer . 2001 Nov;85(9):1295. Accessed 01/25/2018.
The Carter Center. . (20 KB PDF) Accessed 01/25/2018.
Centers for Disease Control and Prevention. . Accessed 01/25/2018.
CDC. . Accessed 01/25/2018.
Sharp, P.M., Hahn, B.H. . Philosophical Transactions of the Royal Society of London. Biological Sciences . 2010 Aug 27;365(1552):2487-94. Accessed 01/25/2018.
Worobey, M., Santiago, M.L., Keele, B.F., Ndjango, J.B., Joy, J.B., Labama, B.L., Dhed'a, B.D., Rambaut, A., Sharp, P.M., Shaw, G.M., Hahn, B.H. Origin of AIDS: contaminated polio vaccine theory refuted. Nature. 2004 Apr 22;428(6985):820-.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Open access
Published: 21 November 2022

Meta-summaries effective for improving awareness and understanding of COVID-19 vaccine safety research

Spencer Williams 1 ,
Joy Lee 2 ,
Brett A. Halperin 1 ,
Joshua M. Liao 2 ,
Gary Hsieh 1 &
Katharina Reinecke 3

Scientific Reports volume 12 , Article number: 19987 ( 2022 ) Cite this article

1381 Accesses

1 Citations

7 Altmetric

Metrics details

Human behaviour
Public health

An Author Correction to this article was published on 03 January 2023

This article has been updated

Despite the efficacy, safety, and availability of COVID-19 vaccines, a lack of awareness and trust of vaccine safety research remains an important barrier to public health. The goal of this research was to design and test online meta-summaries—transparent, interactive summaries of the state of relevant studies—to improve people’s awareness and opinion of vaccine safety research. We used insights from a set of co-design interviews (n = 22) to develop meta-summaries to highlight metascientific information about vaccine safety research. An experiment with 863 unvaccinated participants showed that our meta-summaries increased participants’ perception of the amount, consistency, and direction of vaccine safety research relative to the U.S. Center for Disease Control (CDC) webpage, and that participants found them more trustworthy than the CDC page as well. They were also more likely to discuss it with others in the week following. We conclude that direct summaries of scientific research can be a useful communication tool for controversial scientific topics.

Misunderstanding the harms of online misinformation

Safety outcomes following COVID-19 vaccination and infection in 5.1 million children in England

Determinants of behaviour and their efficacy as targets of behavioural change interventions

Introduction.

The COVID-19 pandemic has highlighted how low public trust and understanding of vaccine research has led to vaccine hesitancy 1 . In turn, hesitancy has contributed to suboptimal vaccination rates, which in turn contributes to an excess of preventable infections, hospitalizations, and deaths 2 . One of the most important causes of vaccine hesitancy is a lack of perceived safety 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , in addition to low perceived efficacy 3 , 10 , logistic challenges 10 , 11 and lack of trust in relevant institutions 4 , 5 , 9 , 10 , 11 , 12 .

Greater transparency and probity 1 , and communication of “facts over exhortations” 13 , are needed to improve the relationship between a vaccine-hesitant public and vaccine research. To meet this need and communicate much-needed vaccine information, this paper reports on online, interactive meta-summaries of COVID-19 vaccine safety research aimed at increasing public awareness, knowledge, and understanding in a transparent and trustworthy way.

Recent work has examined the potential of various online interventions to inform the public about vaccines. These online interventions for vaccine safety communication have shown some promise at informing the public through videos 14 , tailored information 15 , and interactions on social media 16 . They may focus on providing information for “fence-sitters” who seek to make informed decisions about vaccination 17 , so providing clear, high-quality, credible resources is key. These online interventions represent a scalable approach to increasing public awareness and understanding of vaccine safety information, and given how difficult it can be for even experts to stay informed about rapidly evolving research fields like those related to COVID-19 18 , this scalability is important. However, existing public health websites on COVID-19 19 , as well as other vaccine technology 20 , can be difficult to read, or fail to utilize data and graphics effectively, suggesting more work should be done to build online interventions grounded in the information and design needs of vaccine-hesitant groups.

Another approach to improving vaccine attitudes is to communicate the degree of scientific consensus among medical researchers 21 . While there is a large body of work showing that perceived scientific consensus can improve attitudes toward relevant scientific issues 21 , 22 , 23 , some have argued that these consensus messages may not be using an appropriate unit of analysis 24 . That is, these past consensus messages have focused on whether individual scientists agree with a particular finding (e.g., “vaccines are safe”); however, such an authoritative message may induce backfire effects 25 , and future consensus messages should highlight the process of consensus formation as agreement based on a given body of evidence. A more transparent approach may be more convincing, especially to the rising number of people who distrust scientific institutions in the U.S. 26 , as they are unlikely to defer to such appeals to authority.

To that end, we sought to develop ways of communicating COVID-19 vaccine safety research that highlights scientific consensus by summarizing direct evidence.

Co-design interviews: qualitative results

We first present results from a set of co-design interviews on vaccine-hesitant people. Our primary research question driving these sessions was: What kind of meta-information about vaccine safety research is useful and relevant to vaccine-hesitant people, and how can we effectively communicate that information?

We recruited 22 U.S. adults to take part in our co-design interviews, identified from a screener survey we deployed on Amazon Mechanical Turk (MTurk). All participants indicated that they were either unvaccinated and currently hesitant to get vaccinated for COVID-19 (n = 10), or had previously been hesitant (n = 12). 11 were female, and 11 were male. 13 were White, 7 were Black, and 2 were Asian. For the full characteristics of our sample, see Table 1 . Participant quotes are lightly edited for clarity.

Challenges using scientific papers

First, we found that scientific evidence was generally considered important, with several participants using research papers to help make decisions (“I had actually read a lot of scientific journals. I mean, I really dug deep into stuff like that.”—P22). However, these papers were typically not perceived as useful as information sources. First, they were difficult to access (“A lot of the times they're behind paywalls and it takes extra time to actually get the content”—P13). Second, even if they could be accessed, they were difficult to understand (“I didn't really read the raw science because it's way over my head.”—P20). Third, it can be difficult for non-experts to extract key takeaways, with multiple participants describing them as “boring” (“They're just kind of boring and I just want some basic information, like I don't really care to go in depth and that's what most of them are. I can understand what it's saying, but I just don't want to apply myself to do that.”).

However, our participants were interested in understanding the state of the research. Rather than searching through research papers, our prototypes that summarized key statistics and other information from the literature were considered useful. As P10 described:

This would help somebody like me, that's kind of on the verge of not knowing like, wanting to do what's best for everybody to help make a more informed decision without having to spend like 52 hours trying to source information, right? Going down the rabbit hole, and then being able to write it down or put it on a doc and okay, this says this and this, this, and it's like right here. You made the doc.

Given the need for a summary of relevant metascientific information in making vaccination decisions, we then analyzed what specific pieces of information participants considered useful, and how they would want it displayed.

Quantity and consistency of research results

First, many of our participants were convinced by data showing how much research has been done on vaccine safety, and how consistently safe the COVID vaccines have been shown to be (“Something like 8.8 million people kind of makes me more comfortable to go take the vaccine.” -P16). Beyond the quantity, consistency was also important, with participants wanting to know results held over repeated studies (“I mean, if just one person does an experiment, that doesn't really prove much till it's like tested over and over again. So I think that part's really important.”—P14). Others had specific needs, such as who the participants of the studies were (“If I see that more severe side effects are happening more in women, I probably wouldn't get it.”—P8), depending on their specific questions.

Indicators of trust

Not all participants were willing to trust that the data displayed was accurate. A common concern was that safety research (or how we were presenting it) was biased, so metascientific factors like funding source or institution were considered important (“let's just say Johnson and Johnson did the study, or that Moderna did the study. And I'm like, well, that's not unbiased.”—P10). This was considered the most important piece of information by several participants, specifically those who lacked trust in scientific institutions (“Funding source, it tells of a certain bias, I guess, for what they're looking for in their studies and whatnot, and who's funding them, who's giving them money, who made it possible. I think for me, that would be the most important for credibility.”—P9). Information on what country a study was conducted in was also considered relevant, for those who believed research done in the U.S. is untrustworthy (“I would look at studies from different countries, yeah.”—P1). Those who looked for this type of information expressed wanting to know the intentions behind the research; are researchers beholden to moneyed interests? Or are they doing research for altruistic reasons? Can they be trusted?

Design considerations

In terms of design, participants were split on how they wanted to engage with the research. For some, having the ability to interact with and interrogate the data was useful, either to determine its credibility or its relevance to their own circumstances (“I like to have a lot of numbers. That way I can analyze it myself, figure things out. […] It's just the right amount of controllability. I can go from studies that have a hundred participants or studies that have a million, then hover over the icon and get even more of a breakdown of the information. So I think that's pretty amazing.”—P17). Others had no interest in this level of interrogation, preferring a clear message explaining key takeaways (“Interaction feels like a waste of time, especially when it's a message that could still be conveyed with a simple, still graphic that's already sort of developed for me. I just want a clear, clean, simple presentation of information that I can really just digest at a glance.”—P20).

This difference also emerged explicitly in many of our participants’ sketches. While there was some variety in form and function, most commonly participants generated two-tiered, interactive infographics. They often began with high-level, plain-language, bulleted summaries of the state of the research, to ensure the key takeaways are clear. This was usually supplemented by an interactive graph or other visualization, providing additional details on demand for those who want to more deeply interrogate the research. These often involved hovering/clicking on studies to propagate details like funding source, sample size, study population, etc. This general approach allowed for easy interpretation from participants who had no interest in exploring the details of the literature (“Hey, I'm just asking this one question. I just want one sentence really. And then if I'm interested by the answer, I'll click read more. Cause otherwise…this is just too much or overwhelming and I'll just close out of it.”—P19). For others, however, providing transparent details on the metascientific information (institutions, authors, funding sources) could improve trust, and help users make more nuanced decisions about the literature.

Finally, some participants were concerned about bias in the system. For some, the explicit narrative provided by some of our prototypes (e.g. one providing a text-based summary) could feel it’s leading readers to a specific conclusion, and glossing over conflicting information, as P4 describes:

I feel like there would be some sort of study that maybe majority might lead to like this direction, but I'm sure there is some research out there, maybe like a very minute number, that might have opposite results than what's presented here. I would say having that as well might make the reader feel that they're the ones making the decision versus, you know, leading them to a certain decision.

To address this, visualizations that clearly display the full range of studies on vaccine safety could be considered more transparent, and less biased (“The bias was really just coming from how the information is structured or worded. […] But with this [a scatter plot graphing all studies in our sample] you can look at each thing one at a time, so it doesn't feel biased anymore.”—P19). Such an approach would likely rely on users’ trust that the displayed range of studies is representative of the full literature.

Based on the findings from these co-design sessions, we generated a list of design requirements for scientific meta-summaries in this domain:

Provide simple, concise, text-based summaries of the information.

Provide interactions for details-on-demand, to provide deeper insights for those who want to interrogate the literature and ensure credibility.

Visually convey the quantity of research.

Visually convey the consistency of research.

Provide key metascientific signals of credibility (e.g. funding source).

Signal that the research displayed is representative of the full body of COVID-19 vaccine safety research.

A meta-summary of COVID-19 vaccine safety research

Based on the above insights and following our design requirements, we designed an interactive meta-summary meant to provide metascientific information our participants considered valuable when assessing vaccine safety research, in a format that would be useful to them. Following the formatting conventions participants used (high-level takeaways, details on demand), we designed four visualizations describing key pieces of information based on the needs we identified (see Fig. 1 ).

A screenshot of the full version of our intervention. The top visualization is an icon array representing the efficacy of mRNA vaccines at preventing serious COVID-19 outcomes (only present in the full version). Next is a bar chart depicting the number of participants or individuals across studies with or without serious adverse reactions to the vaccine. Below that is an interactive scatterplot depicting the number, size, and risk estimates of studies over time, with the right pane providing additional details. At the bottom is a bar chart representing the most common sources of funding across studies.

We developed and tested two versions of our intervention. In general, our co-design participants were concerned about safety, they considered a large amount of consistent research to be useful in assessing safety, and they considered funding source to be useful in determining credibility. Our interventions prioritized signaling this information. In the first version (“safety only”), we first included visualizations about the number of participants across studies in our sample, using tick marks [e.g. “Population of Australia (40 + million)”] to contextualize the combined size of the studies in our sample. We next included study estimates of vaccine safety risk over time in a scatter plot (highlighting the consistent low risk estimates), where participants could click each study for additional details (providing a transparent overview of the research space). We specifically used serious adverse events as outcomes, defined by the studies on COVID vaccines in our sample, which included outcomes like myocarditis, anaphylaxis, and GBS. Finally, we included a graph of the frequency of different funding sources, which highlighted that most studies were funded by their own university or non-profit organizations.

In the second version (“full version”), we also included a graph depicting the efficacy of the mRNA vaccines at preventing serious outcomes, in order to additionally address the belief shared by a subset of our participants that the vaccine was ineffective or unnecessary.

For both versions, we also drew on qualitative work that suggests providing “facts over exhortations” for vaccine-hesitant people 13 . This is in-line with research on psychological reactance 30 , whereby people respond negatively when they perceive that their freedom is being threatened. To address this, we adapted an “inoculation” message from past work 31 to remind participants that they are free to use the information however they wish:

You’ve probably heard a lot of messages telling you about COVID-19 vaccines. Of course, you can decide what to do with those messages. We, a group of researchers at the University of Washington, have collected all published papers we could identify by searching for “covid,” “vaccine,” “side-effects, and “adverse reactions” on Google Scholar up to December 2021, and it’s up to you to decide how to use this summary.

