literature review of the economics of covid 19

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A literature review of the economics of COVID-19

Affiliation.

1 Department of Economics University of Ottawa Ottawa Ontario Canada.
PMID: 34230772
PMCID: PMC8250825
DOI: 10.1111/joes.12423

The goal of this piece is to survey the developing and rapidly growing literature on the economic consequences of COVID-19 and the governmental responses, and to synthetize the insights emerging from a very large number of studies. This survey: (i) provides an overview of the data sets and the techniques employed to measure social distancing and COVID-19 cases and deaths; (ii) reviews the literature on the determinants of compliance with and the effectiveness of social distancing; (iii) mentions the macroeconomic and financial impacts including the modelling of plausible mechanisms; (iv) summarizes the literature on the socioeconomic consequences of COVID-19, focusing on those aspects related to labor, health, gender, discrimination, and the environment; and (v) summarizes the literature on public policy responses.

Keywords: COVID‐19; coronavirus; economic impact; lockdowns; social impact.

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Publications
IZA Discussion Papers
A Literature Review of the Economics of COVID-19

IZA DP No. 13411: A Literature Review of the Economics of COVID-19

published in: Journal of Economic Surveys, 2021, 35(4), 1007-1044

The goal of this piece is to survey the emerging and rapidly growing literature on the economic consequences of COVID-19 and government response, and to synthetize the insights emerging from a very large number of studies. This survey (i) provides an overview of the data sets used to measure social distancing and COVID-19 cases and deaths; (ii) reviews the literature on the determinants of compliance and effectiveness of social distancing; (iii) summarizes the literature on the socio-economic consequences of COVID-19 and government interventions, focusing on labor, health, gender, discrimination and environmental aspects; and (iv) discusses policy proposals.

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The economics of the COVID-19 pandemic: economic evaluation of government mitigation and suppression policies, health system innovations, and models of care

Review Article
Published: 24 May 2023
Volume 32 , pages 1717–1732, ( 2024 )

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literature review of the economics of covid 19

Kathryn Margaret Antioch ORCID: orcid.org/0000-0003-2925-0380 1 , 2 , 3

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The COVID-19 pandemic has impacted the scope of health economics literature, which will increasingly examine value beyond health care interventions such as government policy and broad health system innovations.

The study analyzes economic evaluations and methodologies evaluating government policies suppressing or mitigating transmission and reducing COVID-19, broad health system innovations, and models of care. This can facilitate future economic evaluations and assist government and public health policy decisions during pandemics.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was used. Methodological quality was quantified using the scoring criteria in European Journal of Health Economics, Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Checklist and the National Institute for Health and Care Excellence’s (NICE) Cost Benefit Analysis Checklist. PUBMED, Medline, and Google Scholar were searched from 2020–2021.

Cost utility analysis (CUA) and cost benefit analysis (CBA) analyzing mortality, morbidity, quality adjusted life year (QALY) gained, national income loss, and value of production effectively evaluate government policies suppressing or mitigating COVID-19 transmission, disease, and impacting national income loss. The WHO’s pandemic economic framework facilitates economic evaluations of social and movement restrictions. Social return on investment (SROI) links benefits to health and broader social improvements. Multi-criteria decision analysis (MCDA) can facilitate vaccine prioritization, equitable health access, and technology evaluation. Social welfare function (SWF) can account for social inequalities and population-wide policy impact. It is a generalization of CBA, and operationally, it is equal to an equity-weighted CBA. It can provide governments with a guideline for achieving the optimal distribution of income, which is vital during pandemics. Economic evaluations of broad health system innovations and care models addressing COVID-19 effectively use cost effectiveness analysis (CEA) that utilize decision trees and Monte Carlo models, and CUAs that effectively utilize decision trees and Markov models, respectively.

These methodologies are very instructive for governments, in addition to their current use of CBA and the value of a statistical life analytical tool. CUA and CBA effectively evaluate government policies suppressing or mitigating COVID-19 transmission, disease, and impacts on national income loss. CEA and CUA effectively evaluate broad health system innovations and care models addressing COVID-19. The WHO’s framework, SROI, MCDA, and SWF can also facilitate government decision-making during pandemics.

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Introduction

Covid-19 and economic studies: a new era calling for a societal approach.

The COVID-19 pandemic has impacted on the scope of health economics literature, which will increasingly examine value beyond health care interventions such as government policies (Mullins and Drummond 2020 ). The aim is to analyze economic evaluations and methodologies assessing COVID-19 government policies suppressing or mitigating transmission, reducing disease, and impacting national income loss; health system innovations and models of care. This can facilitate future economic evaluations and assist government and public health policy decisions during pandemics.