Experimental evaluation

To test whether our interventions improved vaccine hesitant people’s awareness, opinion, and trust of vaccine safety research, and their intention to get vaccinated, we conducted a pre-registered ( https://aspredicted.org/blind.php?x=56W_KT2 ) experiment on MTurk. There were three conditions: the safety only version, the full version, and a baseline condition where we included information from the U.S. Center for Disease Control’s (CDC) page on vaccine safety data.

In total, we received 2198 responses after systematically removing responses which did not meet appropriate checks (see “Methods” for details), and analyzed the responses of the 863 of those who were unvaccinated.

Compared to the CDC condition, we found that participants were more likely to agree that there was more research than they thought (F(2, 871) = 5.15, p = 0.006, η 2 = 0.012), more consensus than they thought (F(2, 871) = 9.65, p < 0.001, η 2 = 0.022), and that the research showed they were safer (F(2, 871) = 15.31, p < 0.001, η 2 = 0.034) than they thought before viewing our interventions. Moreover, participants rated our intervention as more trustworthy than the information on the CDC page, F(2, 871) = 3.36, p = 0.035, η 2 = 0.008. See Table 2 for pairwise comparisons.

However, there was no significant effect of our intervention on participants’ concerns about vaccine safety, F(2, 871) = 0.89, p = 0.413, η 2 = 0.002. There was also no effect on their perceived credibility of vaccine science overall, F(2, 871) 1.36, p = 0.256, η 2 = 0.002. Finally, we ran a logistic regression testing whether participants increased their intention to get vaccinated, but there was again no significant effect (see Table 3 ).

Longitudinal effects

We then conducted a follow-up survey with participants from our experiment between 1–2 weeks after the initial deployment (N = 547), where we asked whether they had thought about the intervention, discussed it with others, been inspired to do more research on COVID-19 vaccines, or made a decision about whether to get vaccinated.

We found that participants who viewed our intervention were more likely to have discussed it with others than those who viewed the CDC version (see Table 4 ). There were no significant effects on other longitudinal activities.

Qualitative results

To help explain our results, we asked participants in both the initial experiment and the follow-up to answer qualitative questions about their initial impressions of the intervention, and the circumstances around any thoughts/discussion/decisions they had in the follow-up.

First, in-line with previous qualitative results, with the amount and consistency of research, and funding sources, were considered useful signals:

First, I didn't realize there had been so many studies on the vaccine, and the correlations of those results were encouraging. I was also encouraged to know that the majority of the research studies were not funded by a government ensuring the science speaks for itself. I would say overall the information slightly improved my feelings towards the safety of the vaccine.

However, there were also a number of reasons the intervention did not work for other participants. First, a number of participants had little trust for science as an institution, believing that researchers may be biased (“I simply don't trust universities either. They are too biased in everything and if anyone even came out with research that shows there's something wrong, they would be canceled and I think that motivates everyone to walk in lockstep with the mainstream narrative.”). This may tie in with the belief that vaccine researchers are financially motivated to publish only positive results (“This information did not change my opinions about vaccine research as I do not believe it is reliable or accurate as researchers are highly motivated to portray the vaccine positively due to enormous financial incentives and funds.”).

Second, there were lingering concerns about potential long-term effects, which participants felt this body of research could not yet address (“It made me feel a bit more confident about it but we still don't know long term effects.”).

Third, as our interventions focused on safety, this was not the main concern for all participants (“I believe that the COVID jabs are "safe", so your research didn't speak to my issue. I haven't gotten one because they are NOT effective at preventing transmission.”). Even participants in our full version were not convinced of the importance of the vaccines (“I still do not believe it to be safe or effective.”). The above factors, as well as a general lack of trust in pro-vaccine messages (“Y'all are liars and I laugh at your dumb propaganda.”), represent additional obstacles for vaccine safety communication.

For the follow-up survey, in-line with our finding that participants who saw our intervention were more likely to discuss it than the CDC page, we found having clear, transparent numbers may help empower those who have already been vaccinated to have discussions with friends who are still hesitant (“I have a relative who was […] spouting nonsense. The information I was shown on the survey gave me a few actual facts rather than just calling him an idiot.”).

In this work, we showed that meta-summaries of a scientific topic can serve as effective communication tools. Our intervention was successful at informing vaccine-hesitant people about the amount, stability, and valence of COVID-19 vaccine safety research. Importantly, it was considered more trustworthy than information from the CDC website, an important communication platform during the pandemic. We have also shown that an approach using more direct scientific evidence, rather than statements of expert consensus, can be effective at establishing scientific consensus on a controversial topic 24 .

While our research showed that scientific meta-summaries can provide trustworthy information, our intervention did not significantly increase people’s intention to get vaccinated, suggesting a need for future work. One issue was that our intervention did not affect people’s perceived credibility of the underlying science; even if they believe the information was reported accurately and honestly, they may still have a broad distrust of the scientific establishment.

One possible approach to increasing credibility of science as a whole would be to empower audiences to better navigate and interrogate vaccine research. Beyond increasing trustworthiness via a show of vulnerability to critical assessment, feelings of powerlessness have been associated with susceptibility to conspiracy theories 32 , 33 , suggesting that interventions to empower people can potentially work to reduce conspiracy-related beliefs 34 . By guiding skeptical audiences to critically-but-competently evaluate the studies provided, or on how to use the metascientific information we provide as useful heuristics (e.g. for research quantity or credibility), it may be possible to further increase trust and understanding of science using a metascience-based approach as we have.

Finally, although safety concerns have been a major issue for vaccine rejection, they are not the only ones; concerns about efficacy, logistics (e.g. cost, transportation), and trust are also important considerations 3 , 4 , 5 , 9 , 10 , 11 , 12 . Thus, even interventions that affect participants’ assessment of safety research, while important, may not be adequate in convincing those participants to get vaccinated, without a more holistic effect on other key concerns.

Data collection for our screener survey, co-design, and experiments had IRB approval by the University of Washington Human Subjects Division. All procedures were carried out in accordance with relevant guidelines, and informed consent was obtained where applicable.

This paper reports on a set of online meta-summaries—text and visualizations summarizing high-level information about the state of the research domain—about COVID-19 vaccine safety research, developed using a human-centered design (HCD) process 27 . We first conducted qualitative interviews with a co-design component 28 with vaccine-hesitant people in the U.S, in order to learn why they were hesitant to get vaccinated and to have them sketch out ways of accessing scientific knowledge about vaccines. As a method, co-design can help build empathy between researchers/designers and participants/users 29 , an important consideration when eliciting feedback from people hesitant about the COVID-19 vaccines 13 . It also allows us to frame the interviews around participants’ needs, with the intention of establishing buy-in from participants who may not otherwise trust research on Covid-related topics.

Co-design interviews

Co-design is a research method where participants are asked to engage directly in the design process 28 . In our sessions, we asked them to sketch designs for a research summary that would best meet their needs. By framing interview sessions as a way of eliciting feedback to produce tools for our participants, we sought to establish a co-operative relationship and build empathy 29 . We expected this would help participants be more candid with their opinions and needs, particularly when working with a population with lower-than-average trust of science 4 , 5 , 11 .

To recruit participants, we deployed a screener survey on MTurk (n = 676), where we asked “Are you—or at some point were you—hesitant to get the COVID-19 vaccine (for example, Pfizer, Moderna, Johnson & Johnson)?”, “If you could ask any question about the COVID-19 vaccines (for example, Pfizer, Moderna, Johnson & Johnson), what would you ask?”, and demographic questions. We emailed those who responded that they were either currently hesitant, or at some point were hesitant, to get the vaccine, and indicated their willingness to participate in an interview. In total we reached out to 153 participants for a final sample of 22 who agreed to participate (14.4%).

Our full interview protocol is provided in Appendix A of the Supplementary Materials. We began by asking preliminary questions about where participants get information about COVID-19 and vaccines, and what made them hesitant. We then provided a list of information about scientific research (information about studies, their findings, their authors, institutions, funding sources, participants, etc.), and asked what they might find useful when making vaccination decisions. We then showed off three mockups: a text-based summary of relevant literature, an interactive scatter plot, and a tool to simulate and visualize possible outcomes of getting vaccinated. We asked what was (not) useful about these mockups, and how they could be improved. We then asked how these might be implemented into social media or search engines, before ending by asking them to sketch a version of the tool that would be best suited to their needs. Sessions were approximately 45–60 min.

Interview data was analyzed using a thematic analysis approach 35 . We first transcribed the audio for each interview, open coded the first five to develop a coding scheme, then close coded the full set. Each coded section from each interview was added to a single document under that code, where we extracted high-level summaries of each code. These were then combined to develop a number of themes, with particular focus on the information needs and goals of different participants.

Distribution

To test our interventions, we deployed an experimental survey on MTurk. Participants were only allowed to take the survey if they were on a laptop or desktop computer, with mobile users being automatically removed, to ensure our prototypes displayed correctly. It was posted to MTurk with the title “Read about Covid-19 vaccines and answer a survey [CANNOT USE MOBILE]”, the description “Read some information about Covid-19 vaccine safety research and give us your opinions. [Mobile responses not allowed; must use laptop or desktop computer]”, and was tagged with the keywords “survey”, “research”, “vaccine”, and “covid”.

Participants were randomly assigned into one of three conditions: the full version, the safety only version, and a baseline using information from the then-currrent CDC page on vaccine safety (There were three conditions: the safety only version, the full version, and a baseline condition where we included information from the CDC’s page on vaccine safety data (see Fig. 2 ). We chose this as a baseline because, like our interventions, it serves as a high-level overview of safety data on COVID-19 vaccines. It mirrors our intervention in that it provides the amount of research (“More than 520 million doses…”) and safety estimate (“VAERS received 11,225 reports of death (0.0022%)…” Thus, it represents a then-current standard in how this information is being communicated to a U.S. audience by an official government body. Any improvement we show relative to this baseline represents an improvement on current communication with similar goals.

A screenshot of the condition we developed by pulling information from the CDC page on COVID vaccine safety research.

We measured vaccination status by asking “Have you been vaccinated for COVID-19?” and for those who responded “yes”, “Have you received a COVID-19 vaccine booster?” Vaccine intention was measured by asking participants “How would you describe your intention to get [next dose]?” (definitely/not sure/definitely not). Participants were also asked to their vaccine hesitancy concerns on a 5-point likert scale (“I am not worried about getting infected with COVID-19”, “I do not believe the COVID-19 vaccines are effective”, “I do not believe the COVID-19 vaccines are safe”, “It is too costly to get a vaccine (for example, can’t get transportation, can’t take time off work)”).

We measured credibility of US vaccine research using three subdomains from prior work: trustworthiness, competence, and benevolence 36 . Specifically, they were asked to rate their agreement with the following statements on a 5-point scale: “I think COVID-19 vaccine safety research in the United States [is trustworthy/is competent/protects public interest]." We also measured their trust of the information in the meta-summary itself, using agreement with two statements from prior work (“I think the information I just read was [believable/balanced]" on a 5-point scale 37 .

We measured their agreement with statements about research amount (“There is more research on COVID-19 vaccine safety than I thought there was before taking this survey.”), research consensus ("Research on the safety of COVID-19 vaccines is more consistent than I thought before taking this survey."), and direction of the research ("Research on the safety of COVID-19 vaccines shows a lower rate of adverse reactions than I thought before taking this survey.") on a 5-point scale.

Participants began by reading a brief explanation of the experiment, including details of what they will be asked to do. Participants were first asked for their vaccination status, vaccine intention, and vaccine hesitancy concerns. Next, they were asked to rate the credibility of US-based vaccine research.

Participants were then randomly assigned to one of our three conditions. They were instructed that they will “see a set of information about the safety of COVID-19 vaccines. Please read through the information on the page before moving on with the survey.” After they left the page, they were given an optional text-entry question asking “How (if at all) did the information you just saw affect your opinions about covid vaccine research?”.

After interacting with the meta-summary, they were asked about their trust of the information on the page. Next, they were asked the same set of questions about vaccine research credibility, as a pre-post measure. After that, they were asked about the amount, consistency, and direction of vaccine research, before responding to the same questions about vaccine intention and reasons for hesitancy as above, again as a pre-post measure.

Finally, participants were given the short need for cognition (NFC) scale 38 , and graph literacy scale 39 , before completing a set of demographic questions and ending the survey.

For analysis and recruitment, we followed the plan laid out in our pre-registration, with three changes. First, when analyzing intention to get vaccinated, we used a logistic regression instead of an ordinal model due to a failure of the latter to converge as specified. Second, we oversampled to ensure that we had an adequate number of unvaccinated participants, as our original sampling plan did not take this into account. Finally, we noticed in the qualitative responses that several participants had seemingly copy-pasted sections of Covid-related articles found online. Many of these were identical to each other, and we concluded these were likely either bots, or the same participants using identical responses across IP addresses.

To improve data quality, we decided to remove responses with this type of qualitative answer. First, to ensure we were removing copy-pastes and not just low-effort responses (e.g. “good”, “no”), we first set a minimum character limit of 50 for qualitative responses. Next, we compared each response against all others, until identifying one with a Levenshtein distance of less than 10% the length of the response. This helped identify obvious copy-pastes with minor errors, like the following:

“THE AVAILABLITY OF A SAFE AND EFFECTIVE VACCINE FOR COVID-19”

“THE AAVAILABILITY OF A SAFE AND EFFICTIVE VACCINE FOR COVID-19”

This procedure identified 268 likely bots out of 2393 total unique IDs.

For analysis, although our pre-registration specified we would analyze specific vaccine hesitant sub-groups, we did not observe any differences or interactions between these groups, and chose not to discuss them here due to a lack of theoretical relevance in interpreting our results.

Follow-up survey

Finally, our follow-up survey was not pre-registered, and was developed within the week following our initial survey deployment. It was deployed on MTurk, was made available only to those who had completed our initial experiment, and ran 8–14 days after that experiment. The survey on MTurk was titled “Follow-up survey to "Read about Covid-19 vaccines and answer a survey [March 8–9]", included the description “This is a follow-up to a survey we launched during March 8–9. You will be asked a few questions about what you remember from the vaccine safety research summary you were shown, and how it has affected you.”, and was tagged with the keywords “survey”, “covid”, “vaccine”, “follow-up”.

We first showed them a screenshot of our different conditions to remind them which survey we were referring to. Next, we asked them to indicate which types of activities (“Thought about the research summary from the original survey,” “Mentioned the research summary (or information from it) in a conversation with someone else”, “Searched for research about COVID-19 vaccine safety,” or “Made a decision about whether or not to get vaccinated”) they had engaged in since participating in the original experiment (all on 5-point scales). For each option they indicated, participants were asked to describe in more detail via open text entry. Finally they were asked to rate how much they agreed with the statement “Reading the research summary on COVID-19 vaccine safety helped me feel more confident talking about COVID-19 vaccine safety with others,” whether they had any additional thoughts, and were compensated.

Data availability

Anonymized interview transcripts and experimental data will be made freely available to any researcher wishing to use them for non-commercial purposes. Please contact the corresponding author for access.

Change history

03 january 2023.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-022-27366-6

Wheelock, A. & Ives, J. Vaccine confidence, public understanding and probity: Time for a shift in focus?. J. Med. Ethics 48 (4), 250–255 (2022).

Article Google Scholar

Cuadros, D. F., Miller, F. D., Awad, S., Coule, P. & MacKinnon, N. J. Analysis of vaccination rates and new COVID-19 infections by US county, July–August 2021. JAMA Netw. Open 5 (2), e2147915–e2147915 (2022).

Almaghaslah, D., Alsayari, A., Kandasamy, G. & Vasudevan, R. COVID-19 vaccine hesitancy among young adults in Saudi Arabia: A cross-sectional web-based study. Vaccines 9 (4), 330 (2021).

Article CAS Google Scholar

Doherty, I. A. et al. COVID-19 vaccine hesitancy in underserved communities of North Carolina. PLoS ONE 16 (11), e0248542 (2021).

Geana, M. V., Anderson, S. & Ramaswamy, M. COVID-19 vaccine hesitancy among women leaving jails: A qualitative study. Public Health Nurs. 38 (5), 892–896 (2021).

Lockyer, B. et al. Understanding COVID-19 misinformation and vaccine hesitancy in context: Findings from a qualitative study involving citizens in Bradford, UK. Health Expect. 24 (4), 1158–1167 (2021).

Maraqa, B. et al. COVID-19 vaccine hesitancy among health care workers in Palestine: A call for action. Prev. Med. 149 , 106618 (2021).

Okubo, R., Yoshioka, T., Ohfuji, S., Matsuo, T. & Tabuchi, T. COVID-19 vaccine hesitancy and its associated factors in Japan. Vaccines 9 (6), 662 (2021).

Prickett, K. C., Habibi, H. & Carr, P. A. COVID-19 vaccine hesitancy and acceptance in a cohort of diverse New Zealanders. Lancet Reg. Health-Western Pac. 14 , 100241 (2021).

Wang, K. et al. Change of willingness to accept COVID-19 vaccine and reasons of vaccine hesitancy of working people at different waves of local epidemic in Hong Kong, China: Repeated cross-sectional surveys. Vaccines 9 (1), 62 (2021).

Sgaier, S. K. Meet the four kinds of people holding us back from full vaccination. New York Times https://www.nytimes.com/interactive/2021/05/18/opinion/covid-19-vaccine-hesitancy.html (2021).

Schernhammer, E. et al. Correlates of COVID-19 vaccine hesitancy in Austria: Trust and the government. J. Public Health 44 , 1–10 (2021).

Google Scholar

Palmedo, P. C., Rauh, L., Lathan, H. S. & Ratzan, S. C. Exploring distrust in the wait and see: Lessons for vaccine communication. Am. Behav. Sci. 1 , 27642 (2021).

Salmon, D. A. et al. MomsTalkShots: An individually tailored educational application for maternal and infant vaccines. Vaccine 37 (43), 6478–6485 (2019).

Bennett, A. et al. Human papillomavirus vaccine uptake after a tailored, online educational intervention for female university students: A randomized controlled trial. J. Women’s Health 24 (11), 950–957 (2015).

Daley, M. F., Narwaney, K. J., Shoup, J. A., Wagner, N. M. & Glanz, J. M. Addressing parents’ vaccine concerns: A randomized trial of a social media intervention. Am. J. Prev. Med. 55 (1), 44–54 (2018).

Finnegan, G. et al. Lessons from an online vaccine communication project. Vaccine 36 (44), 6509–6511 (2018).

do Nascimento, A. et al. Coronavirus disease (COVID-19) pandemic: An overview of systematic reviews. BMC Infect. Dis. 21 (1), 1–24 (2021).

MathSciNet Google Scholar

Valizadeh-Haghi, S., Khazaal, Y. & Rahmatizadeh, S. Health websites on COVID-19: Are they readable and credible enough to help public self-care?. J. Med. Lib. Assoc. 109 (1), 75 (2021).

Vivion, M., Hennequin, C., Verger, P. & Dubé, E. Supporting informed decision-making about vaccination: An analysis of two official websites. Public Health 178 , 112–119 (2020).

van der Linden, S. L., Clarke, C. E. & Maibach, E. W. Highlighting consensus among medical scientists increases public support for vaccines: Evidence from a randomized experiment. BMC Public Health 15 (1), 1–5 (2015).

van der Linden, S. L., Leiserowitz, A. A., Feinberg, G. D. & Maibach, E. W. The scientific consensus on climate change as a gateway belief: Experimental evidence. PLoS ONE 10 (2), e0118489 (2015).

Chinn, S., Lane, D. S. & Hart, P. S. In consensus we trust? Persuasive effects of scientific consensus communication. Public Underst. Sci. 27 (7), 807–823 (2018).

Landrum, A. R. & Slater, M. H. Open questions in scientific consensus messaging research. Environ. Commun. 14 (8), 1033–1046 (2020).

Hart, P. S. & Nisbet, E. C. Boomerang effects in science communication: How motivated reasoning and identity cues amplify opinion polarization about climate mitigation policies. Commun. Res. 39 (6), 701–723 (2012).

Hamilton, L. C. & Safford, T. G. Elite cues and the rapid decline in trust in science agencies on COVID-19. Sociol. Perspect. 64 (5), 988–1011 (2021).

Gasson, S. Human-centered vs user-centered approaches to information system design. J. Inf. Technol. Theory Appl. 5 (2), 5 (2003).

Burkett, I. An introduction to co-design. Sydney: Knode . http://ingridburkett.com/wp-content/uploads/2017/09/Introduction-to-Codesign-2.pdf (2012).

Yuan, S., & Dong, H. Empathy building through co-design. in International Conference on Universal Access in Human-Computer Interaction, 85–91 (2014).

Rosenberg, B. D. & Siegel, J. T. A 50-year review of psychological reactance theory: Do not read this article. Motivat. Sci. 4 (4), 281 (2018).

Richards, A. S., Bessarabova, E., Banas, J. A. & Bernard, D. R. Reducing psychological reactance to health promotion messages: Comparing preemptive and postscript mitigation strategies. Health Commun. 37 (3), 366–374 (2020).

Douglas, K. M., Sutton, R. M. & Cichocka, A. The psychology of conspiracy theories. Curr. Dir. Psychol. Sci. 26 (6), 538–542 (2017).

Natoli, E. E. & Marques, M. D. The antidepressant hoax: Conspiracy theories decrease health-seeking intentions. Br. J. Soc. Psychol. 60 (3), 902–923 (2021).

Van Prooijen, J. W. Empowerment as a tool to reduce belief in conspiracy theories. in Conspiracy theories and the people who believe them , 432–442 (2018).

Braun, V., & Clarke, V. Thematic analysis. in APA Handbook of Research Methods in Psychology, Vol 2: Research Designs: Quantitative, Qualitative, Neuropsychological, and Biological , 57–71 (2012).

Jensen, J. D. & Hurley, R. J. Conflicting stories about public scientific controversies: Effects of news convergence and divergence on scientists’ credibility. Public Underst. Sci. 21 (6), 689–704 (2012).

Yale, R. N., Jensen, J. D., Carcioppolo, N., Sun, Y. & Liu, M. Examining first-and second-order factor structures for news credibility. Commun. Methods Meas. 9 (3), 152–169 (2015).

de HolandaCoelho, G. L., Hanel, P. & Wolf, L. The very efficient assessment of need for cognition: Developing a six-item version. Assessment 27 (8), 1870–1885 (2020).

Garcia-Retamero, R., Cokely, E. T., Ghazal, S. & Joeris, A. Measuring graph literacy without a test: A brief subjective assessment. Med. Decis. Making 36 (7), 854–867 (2016).

Download references

Funding was provided by Vaccine Confidence Fund (Grant No. VCF - 032).

Author information

Authors and affiliations.

Department of Human-Centered Design and Engineering, University of Washington, Seattle, USA

Spencer Williams, Brett A. Halperin & Gary Hsieh

Department of Medicine, University of Washington, Seattle, USA

Joy Lee & Joshua M. Liao

Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, USA

Katharina Reinecke

You can also search for this author in PubMed Google Scholar

Contributions

S.W.: Conceptualization; study design; data collection; analysis; intervention design; writing. J.L.: Literature review support; data collection; editing. B.H.: Intervention design; editing. J.L.: Conceptualization; supervision; editing. G.H.: Conceptualization; supervision; editing. K.R.: Conceptualization; supervision; editing.

Corresponding author

Correspondence to Spencer Williams .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this Article was revised: The original version of this Article contained an error in the name of the author Brett A. Halperin which was incorrectly given as Brett Halperin.

Supplementary Information

Supplementary information., rights and permissions.

Reprints and permissions

About this article

Cite this article.

Williams, S., Lee, J., Halperin, B.A. et al. Meta-summaries effective for improving awareness and understanding of COVID-19 vaccine safety research. Sci Rep 12 , 19987 (2022). https://doi.org/10.1038/s41598-022-24607-6

Download citation

Received : 07 July 2022

Accepted : 17 November 2022

Published : 21 November 2022

DOI : https://doi.org/10.1038/s41598-022-24607-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

Explore articles by subject
Guide to authors
Editorial policies

A man in a suit standing at a podium with a microphone

Are presidents good role models for vaccination uptake? DRC study shows only if they’re trusted, and people get to know about it

Senior researcher, University of Antwerp

Researcher, University of Antwerp

Development Economics Researcher, University of Antwerp

Associate Professor, University of Antwerp

Disclosure statement

Nik Stoop acknowledges financial support from Research Foundation Flanders through a post-doctoral scholarship (nr.: 12W8320N).

Elie Lunanga receives funding from University of Antwerp's Research Fund (DOCPRO – BOF scholarship FFB190256).

Lara Collart receives funding from Research Foundation Flanders (FWO) through a doctoral scholarship (11L9623N).

Marijke Verpoorten receives funding from Research Foundation Flanders (FWO, grant nr. G029321N).

View all partners

Immunisation is considered one of the most cost-effective public health interventions , saving millions of lives each year, and benefiting the health of the wider community through herd immunity.

Yet, there is as much reason to worry as to celebrate. During the COVID-19 pandemic, the world witnessed a strong disruption in routine immunisation, leading to an increase in outbreaks of diphtheria, measles, polio, and yellow fever in over 100 countries . On the one hand, this can be explained by challenges with the supply of vaccines and the reduced availability of healthcare workers due to confinement policies, illness, and the diversion of activities to COVID-19.

But declining confidence in vaccines also played a role . Indeed, vaccine hesitancy, the reluctance or refusal to vaccinate, is a key barrier to immunisation and a major threat to global health.

Some make the case that vaccine demand can be actively promoted through communication campaigns . While there is a large body of evidence on what and how to communicate, less is known about who should communicate.

Recent studies from the US suggest that the public vaccination of high-profile politicians may boost vaccine confidence.

But systematic information on such vaccine role modelling is lacking. And it’s unclear to what extent results apply in different settings.

In a recently published study we set out to close these gaps.

We used the Democratic Republic of Congo as our case study. Vaccine confidence strongly declined in this country during the COVID-19 pandemic. This is acause for concern, as Africa is already lagging behind the rest of the world in achieving universal vaccination coverage.

Our focus was to understand the extent to which the vaccination of a president in public view increased vaccine uptake.

We concluded from our findings that it does, but under two conditions. Firstly, citizens must see the president as trustworthy. And secondly, the president’s vaccination must be communicated as widely as possible and include parts of the country or communities where there is low media access.