The global situation during a pandemic requires new economic evaluation methods in healthcare beyond traditional approaches to CBA and CEA. There are large economic impacts of social distancing, declining stock markets, increasing government spending, and unemployment. Some governments use CBA, monetizing reduced death risks, extending lifetimes, and comparing costs to benefits to determine whether prevention costs outweigh health benefits.

Greenstone and Nigam ( 2020 ) and Thunstrom et al. ( 2020 ) found mortality benefits from social distancing are between $8tn and $12tn, or $60,000 to $95,000 per household in the USA. Costs are high but benefits are greater. Thunstrom et al. ( 2020 ) calculated $5tn net benefits when including costs to GDP from social distancing. These studies assume society should pay $10m to save a person’s life, viz the value of statistical life (VSL). The USA Department of Transport and Environmental Protection Agency analyses are consistent with these findings (Freeman and Groom 2020 ). Greenstone and Nigam’s ( 2020 ) age adjusted data calculated $16.1m to save a 20–29-year-old and $1.5m for those aged 80 and over.

In CEA there is a preference to estimate value based on QALYs rather than a VSL. NICE pays £20,000–£30,000 for drugs to facilitate good health for one extra year. USA’s Institute for Clinical and Economic Review QALY is higher at $50,000–$150,000. In the UK a 70-year-old has 15 years life expectancy. Using cost/QALY of £25,000, this amounts to £375,000 for their future life. This is an over-estimate for those likely to die from COVID-19. However, it is lower than $3.7m Greenstone and Nigam ( 2020 ) assign to a life of an individual aged 70–79. Given £25,000/QALY and mortality estimates, UK households WTP is £6750 each to prevent 600,000 COVID deaths; £185bn in total or £330,000 per life saved. Social costs of distancing such as domestic violence and mental health should be included (Freeman and Groom 2020 ).

Society’s position on whether health benefits of COVID-19 interventions outweigh costs can depend on whether cost/QALY or VSL is used. The implications of economic evaluations depend on how society values change in risk of death or length and quality of lives extended. Trade-offs can be explicit in CBA, quantifying them using values implied by societal decisions. However, Freeman and Groom ( 2020 ) argue neither method, VSL or QALY, is applicable. VSL uses stated WTP to avoid a small increase in risk of death. Lower estimates of cost/QALY reflects health effects of relatively small changes in NHS expenditure, rather than what society “ought” to pay to improve health status (Freeman and Groom 2020 ). There is a paucity of economic evaluations addressing the mitigation of pandemics at the national and societal level, along with equity in decision making. This paper investigates these issues.

The pandemic raises difficult ethical choices for governments such as lockdowns and vaccine prioritization. To what extent and time period should costly lockdowns be used to enable good population health? Who should be prioritized in the allocation of vaccines, ventilators, or intensive care unit beds? Should vaccine doses be equitably shared globally, or should countries prioritize the health and economic well-being of their citizens? Equity in decision making can be addressed by social welfare function (SWF) analyses. SWF is attractive given it accounts for societal inequalities and population-wide policy impact. Policy choices involve health and income trade-offs, with consequences frequently heterogeneously distributed across populations. Older adults are at highest risk of severe COVID-19. The working-age encounter the burden of economic lockdowns, with excessive impacts on low socioeconomic-status individuals given they may not work at home (Ferranna et al. 2021a ).

The following sections commence with a systematic review of full economic evaluations of pandemic interventions. They address COVID-19 government policies suppressing or mitigating transmission, reducing disease, and impacting national income loss, health system innovations and models of care. The government policies concern restrictions such as social distancing, stay at home orders, and institutional closures as lockdowns. Health system innovations involve COVID-19 workforce prevention, sheltered homelessness interventions, staffing ICU bed reserve capacity in Europe, and epidemic control strategies such as testing, contact-tracing, isolation centers, screening, and quarantine centers. New models of care concern home maintenance allergen immunology versus clinics, hospitalized COVID-19 patients versus supportive care, standard COVID-19 care versus telemonitoring for heart failure patients, COVID-19 patients in public versus private-health systems, and COVID-19 testing for diagnosing and discharging patients.

Given the scope of health economics literature is expanding to evaluate value beyond healthcare interventions, such as other government policies, the research also analyses theoretical issues concerning welfare economics, SWF, social return on investment (SROI), WHO’s pandemic economic risk framework for social and movement measures, and MCDA.