Where these two conditions aren’t met, vaccinating public village leaders or respected older adult community members might be a more effective approach to increasing vaccine uptake.

Presidents and vaccines

We found that around the world, 168 out of 173 leaders explicitly supported the COVID-19 vaccination campaign, 139 leaders (80%) made their own COVID-19 vaccination public and 108 leaders (78% of those vaccinated) distributed a picture or video of their vaccination.

President Felix Tshisekedi of the DRC received his COVID-19 vaccine live on Congolese television on 13 September 2021.

Vaccination rates in the country were low. By March 2022, only 5.7% of the population had received at least one vaccine dose, and just 1.03% were fully vaccinated. A number of factors were behind these low numbers:

low confidence in COVID-19 vaccines

a combination of limited healthcare services, poor transport infrastructure, and concerns about the safety of the AstraZenica vaccine, making the DRC unable to use most of the 1.7 million vaccine doses it received under the global Covax scheme for poorer countries

broader governance issues , including rampant corruption and political instability.

DR Congo is ranked near the bottom of the Human Development Index, occupying place 180 out of 193 countries. This indicates low levels of health, education and income. Our research took place in the country’s east, which has been plagued by violence for over two decades.

In addition, the region was facing an outbreak of the Ebola virus disease when COVID-19 hit.

Within this context, we analysed the potential of President Tshisekedi to act as a vaccine ambassador and influence COVID-19 vaccine uptake.

In September 2021, we conducted a survey with 600 people in six villages of Lubero territory, in the province of North Kivu. Lubero is a remote and mostly rural area with poor public infrastructure and little access to media or news outlets. COVID-19 vaccines were not yet available in the study area.

Our survey started before Tshisekedi got vaccinated.

We asked: “Let’s assume a vaccine against coronavirus was available for you; would you take it?”.

While 98% of respondents said they had vaccinated their children against diseases such as tuberculosis, polio or measles, only 22% indicated they would accept a COVID-19 vaccine.

From answers to open questions we learned that this mismatch can largely be explained by respondents’ general lack of trust in the COVID-19 vaccine and its efficacy, and the fear of potentially mortal side-effects.

We further found low levels of institutional trust. Only 17% of respondents indicated they trusted the president when asked to what extent they believed he represented the best interests of the Congolese population.

Respondents also reported low phone ownership and access to media. In the week prior to the survey, 91% of respondents did not watch television and 57% did not listen to the radio.

Prior to asking about COVID-19 vaccine acceptance, a random third of respondents received the prompt: “Assume the president, Félix Tshisekedi, were to take the vaccine live on television”.

We measured the impact of this prompt by comparing respondents’ stated vaccine acceptance to that of a randomly selected control group and found that trust moderated the results. For those who reported trusting the president, we found that the survey experiment boosted vaccine acceptance by 25 percentage points. Instead, for those who mistrusted the president, vaccine acceptance was lower among those who saw the prompt, by 6 percentage points.

To our surprise, the president got publicly vaccinated while our survey was in progress. Given low media access in our study region, only 18% of those interviewed after the broadcasting of Tshisekedi’s vaccination reported being aware of it. When comparing respondents with similar socio-economic profiles, access to media and levels of trust, we found that being aware of the president’s vaccination increased vaccine acceptance by 20 percentage points.

Policy implications

Our findings highlight that to serve as a vaccination model:

the leader should be perceived as trustworthy by citizens

the vaccination should be widely communicated.

When trust in national leaders is lacking, or news on their actions is inaccessible, other leaders might be more effective in boosting vaccine acceptance.

Immunisation
World Health Organization (WHO)
Anti-vaccination
Democratic Republic of the Congo (DRC)

Dean (Head of School), Indigenous Knowledges

Business Improvement Lead

Senior Research Fellow - Curtin Institute for Energy Transition (CIET)

Laboratory Head - RNA Biology

Head of School, School of Arts & Social Sciences, Monash University Malaysia

Coronavirus Pandemic (COVID-19)

Research and data: Edouard Mathieu, Hannah Ritchie, Lucas Rodés-Guirao, Cameron Appel, Daniel Gavrilov, Charlie Giattino, Joe Hasell, Bobbie Macdonald, Saloni Dattani, Diana Beltekian, Esteban Ortiz-Ospina, and Max Roser

Coronavirus
Data explorer
Hospitalizations
Vaccinations
Mortality risk
Excess mortality
Policy responses

Explore all metrics – including cases, deaths, testing, and vaccinations – in one place.

Get an overview of the pandemic for any country on a single page.

Download our complete dataset of COVID-19 metrics on GitHub. It’s open access and free for anyone to use.

Explore our global dataset on COVID-19 vaccinations.

See state-by-state data on vaccinations in the United States.

Explore the data on confirmed COVID-19 cases for all countries.

Explore the data on confirmed COVID-19 deaths for all countries.

Explore our data on COVID-19 testing to see how confirmed cases compare to actual infections.

See data on how many people are being hospitalized for COVID-19.

See how government policy responses – on travel, testing, vaccinations, face coverings, and more – vary across the world.

Learn what we know about the mortality risk of COVID-19 and explore the data used to calculate it.

Compare the number of deaths from all causes during COVID-19 to the years before to gauge the total impact of the pandemic on deaths.

Explore the global situation

→ Open the Data Explorer in a new tab.

Coronavirus Country Profiles

We built 207 country profiles which allow you to explore the statistics on the coronavirus pandemic for every country in the world .

In a fast-evolving pandemic it is not a simple matter to identify the countries that are most successful in making progress against it. For a comprehensive assessment, we track the impact of the pandemic across our publication and we built country profiles for 207 countries to study in depth the statistics on the coronavirus pandemic for every country in the world .

Each profile includes interactive visualizations , explanations of the presented metrics, and the details on the sources of the data .

Every country profile is updated daily .

Our 12 most visited country profiles

United States
United Kingdom
New Zealand

Every profile includes five sections:

Cases: How many new cases are being confirmed each day? How many cases have been confirmed since the pandemic started? How is the number of cases changing?
Deaths: How many deaths from COVID-19 have been reported? Is the number of deaths rising or falling? How does the death rate compare to other countries?
Vaccinations: How many vaccine doses are being administered each day? How many doses have been administered in total? What share of the population has been vaccinated?
Testing: How much testing for coronavirus do countries conduct? How many tests did a country do to find one COVID-19 case?
Government responses: What measures did countries take in response to the pandemic?

Acknowledgements

We would like to acknowledge and thank a number of people in the development of this work: Carl Bergstrom , Bernadeta Dadonaite , Natalie Dean , Joel Hellewell, Jason Hendry , Adam Kucharski , Moritz Kraemer and Eric Topol for their very helpful and detailed comments and suggestions on earlier versions of this work. We thank Tom Chivers for his editorial review and feedback.

And we would like to thank the many hundreds of readers who give us feedback on this work. Your feedback is what allows us to continuously clarify and improve it. We very much appreciate you taking the time to write. We cannot respond to every message we receive, but we do read all feedback and aim to take the many helpful ideas into account.

Our World in Data is free and accessible for everyone.

Help us do this work by making a donation.

COVID-19 vaccines: Get the facts

Looking to get the facts about COVID-19 vaccines? Here's what you need to know about the different vaccines and the benefits of getting vaccinated.

As the coronavirus disease 2019 (COVID-19) continues to cause illness, you might have questions about COVID-19 vaccines. Find out about the different types of COVID-19 vaccines, how they work, the possible side effects, and the benefits for you and your family.

COVID-19 vaccine benefits

What are the benefits of getting a covid-19 vaccine.

Staying up to date with a COVID-19 vaccine can:

Help prevent serious illness and death due to COVID-19 for both children and adults.
Help prevent you from needing to go to the hospital due to COVID-19 .
Be a less risky way to protect yourself compared to getting sick with the virus that causes COVID-19.
Lower long-term risk for cardiovascular complications after COVID-19.

Factors that can affect how well you're protected after a vaccine can include your age, if you've had COVID-19 before or if you have medical conditions such as cancer.

How well a COVID-19 vaccine protects you also depends on timing, such as when you got the shot. And your level of protection depends on how the virus that causes COVID-19 changes and what variants the vaccine protects against.

Talk to your healthcare team about how you can stay up to date with COVID-19 vaccines.

Should I get the COVID-19 vaccine even if I've already had COVID-19?

Yes. Catching the virus that causes COVID-19 or getting a COVID-19 vaccination gives you protection, also called immunity, from the virus. But over time, that protection seems to fade. The COVID-19 vaccine can boost your body's protection.

Also, the virus that causes COVID-19 can change, also called mutate. Vaccination with the most up-to-date variant that is spreading or expected to spread helps keep you from getting sick again.

Researchers continue to study what happens when someone has COVID-19 a second time. Later infections are generally milder than the first infection. But severe illness can still happen. Serious illness is more likely among people older than age 65, people with more than four medical conditions and people with weakened immune systems.

Safety and side effects of COVID-19 vaccines

What covid-19 vaccines have been authorized or approved.

The COVID-19 vaccines available in the United States are:

2023-2024 Pfizer-BioNTech COVID-19 vaccine, available for people age 6 months and older.
2023-2024 Moderna COVID-19 vaccine, available for people age 6 months and older.
2023-2024 Novavax COVID-19 vaccine, available for people age 12 years and older.

These vaccines have U.S. Food and Drug Administration (FDA) emergency use authorization or approval.

In December 2020, the Pfizer-BioNTech COVID-19 vaccine two-dose series was found to be both safe and effective in preventing COVID-19 infection in people age 18 and older. This data helped predict how well the vaccines would work for younger people. The effectiveness varied by age.

The Pfizer-BioNTech vaccine is approved under the name Comirnaty for people age 12 and older. The FDA authorized the vaccine for people age 6 months to 11 years. The number of shots in this vaccination series varies based on a person's age and COVID-19 vaccination history.

In December 2020, the Moderna COVID-19 vaccine was found to be both safe and effective in preventing infection and serious illness among people age 18 or older. The vaccine's ability to protect younger people was predicted based on that clinical trial data.

The FDA approved the vaccine under the name Spikevax for people age 12 and older. The FDA authorized use of the vaccine in people age 6 months to 11 years. The number of shots needed varies based on a person's age and COVID-19 vaccination history.

In July 2022, this vaccine was found to be safe and effective and became available under an emergency use authorization for people age 18 and older.

In August 2022, the FDA authorized the vaccine for people age 12 and older. The number of shots in this vaccination series varies based on a person's age and COVID-19 vaccination history.

In August 2022, the FDA authorized an update to the Moderna and the Pfizer-BioNTech COVID-19 vaccines. Both included the original and omicron variants of the virus that causes COVID-19. In June 2023, the FDA directed vaccine makers to update COVID-19 vaccines. The vaccines were changed to target a strain of the virus that causes COVID-19 called XBB.1.5. In September and October 2023, the FDA authorized the use of the updated 2023-2024 COVID-19 vaccines made by Novavax, Moderna and Pfizer-BioNTech.

How do the COVID-19 vaccines work?

COVID-19 vaccines help the body get ready to clear out infection with the virus that causes COVID-19.

Both the Pfizer-BioNTech and the Moderna COVID-19 vaccines use genetically engineered messenger RNA (mRNA). The mRNA in the vaccine tells your cells how to make a harmless piece of virus that causes COVID-19.

After you get an mRNA COVID-19 vaccine, your muscle cells begin making the protein pieces and displaying them on cell surfaces. The immune system recognizes the protein and begins building an immune response and making antibodies. After delivering instructions, the mRNA is immediately broken down. It never enters the nucleus of your cells, where your DNA is kept.

The Novavax COVID-19 adjuvanted vaccine is a protein subunit vaccine. These vaccines include only protein pieces of a virus that cause your immune system to react the most. The Novavax COVID-19 vaccine also has an ingredient called an adjuvant that helps raise your immune system response.

With a protein subunit vaccine, the body reacts to the proteins and creates antibodies and defensive white blood cells. If you later become infected with the COVID-19 virus, the antibodies will fight the virus. Protein subunit COVID-19 vaccines don't use any live virus and can't cause you to become infected with the COVID-19 virus. The protein pieces also don't enter the nucleus of your cells, where your DNA is kept.

Can a COVID-19 vaccine give you COVID-19?

No. The COVID-19 vaccines available in the U.S. don't use the live virus that causes COVID-19. Because of this, the COVID-19 vaccines can't cause you to become sick with COVID-19.

It can take a few weeks for your body to build immunity after getting a COVID-19 vaccination. As a result, it's possible that you could become infected with the virus that causes COVID-19 just before or after being vaccinated.

What are the possible general side effects of a COVID-19 vaccine?

Some people have no side effects from the COVID-19 vaccine. For those who get them, most side effects go away in a few days.

A COVID-19 vaccine can cause mild side effects after the first or second dose. Pain and swelling where people got the shot is a common side effect. That area also may look reddish on white skin. Other side effects include:

Fever or chills.
Muscle pain or joint pain.
Tiredness, called fatigue.
Upset stomach or vomiting.
Swollen lymph nodes.

For younger children up to age 4, symptoms may include crying or fussiness, sleepiness, loss of appetite, or, less often, a fever.

In rare cases, getting a COVID-19 vaccine can cause an allergic reaction. Symptoms of a life-threatening allergic reaction can include:

Breathing problems.
Fast heartbeat, dizziness or weakness.
Swelling in the throat.

If you or a person you're caring for has any life-threatening symptoms, get emergency care.

Less serious allergic reactions include a general rash other than where you got the vaccine, or swelling of the lips, face or skin other than where you got the shot. Contact your healthcare professional if you have any of these symptoms.

You may be asked to stay where you got the vaccine for about 15 minutes after the shot. This allows the healthcare team to help you if you have an allergic reaction. The healthcare team may ask you to wait for longer if you had an allergic reaction from a previous shot that wasn't serious.

Contact a healthcare professional if the area where you got the shot gets worse after 24 hours. And if you're worried about any side effects, contact your healthcare team.

Are there any long-term side effects of the COVID-19 vaccines?

The vaccines that help protect against COVID-19 are safe and effective. Clinical trials tested the vaccines to make sure of those facts. Healthcare professionals, researchers and health agencies continue to watch for rare side effects, even after hundreds of millions of doses have been given in the United States.

Side effects that don't go away after a few days are thought of as long term. Vaccines rarely cause any long-term side effects.

If you're concerned about side effects, safety data on COVID-19 vaccines is reported to a national program called the Vaccine Adverse Event Reporting System in the U.S. This data is available to the public. The U.S. Centers for Disease Control and Protection (CDC) also has created v-safe, a smartphone-based tool that allows users to report COVID-19 vaccine side effects.

If you have other questions or concerns about your symptoms, talk to your healthcare professional.

Can COVID-19 vaccines affect the heart?

In some people, COVID-19 vaccines can lead to heart complications called myocarditis and pericarditis. Myocarditis is the swelling, also called inflammation, of the heart muscle. Pericarditis is the swelling, also called inflammation, of the lining outside the heart.

Symptoms to watch for include:

Chest pain.
Shortness of breath.
Feelings of having a fast-beating, fluttering or pounding heart.

If you or your child has any of these symptoms within a week of getting a COVID-19 vaccine, seek medical care.

The risk of myocarditis or pericarditis after a COVID-19 vaccine is rare. These conditions have been reported after COVID-19 vaccination with any of the vaccines offered in the United States. Most cases have been reported in males ages 12 to 39.

These conditions happened more often after the second dose of the COVID-19 vaccine and typically within one week of COVID-19 vaccination. Most of the people who got care felt better after receiving medicine and resting.

These complications are rare and also may happen after getting sick with the virus that causes COVID-19. In general, research on the effects of the most used COVID-19 vaccines in the United States suggests the vaccines lower the risk of complications such as blood clots or other types of damage to the heart.

If you have concerns, your healthcare professional can help you review the risks and benefits based on your health condition.

Things to know before a COVID-19 vaccine

Are covid-19 vaccines free.

In the U.S., COVID-19 vaccines may be offered at no cost through insurance coverage. For people whose vaccines aren't covered or for those who don't have health insurance, options are available. Anyone younger than 18 years old can get no-cost vaccines through the Vaccines for Children program. Adults can get no-cost COVID-19 vaccines through the temporary Bridges to Access program, which is scheduled to end in December 2024.

Can I get a COVID-19 vaccine if I have an existing health condition?

Yes, COVID-19 vaccines are safe for people who have existing health conditions, including conditions that have a higher risk of getting serious illness with COVID-19.

The COVID-19 vaccine can lower the risk of death or serious illness caused by COVID-19. Your healthcare team may suggest that you get added doses of a COVID-19 vaccine if you have a moderately or severely weakened immune system.

Cancer treatments and other therapies that affect some immune cells also may affect your COVID-19 vaccine. Talk to your healthcare professional about timing additional shots and getting vaccinated after immunosuppressive treatment.

Talk to your healthcare team if you have any questions about when to get a COVID-19 vaccine.

Is it OK to take an over-the-counter pain medicine before or after getting a COVID-19 vaccine?

Don't take medicine before getting a COVID-19 vaccine to prevent possible discomfort. It's not clear how these medicines might impact the effectiveness of the vaccines. It is OK to take this kind of medicine after getting a COVID-19 vaccine, as long as you have no other medical reason that would prevent you from taking it.

Allergic reactions and COVID-19 vaccines

What are the signs of an allergic reaction to a covid-19 vaccine.

Symptoms of a life-threatening allergic reaction can include:

If you or a person you're caring for has any life-threatening symptoms, get emergency care right away.

Less serious allergic reactions include a general rash other than where you got the vaccine, or swelling of the lips, face or skin other than where the shot was given. Contact your healthcare professional if you have any of these symptoms.

Tell your healthcare professional about your reaction, even if it went away on its own or you didn't get emergency care. This reaction might mean that you are allergic to the vaccine. You might not be able to get a second dose of the same vaccine. But you might be able to get a different vaccine for your second dose.

Can I get a COVID-19 vaccine if I have a history of allergic reactions?

If you have a history of severe allergic reactions not related to vaccines or injectable medicines, you may still get a COVID-19 vaccine. You're typically monitored for 30 minutes after getting the vaccine.

If you've had an immediate allergic reaction to other vaccines or injectable medicines, ask your healthcare professional about getting a COVID-19 vaccine. If you've ever had an immediate or severe allergic reaction to any ingredient in a COVID-19 vaccine, the CDC recommends not getting that specific vaccine.

If you have an immediate or severe allergic reaction after getting the first dose of a COVID-19 vaccine, don't get the second dose. But you might be able to get a different vaccine for your second dose.

Pregnancy, breastfeeding and fertility with COVID-19 vaccines

Can pregnant or breastfeeding women get the covid-19 vaccine.

The CDC recommends getting a COVID-19 vaccine if:

You are planning to or trying to get pregnant.
You are pregnant now.
You are breastfeeding.

Staying up to date on your COVID-19 vaccine helps prevent severe COVID-19 illness. It also may help a newborn avoid getting COVID-19 if you are vaccinated during pregnancy.

People at higher risk of serious illness can talk to a healthcare professional about additional COVID-19 vaccines or other precautions. It also can help to ask about what to do if you get sick so that you can quickly start treatment.

Children and COVID-19 vaccines

If children don't often experience severe illness with covid-19, why do they need a covid-19 vaccine.

While rare, some children can become seriously ill with COVID-19 after getting the virus that causes COVID-19 .

A COVID-19 vaccine might prevent your child from getting the virus that causes COVID-19 . It also may prevent your child from becoming seriously ill or having to stay in the hospital due to the COVID-19 virus.

After a COVID-19 vaccine

Can i stop taking safety precautions after getting a covid-19 vaccine.

You can more safely return to activities that you might have avoided before your vaccine was up to date. You also may be able to spend time in closer contact with people who are at high risk for serious COVID-19 illness.

But vaccines are not 100% effective. So taking other action to lower your risk of getting COVID-19 still helps protect you and others from the virus. These steps are even more important when you're in an area with a high number of people with COVID-19 in the hospital. Protection also is important as time passes since your last vaccination.

If you are at higher risk for serious COVID-19 illness, basic actions to prevent COVID-19 are even more important. Some examples are:

Avoid close contact with anyone who is sick or has symptoms, if possible.
Use fans, open windows or doors, and use filters to move the air and keep any germs from lingering.
Wash your hands well and often with soap and water for at least 20 seconds. Or use an alcohol-based hand sanitizer with at least 60% alcohol.
Cough or sneeze into a tissue or your elbow. Then wash your hands.
Clean and disinfect high-touch surfaces. For example, clean doorknobs, light switches, electronics and counters regularly.
Spread out in crowded public areas, especially in places with poor airflow. This is important if you have a higher risk of serious illness.
The CDC recommends that people wear a mask in indoor public spaces if COVID-19 is spreading. This means that if you're in an area with a high number of people with COVID-19 in the hospital a mask can help protect you. The CDC suggests wearing the most protective mask possible that you'll wear regularly, that fits well and is comfortable.

Can I still get COVID-19 after I'm vaccinated?

COVID-19 vaccination will protect most people from getting sick with COVID-19. But some people who are up to date with their vaccines may still get COVID-19. These are called vaccine breakthrough infections.

People with vaccine breakthrough infections can spread COVID-19 to others. However, people who are up to date with their vaccines but who have a breakthrough infection are less likely to have serious illness with COVID-19 than those who are not vaccinated. Even when people who are vaccinated get symptoms, they tend to be less severe than those felt by unvaccinated people.

Researchers continue to study what happens when someone has COVID-19 a second time. Reinfections and breakthrough infections are generally milder than the first infection. But severe illness can still happen. Serious illness is more likely among people older than age 65, people with more than four medical conditions and people with weakened immune systems.

There is a problem with information submitted for this request. Review/update the information highlighted below and resubmit the form.

From Mayo Clinic to your inbox

Sign up for free and stay up to date on research advancements, health tips, current health topics, and expertise on managing health. Click here for an email preview.

Error Email field is required

Error Include a valid email address

To provide you with the most relevant and helpful information, and understand which information is beneficial, we may combine your email and website usage information with other information we have about you. If you are a Mayo Clinic patient, this could include protected health information. If we combine this information with your protected health information, we will treat all of that information as protected health information and will only use or disclose that information as set forth in our notice of privacy practices. You may opt-out of email communications at any time by clicking on the unsubscribe link in the e-mail.

Thank you for subscribing!

You'll soon start receiving the latest Mayo Clinic health information you requested in your inbox.

Sorry something went wrong with your subscription

Please, try again in a couple of minutes

Benefits of getting a COVID-19 vaccine. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/vaccine-benefits.html. Accessed April 15, 2024.
Mercadé-Besora N, et al. The role of COVID-19 vaccines in preventing post-COVID-19 thromboembolic and cardiovascular complications. Heart. 2024; doi: 10.1136/heartjnl-2023-323483.
Vaccine effectiveness studies. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/effectiveness/how-they-work.html. Accessed April 15, 2024.
Goldman L, et al., eds. COVID-19: Epidemiology, clinical manifestations, diagnosis, community prevention, and prognosis. In: Goldman-Cecil Medicine. 27th ed. Elsevier; 2024. https://www.clinicalkey.com. Accessed April 15, 2024.
Deng J, et al. Severity and outcomes of SARS-CoV-2 reinfection compared with primary infection: A systematic review and meta-analysis. International Journal of Environmental Research and Public Health. 2023; doi:10.3390/ijerph20043335.
What is COVID-19 reinfection? Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/your-health/reinfection.html. Accessed April 15, 2024.
Stay up to date with COVID-19 vaccines. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/stay-up-to-date.html. Accessed April 15, 2024.
Interim clinical considerations for use of COVID-19 vaccines in the United States. Centers for Disease Control and Prevention. https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Accessed April 15, 2024.
Comirnaty. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/Comirnaty. Accessed April 15, 2024.
Spikevax summary basis for regulatory action. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/Spikevax. Accessed April 15, 2024.
Spikevax package insert. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/Spikevax. Accessed April 15, 2024.
Overview of COVID-19 Vaccines. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/different-vaccines/overview-COVID-19-vaccines.html. Accessed April 15, 2024.
Novavax COVID-19 vaccine, adjuvanted. Food and Drug Administration. https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/novavax-covid-19-vaccine-adjuvanted. Accessed April 15, 2024.
Pfizer-BioNTech emergency use authorization for unapproved product review memorandum. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/Comirnaty. Accessed April 15, 2024.
Link-Gelles, et al. Estimates of bivalent mRNA vaccine durability in preventing COVID-19-associated hospitalization and critical illness among adults with and without immunocompromising conditions — VISION network, September 2022-April 2023. MMWR Morbidity and Mortality Weekly Report. 2023; doi:10.15585/mmwr.mm7221a3.
Updated COVID-19 vaccines for use in the United States beginning in fall 2023. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/updated-covid-19-vaccines-use-united-states-beginning-fall-2023. Accessed April 15, 2024.
Coronavirus (COVID-19), CBER-regulated biologics: COVID-19 vaccines. U.S. Food and Drug Administration. https://www.fda.gov/vaccines-blood-biologics/industry-biologics/coronavirus-covid-19-cber-regulated-biologics. Accessed April 15, 2024.
Understanding how COVID-19 vaccines work. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/different-vaccines/how-they-work.html. Accessed April 15, 2024.
Safety of COVID-19 vaccines. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/safety-of-vaccines.html. Accessed April 15, 2024.
Getting your COVID-19 vaccine. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/expect.html. Accessed April 15, 2024.
COVID-19 VIS. Centers for Disease Control and Prevention. https://www.cdc.gov/vaccines/hcp/vis/vis-statements/covid-19.html. Accessed April 15, 2024.
Allergic reactions after COVID-19 vaccination. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/allergic-reaction.html. Accessed April 15, 2024.
Orenstein W, et al., eds. Vaccine safety. In: Plotkin's Vaccines. 8th ed. Elsevier; 2024. https://www.clinicalkey.com. Accessed April 15, 2024.
Vaccine adverse event reporting system (VAERS). Vaccine Adverse Event Reporting System. https://vaers.hhs.gov/. Accessed April 15, 2024.
V-safe. Centers for Disease Control and Prevention. https://www.cdc.gov/vaccinesafety/ensuringsafety/monitoring/v-safe/index.html. Accessed April 15, 2024.
Myocarditis and pericarditis following mRNA COVID-19 vaccination. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/myocarditis.html. Accessed April 15, 2024.
Vaccines for children. Centers for Disease Control and Prevention. https://www.cdc.gov/vaccines/programs/vfc/index.html. Accessed April 15, 2024.
Bridge access program. Centers for Disease Control and Prevention. https://www.cdc.gov/vaccines/programs/bridge/index.html. Accessed April 15, 2024.
COVID-19: What people with cancer should know. National Cancer Institute. https://www.cancer.gov/about-cancer/coronavirus/coronavirus-cancer-patient-information. Accessed April 15, 2024.
COVID-19 vaccines while pregnant or breastfeeding. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/recommendations/pregnancy.html. Accessed April 15, 2024.
Berghella V, et al. COVID-19: Overview of pregnancy issues. https://www.uptodate.com/contents/search. Accessed April 15, 2024.
How to protect yourself and others. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html. Accessed April 15, 2024.
Pediatric data. Centers for Disease Control and Prevention. https://covid.cdc.gov/covid-data-tracker/#pediatric-data. Accessed April 15, 2024.
Hygiene and respiratory viruses prevention. Centers for Disease Control and Prevention. https://www.cdc.gov/respiratory-viruses/prevention/hygiene.html. Accessed April 15, 2024.

Products and Services

A Book: Endemic - A Post-Pandemic Playbook
Begin Exploring Women's Health Solutions at Mayo Clinic Store
A Book: Future Care
Antibiotics: Are you misusing them?
COVID-19 and vitamin D
Convalescent plasma therapy
Coronavirus disease 2019 (COVID-19)
COVID-19: How can I protect myself?
Herd immunity and respiratory illness
COVID-19 and pets
COVID-19 and your mental health
COVID-19 antibody testing
COVID-19, cold, allergies and the flu
Long-term effects of COVID-19
COVID-19 tests
COVID-19 drugs: Are there any that work?
COVID-19 in babies and children
Coronavirus infection by race
COVID-19 travel advice
COVID-19 vaccine: Should I reschedule my mammogram?
COVID-19 vaccines for kids: What you need to know
COVID-19 variant
COVID-19 vs. flu: Similarities and differences
COVID-19: Who's at higher risk of serious symptoms?
Debunking coronavirus myths
Different COVID-19 vaccines
Extracorporeal membrane oxygenation (ECMO)
Fever: First aid
Fever treatment: Quick guide to treating a fever
Fight coronavirus (COVID-19) transmission at home
Honey: An effective cough remedy?
How do COVID-19 antibody tests differ from diagnostic tests?
How to measure your respiratory rate
How to take your pulse
How to take your temperature
How well do face masks protect against COVID-19?
Is hydroxychloroquine a treatment for COVID-19?
Loss of smell
Mayo Clinic Minute: You're washing your hands all wrong
Mayo Clinic Minute: How dirty are common surfaces?
Multisystem inflammatory syndrome in children (MIS-C)
Nausea and vomiting
Pregnancy and COVID-19
Safe outdoor activities during the COVID-19 pandemic
Safety tips for attending school during COVID-19
Sex and COVID-19
Shortness of breath
Thermometers: Understand the options
Treating COVID-19 at home
Unusual symptoms of coronavirus
Vaccine guidance from Mayo Clinic
Watery eyes

Related information

Debunking COVID-19 myths - Related information Debunking COVID-19 myths
Different types of COVID-19 vaccines: How they work - Related information Different types of COVID-19 vaccines: How they work
COVID-19 vaccines for kids: What you need to know - Related information COVID-19 vaccines for kids: What you need to know
COVID-19 vaccines Get the facts

We’re transforming healthcare

Make a gift now and help create new and better solutions for more than 1.3 million patients who turn to Mayo Clinic each year.

Skip to main content
Skip to FDA Search
Skip to in this section menu
Skip to footer links

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

U.S. Food and Drug Administration

Search
Menu
Vaccines, Blood & Biologics

Vaccines, as with all products regulated by FDA, undergo a rigorous review of laboratory and clinical data to ensure the safety, efficacy, purity and potency of these products. Vaccines approved for marketing may also be required to undergo additional studies to further evaluate the vaccine and often to address specific questions about the vaccine's safety, effectiveness or possible side effects.

According to the Centers for Disease Control and Prevention, vaccines have reduced preventable infectious diseases to an all-time low and now few people experience the devastating effects of measles, pertussis and other illnesses.

The Center for Biologics Evaluation and Research (CBER) regulates vaccine products. Many of these are childhood vaccines that have contributed to a significant reduction of vaccine-preventable diseases.

Vaccine Information

Emergency Use Authorization for Vaccines Explained
Biologics License Applications (BLA) Process (CBER)
CDC National Immunization Program
Questions about Vaccines
Vaccines and Related Biological Products Advisory Committee
Vaccine and Related Biological Product Guidances
Vaccines Licensed for Use in the United States
Vaccine Notices, Proposed and Final Rules
Vaccine Safety & Availability
Common Ingredients in FDA-Approved Vaccines
Vaccine Adverse Events
Influenza Virus Vaccine Safety & Availability
Vaccine Safety Questions and Answers
Recommendations for the Use of Vaccines Manufactured with Bovine-Derived Materials
Thimerosal in Vaccines
MMWR - Guillain-Barre Syndrome Among Recipients of Menactra Meningococcal Conjugate Vaccine
Vaccines for Use During Pregnancy to Protect Young Infants from Disease - FDA Update

Medical Countermeasures

Key Facts About Vaccines to Prevent Monkeypox Disease
Update: COVID-19 Vaccine Booster Composition
Memorandum Re: Fall 2022 COVID-19 Vaccine Strain Composition Selection Recommendation
Pandemic Influenza Information

Seasonal Information

Is It a Cold or the Flu? Prevention, Symptoms, Treatments

Related Information

Vaccines Research

Follow CBER

Division of Communication and Consumer Affairs Office of Communication, Outreach and Development Center for Biologics Evaluation and Research Food and Drug Administration 10903 New Hampshire Ave WO71-3103 Silver Spring, MD 20993-0002

(800) 835-4709 (240) 402-8010

For Updates on Twitter, follow @fdacber

Resources for You (Biologics)
About the Center for Biologics Evaluation and Research (CBER)
Report a Problem to the Center for Biologics Evaluation & Research
Recalls (Biologics)
CBER-Regulated Products: Shortages and Discontinuations
Biologics Products & Establishments

Subscribe for CBER Updates

Get e-mail updates on What’s New at CBER!

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
Proc Natl Acad Sci U S A
v.114(16); 2017 Apr 18

Simply put: Vaccination saves lives

Walter a. orenstein.

a Department of Medicine, Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, 30322;

b Department of Microbiology & Immunology, Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, 30322

Author contributions: W.A.O. and R.A. wrote the paper.

Few measures in public health can compare with the impact of vaccines. Vaccinations have reduced disease, disability, and death from a variety of infectious diseases. For example, in the United States, children are recommended to be vaccinated against 16 diseases ( 1 ). Table 1 highlights the impact in the United States of immunization against nine vaccine-preventable diseases, including smallpox and a complication of one of those diseases, congenital rubella syndrome, showing representative annual numbers of cases in the 20th century compared with 2016 reported cases ( 2 , 3 ). All of the diseases have been reduced by more than 90% and many have either been eliminated or reductions of 99% or more have been achieved. A recent analysis of vaccines to protect against 13 diseases estimated that for a single birth cohort nearly 20 million cases of diseases were prevented, including over 40,000 deaths ( 4 ). In addition to saving the lives of our children, vaccination has resulted in net economic benefits to society amounting to almost $69 billion in the United States alone. A recent economic analysis of 10 vaccines for 94 low- and middle-income countries estimated that an investment of $34 billion for the immunization programs resulted in savings of $586 billion in reducing costs of illness and $1.53 trillion when broader economic benefits were included ( 5 ). The only human disease ever eradicated, smallpox, was eradicated using a vaccine, and a second, polio, is near eradication, also using vaccines ( 6 , 7 ).

Comparison of 20th century annual morbidity and current estimates vaccine-preventable diseases

Disease	20th Century annual morbidity ( )	2016 Reported cases ( )	Percent decrease (%)
Smallpox	29,005	0	100
Diphtheria	21,053	0	100
Measles	530,217	69	>99
Mumps	162,344	5,311	97
Pertussis	200,752	15,737	92
Polio (paralytic)	16,316	0	100
Rubella	47,745	5	>99
Congenital rubella syndrome	152	1	99
Tetanus	580	33	94
	20,000	22	>99

Vaccines not only provide individual protection for those persons who are vaccinated, they can also provide community protection by reducing the spread of disease within a population ( Fig. 1 ). Person-to-person infection is spread when a transmitting case comes in contact with a susceptible person. If the transmitting case only comes in contact with immune individuals, then the infection does not spread beyond the index case and is rapidly controlled within the population. Interestingly, this chain of human-to-human transmission can be interrupted, even if there is not 100% immunity, because transmitting cases do not have infinite contacts; this is referred to as “herd immunity” or “community protection,” and is an important benefit of vaccination.

An external file that holds a picture, illustration, etc.
Object name is pnas.1704507114fig01.jpg

( A ) A highly susceptible population in which a transmitting case is likely to come in contact with a susceptible person leading to a chain of person-to-person transmission. ( B ) A highly immune population in which a transmitting case is unlikely to come in contact with a susceptible person, thereby breaking the chain of transmission and achieving indirect protection of remaining susceptibles because they are not exposed.

Mathematical modelers can estimate on average how many persons the typical transmitting case is capable of infecting if all of the contacts were susceptible (i.e., a population of 100% susceptibility). This number is known as R 0 , or the basic reproductive number. The immunity threshold needed within the population for terminating transmission can be calculated in percent as ( R 0 − 1)/ R 0 × 100 and is a guide to setting immunity levels and vaccination coverage targets for various diseases ( 8 ). For example, measles is one of the most contagious of vaccine-preventable diseases, with an estimated immunity threshold of 92–94%. In contrast, the protection threshold for rubella is estimated at 83–85%. Thus, eliminating rubella transmission is easier than measles, and when there are gaps in immunization coverage leading to accumulation of susceptibles, measles is often the first vaccine-preventable disease identified. Because of community protection induced by vaccines, persons who cannot be vaccinated (e.g., have contraindications or are younger than the age for whom vaccines are recommended), as well as persons who fail to make an adequate immune response to the vaccine (although most vaccines are highly effective, they are not 100% effective), can be protected indirectly because they are not exposed ( Fig. 1 ). Thus, for most vaccines, achieving high levels of coverage is important not only for individual protection but in preventing disease in vulnerable populations that cannot be directly protected by vaccination. This provides the rationale for interventions to achieve high population immunity, such as removing barriers that may prevent access to vaccines (e.g., providing recommended vaccines without cost), as well as mandates for immunization requirements for attending school ( 9 ). There are many reasons why vaccinations may not be received as recommended. One extreme is outright opposition to vaccines. Probably even more common may be that making the effort to receive vaccines (e.g., making the healthcare visits at the appropriate time so vaccines can be administered) may be a low priority compared with other issues, so in the absence of having a mandate for vaccination, other things take priority. Thus, appropriate mandates could help in making vaccination a priority for all ( 10 ).

It’s often said that vaccines save lives, but this is not strictly true; it is vaccination that saves lives. A vaccine that remains in the vial is 0% effective even if it is the best vaccine in the world. Thus, it is imperative that we all work together to assure that a high level of coverage is obtained among populations for whom vaccines are recommended. In some sense, vaccines have become victims of their own success. Diseases that once induced fear and sparked desire for vaccines are now rare, and there is a false and dangerous sense of complacency among the public.

In addition, in recent years, growing numbers of persons have become hesitant about vaccines, fearing side effects and not appreciative of the enormous health and economic benefits that vaccines provide. A CDC report on 159 measles cases reported between January 4 and April 2, 2015, showed that 68 United States residents with measles were unvaccinated, and of these 29 (43%) cited philosophical or religious objections to vaccination ( 11 ). A 2014 national web-based poll of parents in the United States estimated that 90.8% (89.3–92.1%) reported accepting or planning to accept all recommended noninfluenza childhood vaccines, 5.6% (4.6–6.9%) reported intentionally delaying one or more, and 3.6% (2.8–4.5%) reported refusing one or more vaccines ( 12 ). A national survey of pediatricians in the United States reported that the proportion of pediatricians reporting parental vaccine refusals increased from 74.5% in 2006 to 87.0% in 2013 ( 13 ). A 67-country survey on the state of vaccine confidence reported an average of 5.8% of respondents globally were skeptical about the importance of vaccines, with that proportion rising to more than 15% in some countries ( 14 ). One of the major concerns in recent years has been the allegations that vaccines can cause autism. There are three major theories advanced on the role of vaccines in causing autism: ( i ) measles, mumps, rubella vaccine (MMR); ( ii ) thimerosal, an ethyl mercury containing preservative in many vaccines in the United States in the past, now mostly out of vaccines recommended for children; and ( iii ) too many vaccines ( 15 ). There have been multiple well-conducted studies and independent reviews of those studies by the Institute of Medicine (now the National Academy of Medicine) that do not support a role for vaccines in causing autism ( 16 ). Independent evaluation of the safety of the immunization schedule has found it to be extremely safe ( 17 ). However, translating the science into information capable of influencing vaccine skeptics has been difficult.

The National Vaccine Advisory Committee (NVAC) in the United States issued a report in 2015, with 23 recommendations to assure high levels of vaccine confidence ( 18 ). The recommendations have five focus areas: ( i ) measuring and tracking vaccine confidence, ( ii ) communication and community strategies to increase vaccine confidence, ( iii ) healthcare provider strategies to increase vaccine confidence, ( iv ) policy strategies to increase vaccine confidence, and ( v ) continued support and monitoring of the state of vaccine confidence. Critical to assuring confidence is evidence-based research to evaluate which interventions are most effective. The NVAC recommended that a repository of evidence-based best practices for informing, educating, and communicating with parents and others in ways that foster or increase vaccine confidence be created. And while we have focused on children, vaccine preventable diseases exact a substantial health burden in adults and immunization coverage rates for most recommended vaccines are substantially lower for adults than those achieved for recommended vaccines in children. Thus, there is need not only in enhancing immunization rates in children but also in adults.

In summary, vaccines are some of the most effective and also cost-effective prevention tools we have. But vaccines that are not administered to persons for whom they are recommended are not useful. It is incumbent upon all of us who work in the healthcare setting, as well as community leaders, to stress to our friends and colleagues the importance of vaccination both for the individual vaccinated as well as for the communities in which the individuals live. Also critically important, there remains an urgent need for greater emphasis on research to develop vaccines for global diseases for which vaccines either do not exist or need improvement.

Acknowledgments

The authors thank Dianne Miller, Ali Ellebedy, and Sandra Roush for their assistance in preparation of the manuscript.

See Perspective on page 4055 .

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Understanding How COVID-19 Vaccines Work

What you need to know.

COVID-19 vaccines help our bodies develop immunity to the virus that causes COVID-19 without us having to get the illness.

Different COVID-19 vaccines may work in our bodies differently but all provide protection against the virus that causes COVID-19.
None of the COVID-19 vaccines can give you COVID-19.
Bringing new vaccines to the public involves various steps, all which must be followed to ensure they are safe and effective before they are made available for use.

How COVID-19 Vaccines Work

Woman with bandaid on arm after vaccination

Different types of vaccines work in different ways to offer protection. But with all types of vaccines, the body is left with a supply of “memory” T-lymphocytes as well as B-lymphocytes that will remember how to fight that virus in the future.

It typically takes a few weeks after vaccination for the body to produce T-lymphocytes and B-lymphocytes.

Sometimes after vaccination, the process of building immunity can cause symptoms, such as fever. These symptoms are normal signs the body is building immunity.

Types of Vaccines: mRNA, and Protein Subunit

There are different types of vaccines.

All COVID-19 vaccines prompt our bodies to recognize and help protect us from the virus that causes COVID-19.
Currently, there are two types of COVID-19 vaccines for use in the United States: mRNA , and protein subunit vaccines.

None of these vaccines can give you COVID-19.

Vaccines do not use any live virus.
Vaccines cannot cause infection with the virus that causes COVID-19 or other viruses.

They do not affect or interact with our DNA.

These vaccines do not enter the nucleus of the cell where our DNA (genetic material) is located, so it cannot change or influence our genes.

mRNA vaccines (Pfizer-BioNTech or Moderna)

To trigger an immune response, many vaccines put a weakened or inactivated germ into our bodies. Not mRNA vaccines. Instead, mRNA vaccines use mRNA created in a laboratory to teach our cells how to make a protein—or even just a piece of a protein—that triggers an immune response inside our bodies. This immune response, which produces antibodies, is what helps protect us from getting sick from that germ in the future.

Research for mRNA technology

Researchers have been studying and working with mRNA vaccines for decades .

In fact, mRNA vaccines have been studied before for flu, Zika, rabies, and cytomegalovirus (CMV).
Beyond vaccines, cancer research has also used mRNA to trigger the immune system to target specific cancer cells.
First, mRNA COVID-19 vaccines are given in the upper arm muscle or upper thigh, depending on the age of who is getting vaccinated.
After vaccination, the mRNA will enter the muscle cells. Once inside, they use the cells’ machinery to produce a harmless piece of what is called the spike protein. The spike protein is found on the surface of the virus that causes COVID-19. After the protein piece is made, our cells break down the mRNA and remove it, leaving the body as waste.
Next, our cells display the spike protein piece on their surface. Our immune system recognizes that the protein does not belong there. This triggers our immune system to produce antibodies and activate other immune cells to fight off what it thinks is an infection. This is what your body might do if you got sick with COVID-19.
At the end of the process, our bodies have learned how to help protect against future infection with the virus that causes COVID-19. The benefit is that people get this protection from a vaccine, without ever having to risk the potentially serious consequences of getting sick with COVID-19. Any side effects from getting the vaccine are normal signs the body is building protection.

How mRNA COVID-19 Vaccines Work

PDF infographic explaining how mRNA COVID-19 vaccines work.

English [128 KB, 1 page]
Other Languages

Protein subunit vaccines (Novavax)

Protein subunit vaccines contain pieces (proteins) of the virus that causes COVID-19. These virus pieces are the spike protein. The vaccine also contains another ingredient called an adjuvant that helps the immune system respond to that spike protein in the future. Once the immune system knows how to respond to the spike protein, the immune system will be able to respond quickly to the actual virus spike protein and protect you against COVID-19.

Research for protein subunit technology

Protein subunit vaccines have been used for years.

More than 30 years ago, a hepatitis B vaccine became the first protein subunit vaccine to be approved for use in people in the United States.
Another example of other protein subunit vaccines used today include whooping cough vaccines.
Protein subunit COVID-19 vaccines are given in the upper arm muscle. After vaccination, nearby cells pick up these proteins.
Next, our immune system recognizes that these proteins do not belong there. Another ingredient in the vaccine, the adjuvant, helps our immune system to produce antibodies and activate other immune cells to fight off what it thinks is an infection. This is what your body might do if you got sick with COVID-19.
At the end of the process, our bodies have learned how to help protect against future infection with the virus that causes COVID-19. The benefit is that people get this protection from a vaccine, without ever having to risk the potentially serious consequences of getting sick with COVID-19. Many side effects from getting the vaccine are normal signs the body is building protection.

How Protein Subunit COVID-19 Vaccines Work

PDF infographic explaining how Protein Subunit COVID-19 vaccines work.

English [953 KB, 1 page]

Developing COVID-19 Vaccines

While COVID-19 vaccines were developed rapidly, all steps have been taken to ensure their safety and effectiveness. Bringing a new vaccine to the public involves many steps including:

vaccine development,
clinical trials,
U.S. Food and Drug Administration (FDA) authorization or approval,
and development and approval of vaccine recommendations through the Advisory Committee on Immunization Practices (ACIP) and CDC.

As vaccines are distributed outside of clinical trials, monitoring systems are used to make sure that COVID-19 vaccines are safe.

New vaccines are first developed in laboratories. Scientists have been working for many years to develop vaccines against coronaviruses, such as those that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). SARS-CoV-2, the virus that causes COVID-19, is related to these other coronaviruses. The knowledge that was gained through past research on coronavirus vaccines helped speed up the initial development of the current COVID-19 vaccines.

After initial laboratory development, vaccines go through three phases of clinical trials to make sure they are safe and effective. No trial phases have been skipped.

The clinical trials for COVID-19 vaccines have involved tens of thousands of volunteers of different ages, races, and ethnicities.

Clinical trials for vaccines compare outcomes (such as how many people get sick) between people who are vaccinated and people who are not. Results from these trials have shown that COVID-19 vaccines are safe and effective , especially against severe illness, hospitalization, and death.

Before vaccines are made available to people in real-world settings, FDA assesses the findings from clinical trials. Initially, they determined that COVID-19 vaccines met FDA’s safety and effectiveness standards and granted those vaccines Emergency Use Authorizations (EUAs) . The EUAs allowed the vaccines to be quickly distributed for use while maintaining the same high safety standards required for all vaccines. Learn more in this video about EUAs .

FDA has granted full approval for some COVID-19 vaccines. Before granting approval, FDA reviewed evidence that built on the data and information submitted to support the EUA. This included:

preclinical and clinical trial data and information,
as well as details of the manufacturing process,
vaccine testing results to ensure vaccine quality, and
inspections of the sites where the vaccine is made.

These vaccines were found to meet the high standards for safety, effectiveness, and manufacturing quality FDA requires of an approved product. Learn more about the process for FDA approval .

When FDA authorizes or approves a COVID-19 vaccine, ACIP reviews all available data about that vaccine to determine whether to recommend it and who should receive it. These vaccine recommendations then go through an approval process that involves both ACIP and CDC.

Watch Video: Understanding ACIP and How Vaccine Recommendations are Made [00:05:02]

Hundreds of millions of people in the United States have received COVID-19 vaccines under the most intense safety monitoring in U.S. history.

Several monitoring systems continue to track outcomes from COVID-19 vaccines to ensure their safety. Some people have no side effects. Many people have reported common side effects after COVID-19 vaccination , like pain or swelling at the injection site, a headache, chills, or fever. These reactions are common and are normal signs that your body is building protection.

Reports of serious adverse events after vaccination are rare .

How can you prepare for vaccination?
What can you expect during and after your vaccination?
Uninsured? You can still get a free COVID-19 vaccine. Learn more about CDC’s Bridge Access program .

COVID-19 Clinical and Professional Resources

Coronaviruses
Vaccine Development Process: How Was Time Saved [779 KB, 1 Page]

To receive email updates about COVID-19, enter your email address:

Exit Notification / Disclaimer Policy

The Centers for Disease Control and Prevention (CDC) cannot attest to the accuracy of a non-federal website.
Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website.
You will be subject to the destination website's privacy policy when you follow the link.
CDC is not responsible for Section 508 compliance (accessibility) on other federal or private website.

IMD-mediated innate immune priming increases Drosophila survival and reduces pathogen transmission

June 10, 2024

IMD-mediated innate immune priming increases Drosophila survival and reduces pathogen transmission

Image credit: ppat.1012308

Calling all experts!

Plos pathogens welcomes talented individuals to join our editorial board. .

research article

Herpes simplex virus spreads rapidly in human foreskin, partly driven by chemokine-induced redistribution of Nectin-1 on keratinocytes

Insights into the initial events that lead to HSV1 infection and spread within human genital mucosa and definition of a time window of opportunity to target the virus before it enters epidermal nerves and becomes latent.

Image credit: ppat.1012267

Herpes simplex virus spreads rapidly in human foreskin, partly driven by chemokine-induced redistribution of Nectin-1 on keratinocytes

Recently Published Articles

Caenorhabditis briggsae isolates by two RNA viruses">Natural variation in infection specificity of Caenorhabditis briggsae isolates by two RNA viruses

Current Issue May 2024

The anti-apoptotic function of HSV-1 LAT in neuronal cell cultures but not its function during reactivation correlates with expression of two small non-coding RNAs, sncRNA1&2

LAT resides within the two sncRNAs, which works independently of its latency-reactivation function and it has suppressive effect on LAT expression in vivo and in vitro .

Image credit: ppat.1012307

The anti-apoptotic function of HSV-1 LAT in neuronal cell cultures but not its function during reactivation correlates with expression of two small non-coding RNAs, sncRNA1&2

Arboviruses antagonize insect Toll antiviral immune signaling to facilitate the coexistence of viruses with their vectors

Novel strategies to evade and even exploit insect Toll antiviral immune response to facilitate persistent viral transmission.

Image credit: ppat.1012318

Arboviruses antagonize insect Toll antiviral immune signaling to facilitate the coexistence of viruses with their vectors

Quantifying the fitness effects of resistance alleles with and without anthelmintic selection pressure using Caenorhabditis elegans

Multiple traits should be considered to understand resistance comprehensively and that the determination of whether a gene plays a role in anthelmintic resistance depends on the trait measured.

Image credit: ppat.1012245

Infectious hepatitis E virus is associated with the mature sperm head

HEV isolated from sperm remained infectious suggesting a potential transmission route via sexual partners.

Image credit: ppat.1012240

Protecting the endothelial glycocalyx in COVID-19

Hyperimmune activation or persistent presence of viral antigens are associated with EG damage and may potentially bring about continuous endothelial dysfunction even after clinical recovery.

Image credit: ppat.1012203

Research Article

The read-through transcription-mediated autoactivation circuit for virulence regulator expression drives robust type III secretion system 2 expression in Vibrio parahaemolyticus

Autoregulatory loop is essential for sustained vtrB activation ...

Image credit: ppat.1012094

Characterization and genomic analysis of the Lyme disease spirochete bacteriophage ϕBB-1

The ubiquitous ϕBB-1 phage and its implications in the generalized transduction of diverse genes and the maintenance of genetic diversity.

Image credit: ppat.1012122

Broad-spectrum Delta-BA.2 tandem-fused heterodimer mRNA vaccine delivered by lipopolyplex

This vaccine has demonstrated its ability to induce immunogenicity in mice and offers protection to both mice and monkeys when exposed to live SARS-CoV-2 challenges.

Image credit: ppat.1012116

Pathobiology and dysbiosis of the respiratory and intestinal microbiota in 14 months old Golden Syrian hamsters infected with SARS-CoV-2

Brittany Seibert, C. Joaquín Cáceres, and colleagues

Bile acids promote the caveolae-associated entry of swine acute diarrhea syndrome coronavirus in porcine intestinal enteroids

Qi-Yue Yang, Yong-Le Yang, and colleagues

Multi-omics analysis of the cervical epithelial integrity of women using depot medroxyprogesterone acetate

Frideborg Bradley and colleagues

Modulation of sensory perception by hydrogen peroxide enables Caenorhabditis elegans to find a niche that provides both food and protection from hydrogen peroxide

Jodie A. Schiffer & Stephanie V. Stumbur and colleagues

Evidence of MHC class I and II influencing viral and helminth infection via the microbiome in a non-human primate

B. Karina Montero and colleagues

Advances in understanding red blood cell modifications by Babesia

Hakimi et al.

After the virus has cleared—Can preclinical models be employed for Long COVID research?

Jansen et al.

Viral-mediated activation and inhibition of programmed cell death

Verburg et al.

Molecular architecture of bacterial type IV secretion systems

Sheedlo et al.

Bidirectional cytokine-microRNA control: A novel immunoregulatory framework in leishmaniasis

Jafarzadeh et al.

Publish with PLOS

Submission Instructions
Submit Your Manuscript

Connect with Us

PLOS Pathogens on Twitter
PLOS on Facebook

Get new content from PLOS Pathogens in your inbox

Thank you you have successfully subscribed to the plos pathogens newsletter., sorry, an error occurred while sending your subscription. please try again later..

IMAGES

70 Vaccination Research Paper Topics
≫ Vaccinations: Are There any Real Benefits? Free Essay Sample on
≫ Pro Vaccination Free Essay Sample on Samploon.com
≫ Vaccination Requirements for Children Free Essay Sample on Samploon.com
≫ Vaccinations: Questions Concerning Childhood Immunizations Free Essay
≫ Vaccinations For All Free Essay Sample on Samploon.com

VIDEO

Is vaccine hyperimmunity possible?
AstraZeneca Admits Its COVID Vaccine, Covishield, Can Cause Rare Side Effect #shorts #covishield
Questions about the COVID-19 Vaccine: Has There Been Enough Research?
Taking part in an adult vaccine study
SA-led HIV vaccination research programme receives R860m grant
Dr.Homi Bhabha Balvaidnyanik Competition

COMMENTS

Vaccine Effectiveness Studies in the Field
A recent test-negative design study in Canada showed positive findings regarding vaccine effectiveness with the BNT162b2, mRNA-1273, and ChAdOx1 nCoV-19 vaccines against symptomatic disease with ...
A guide to vaccinology: from basic principles to new developments
A vaccine is a biological product that can be used to safely induce an immune response that confers protection against infection and/or disease on subsequent exposure to a pathogen. To achieve ...
Vaccine Innovations
Vaccination is a powerful method of disease prevention that is relevant to people of all ages and in all countries, as the Covid-19 pandemic illustrates. Vaccination can improve people's chances ...
Comprehensive literature review on COVID-19 vaccines and role of SARS
Introduction. The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in over 192 million cases and 4.1 million deaths as of July 22, 2021. 1 This pandemic has brought along a massive burden in morbidity and mortality in the healthcare systems. Despite the implementation of stringent public health measures, there ...
Advances in vaccines: revolutionizing disease prevention
In another paper showcasing the benefits of an in silico approach, Palatnik‐de‐Sousa et al. 8 report the design and development of a multiepitope multivariant vaccine based on highly conserved ...
Willingness to vaccinate against Covid-19: A qualitative study
The thematic analysis resulted in three main themes in relation to our research question. The first theme refers to participants' understanding of the vaccination as a means to loosen current freedom-limiting protective measures; the second theme refers to participants' belief that protective measures will always be safer than the vaccine ...
Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
The Coronavirus Efficacy (COVE) phase 3 trial was launched in late July 2020 to assess the safety and efficacy of the mRNA-1273 vaccine in preventing SARS-CoV-2 infection. An independent data and ...
COVID-19 mRNA Vaccines: Lessons Learned from the ...
Our understanding of COVID-19 vaccinations and their impact on health and mortality has evolved substantially since the first vaccine rollouts. Published reports from the original randomized phase 3 trials concluded that the COVID-19 mRNA vaccines could greatly reduce COVID-19 symptoms. In the inter …
Coronavirus disease (COVID-19): Vaccine research and development
WHO and its partners are committed to accelerating the development of COVID-19 vaccines while maintaining the highest standards on safety. Vaccines go through various phases of development and testing - there are usually three phases to clinical trials, with the last one designed to assess the ability of the product to protect against disease ...
COVID vaccines and safety: what the research says
There is no question that the current vaccines are effective and safe. The risk of severe reaction to a COVID-19 jab, say researchers, is outweighed by the protection it offers against the deadly ...
To vaccinate or not to vaccinate? The interplay between pro- and
Our research questions can be summarized by trying to describe the relationship exploited by the directed acyclic graph in Fig. ... Understanding the behavioural and social drivers of vaccine uptake WHO position paper - May 2022 - Comprendre les facteurs comportementaux et sociaux de l'adoption des vaccins Note de synthèse de l'OMS ...
Impact of Vaccines; Health, Economic and Social Perspectives
A vaccination program started in the United Kingdom in 2008, and at the time of writing over 10.5 million doses had been given to girls (Public Health England, 2018), with the aim of preventing primary infection with HPV. The vaccine coverage was 83.8% for 13-14 year old girls in England in 2017/18 (Public Health England, 2019).
Rapid qualitative research to increase COVID-19 vaccination uptake: a
Abstract. This qualitative tool provides step by step guidance on how to design and conduct rapid qualitative research with different target groups to understand their barriers and drivers to COVID-19 vaccination. These insights can then be used to inform the development of interventions tailored to the target groups for successful COVID-19 ...
COVID‐19 vaccine research and development: ethical issues
The achievements of vaccine research and development bring a hope to our societies that we may cope with the COVID‐19 pandemic. There are two aspects that should be maintained in balance: the immediate necessity for speed of vaccine research and the inherent need for protection of research subjects, which is the foremost concern of research ethics.
11 Questions to Ask About COVID-19 Research
When hundreds of millions of people are vaccinated, millions of them will be afflicted anyway, in the course of life, by conditions like strokes, anaphylaxis, and Bell's palsy. "We have to have faith that people collecting the data will let us know if we are seeing those things above the baseline rate.". 3.
Impact of Routine Childhood Immunization in Reducing Vaccine
Childhood vaccination has dramatically reduced morbidity, mortality, and disability caused by vaccine-preventable diseases, with ∼21 million hospitalizations, 732 000 deaths, and 322 million cases of disease averted in the United States between 1994 and 2013. 1 Among diseases targeted by vaccines recommended before 1980, 3—polio, measles, and rubella—have achieved elimination status as ...
PDF Critical EVIDENCE Questions FOR COVID-19 VACCINES POLICY MAKING
The objective AND METHODS. of this list of critical evidence questions is to. enable SAGE to issue evidence-informed policy on the accelerated use of COVID-19 vaccines. The questions are grouped by criteria that SAGE takes into consideration in the context of vaccine policymaking and which are outlined in its Evidence-to-Recommendation framework1:
COVID-19 vaccines and adverse events of special interest: A
1.Introduction. Since declaration of the COVID-19 pandemic by the World Health Organization (WHO) on March 11, 2020 [1] more than 13.5 billion doses of COVID-19 vaccines have been administered worldwide [2].As of November 2023, at least 70.5 % of the world's population had received at least one dose of a COVID-19 vaccine [2].This unparalleled scenario underscores the pressing need for ...
PDF Survey Question Wording and Topline
2021 PEW RESEARCH CENTER'S AMERICAN TRENDS PANEL . WAVE 83 February 2021 . SCIENCE TOPLINE . February 16-21, 2021 . TOTAL N=10,121 . ... 3 Prior to Feb 16-21, 2021, the question wording was, "If a vaccine to prevent COVID-19 were available today, would you…" Very concerned Somewhat concerned Not too concerned Not at all
Vaccine Safety Research and Safety Studies
As science advances and new information becomes available, this system will continue to improve. Vaccine safety research: Ensures the benefits of vaccines approved in the U.S. outweigh the risks. Defines which groups should not receive certain vaccines. Describes side effects and adverse events reported after vaccination.
Top 20 Questions about Vaccination
Detailed answers to the most frequently asked questions about vaccination. ... Research continues on the persistence of immunity generated by vaccines. ... This possibility was publicized after a 1998 paper by a British physician who claimed to have evidence that the MMR (measles, mumps and rubella) vaccine was linked to autism. ...
Meta-summaries effective for improving awareness and ...
To meet this need and communicate much-needed vaccine information, this paper reports on online, interactive meta-summaries of COVID-19 vaccine safety research aimed at increasing public awareness ...
Are presidents good role models for vaccination uptake? DRC study shows
Nik Stoop acknowledges financial support from Research Foundation Flanders through a post-doctoral scholarship (nr.: 12W8320N). Elie Lunanga receives funding from University of Antwerp's Research ...
Vaccine Information and Safety Studies
The Vaccine Safety Datalink (VSD) is a collaboration between CDC and 13 health care organizations that conducts active vaccine safety monitoring and research. V-safe is a safety monitoring system that vaccine recipients can use to share with CDC how they feel after vaccination. The Clinical Immunization Safety Assessment (CISA) Project is a ...
Coronavirus Pandemic (COVID-19)
Download our complete dataset of COVID-19 metrics on GitHub. It's open access and free for anyone to use. Explore our global dataset on COVID-19 vaccinations. See state-by-state data on vaccinations in the United States. Explore the data on confirmed COVID-19 cases for all countries. Explore the data on confirmed COVID-19 deaths for all ...
Get the facts about COVID-19 vaccines
These vaccines have U.S. Food and Drug Administration (FDA) emergency use authorization or approval. 2023-2024 Pfizer-BioNTech COVID-19 vaccine.. In December 2020, the Pfizer-BioNTech COVID-19 vaccine two-dose series was found to be both safe and effective in preventing COVID-19 infection in people age 18 and older.
Vaccines
Division of Communication and Consumer Affairs Office of Communication, Outreach and Development Center for Biologics Evaluation and Research Food and Drug Administration 10903 New Hampshire Ave ...
Simply put: Vaccination saves lives
A recent economic analysis of 10 vaccines for 94 low- and middle-income countries estimated that an investment of $34 billion for the immunization programs resulted in savings of $586 billion in reducing costs of illness and $1.53 trillion when broader economic benefits were included ( 5 ). The only human disease ever eradicated, smallpox, was ...
Understanding How COVID-19 Vaccines Work
How COVID-19 Vaccines Work. COVID-19 vaccines help our bodies develop immunity to the virus that causes COVID-19 without us having to get the illness. Different types of vaccines work in different ways to offer protection. But with all types of vaccines, the body is left with a supply of "memory" T-lymphocytes as well as B-lymphocytes that ...
PLOS Pathogens
Broad-spectrum Delta-BA.2 tandem-fused heterodimer mRNA vaccine delivered by lipopolyplex. This vaccine has demonstrated its ability to induce broad-spectrum immunogenicity in mice and offers protection to both mice and monkeys when exposed to live SARS-CoV-2 challenges. Image credit: ppat.1012116. 02/28/2024.

Save citation to file

Add to My Bibliography

COVID-19 mRNA Vaccines: Lessons Learned from the Registrational Trials and Global Vaccination Campaign

Retraction in

Conflict of interest statement

Similar articles

Publication types

Related information

Miscellaneous

To vaccinate or not to vaccinate? The interplay between pro- and against- vaccination reasons

Conclusions

Introduction

Participants

Scoring of reasons

Statistical analysis

COVID-19 Perceived risk—exploratory factor analysis

Propensity score weighting

Regression models

Classification tree analysis

Availability of data and materials

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Consent for publication

Additional information

Supplementary Information

Rights and permissions

About this article

Share this article

BMC Public Health

REVIEW article

Introduction

Brief History of Vaccine Development

Health Benefits of Vaccination

Eradication of Infectious Diseases

Herd Immunity

Reduction in Secondary Infections That Complicate Vaccine-Preventable Diseases

Prevention of Cancer

Preventing Antibiotic Resistance

Economic Benefits

Productivity Gains

Minimizing the Impact on Family

Cost-Effective Preparedness for Outbreaks

Establishing Programs for Vaccine Development

Social Benefits

Strengthening Health and Social Care Infrastructure

Impact of Life Expectancy and Opportunity

Empowerment of Women

Author Contributions

Conflict of Interest

Related Links

View Statistics

11 Questions to Ask About COVID-19 Research

1. Did the study appear in a peer-reviewed journal?

2. Who conducted the study, and where did it appear?

3. Who was studied, and where?

4. How big was the sample?

5. Did the researchers control for key differences, and do those differences apply to you?

The Science of Happiness

6. Was there a control group?

7. Did the researchers establish causality, correlation, dependence, or some other kind of relationship?

8. Are journalists and politicians, or even scientists, overstating the result?

9. Is there any conflict of interest suggested by the funding or the researchers’ affiliations?

10. Do the authors reference preceding findings and original sources?

Greater Good’s Guide to Well-Being During Coronavirus

11. Do researchers, journalists, and politicians acknowledge limitations and entertain alternative explanations?

About the Authors

Jeremy Adam Smith

Emiliana R. Simon-Thomas

You May Also Enjoy

Why Is COVID-19 Killing So Many Black Americans?

How Does COVID-19 Affect Trust in Government?

Why Your Sacrifices Matter During the Pandemic

How to Form a Pandemic Pod

In a Pandemic, Elbow Touches Might Keep Us Going

How to Keep the Greater Good in Mind During the Coronavirus Outbreak

Prevaccine and Vaccine-Era Disease Estimates

Supplementary data