The current research makes a significant contribution to the economic literature as there were no prior systematic or scoping reviews that addressed the breadth of research question being addressed in this study. A study by Dawoud and Soliman ( 2020 ) undertook a systematic review of the cost effectiveness of antiviral treatments for pandemics and outbreaks of respiratory illnesses, including COVID-19. A systematic review by Rees et al. ( 2020 ) analyzed COVID-19 length of hospital stay to project future system demands by various levels of care. A systematic review concerning the economic evaluation of programs against COVID-19 was undertaken by Rezapour et al. ( 2021 ). Their aim was different as it focused on COVID-19 treatments and programs rather than government policies and excluded more recent studies undertaken since July 2020. They reviewed studies from December 2019 to July 2020. The current study included studies from 2020 to 2021 and explored broader issues concerning health system changes, government policies aimed at suppressing or mitigating transmission, reducing disease, and national income loss. Importantly, it analyses important methodological issues.

Rasmussen et al. ( 2022 ) published a scoping review of economic evaluations against viral pandemics. It was different to the current study as it included a broader number of diseases such as Ebola, Zika, SARS, MERS, H1NI, and H5N1. It did not include the study results and their implications and did not assess the quality of the economic evaluations. Rather, the authors only included summary statistics on study perspective, costs, comparators, and economic models.

Further, the study by Rasmussen et al. ( 2022 ) did not explore economic methodological issues pertinent to public health decision making during a pandemic. Importantly, in addition to analyzing the full economic evaluations of pandemic interventions, the current study analyses methodological issues in economics impacting on pandemics including welfare economics, social return on investment, social welfare function, multi-criteria decision analysis, and the WHO pandemic social and movements decision-making and economics framework. The study thereby provides an important and unique contribution to the literature.

Methodology

Literature review framework and protocol registration.

The research aimed to analyze economic evaluations and methodologies assessing COVID-19 interventions and government policies to suppress or mitigate transmission, reduce disease, and impacting on national income loss; health system innovations and models of care. Hence, the study analyses economic studies and novel methodologies that can evaluate broader health system and societal impacts of pandemic interventions. A systematic scoping review of the literature is appropriate in circumstances where the study aim is to identify the types of evidence available in the field and any knowledge gaps (Peters et al. 2020a ; Munn et al. 2018 ; Peters et al. 2020b ). A systematic scoping review was undertaken using PRISMA-ScR including the review design, population, concept and context (PCC), protocol and PRISMA flow charts (Peters et al. 2020b ). The review was based on an a priori defined PRISMA-Scr protocol, which was registered by Open Science Framework (OSF). [ https://osf.io/4wzac/?view_only=a412c5177f624fcd94f06e76c583a31f ] The OSF registered PRISMA-Scr protocol is also in Appendix 1 . The completed PRISMA-Scr checklist is in Appendix 2 . Full economic evaluations were assessed for quality and methodological rigor using the CHEERS Checklist (Husereau et al. 2022 ) with the assessment scoring tool published in the “European Journal of Health Economics” by Antioch et al. ( 2002 ), and NICE’s ( 2012 ) cost benefit analysis checklist.

Search strategy and selection of studies

Searches were undertaken using PUBMED, Medline, PUBMED Central (PMC), and the National Centre for Biotechnology Information (NCBI) Bookshelf for April 2020 to June 2021. The search engine was PUBMED Advanced Search Builder, National Library of Medicine, USA. Search terms: (COVID-19[MeSH Terms]) AND (cost effectiveness[MeSH Terms]) April 2020 to April 2021, resulting in 109 references. The second search included terms (cost benefit analysis) AND (COVID-19) June 2020 to June 2021, resulted in 196 references. See Appendix 3 for details of PUBMED searches. The additional 25 studies were identified from other sources, including references from selected journal articles and Google Scholar. Once duplicates were removed, title and abstract reviews were conducted to assess eligibility. Full text reviews were also conducted, and full economic evaluations assessed for methodological quality. A PRISMA flow diagram summarizing the study selection process is shown in Fig. 1 , based on the PRISMA 2020 statement: an updated guideline for reporting systematic review (Page et al. 2021 )

PRISMA flow chart for reporting the systematic scoping review of economic evaluations of pandemic interventions. Source: based on framework in Page et al. ( 2021 ) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ;372:(71). doi: 10.1136/bmj.n71

Eligibility criteria

All records identified were assessed for inclusion against the following participants, concept and context (PCC) criteria. The results of quality assessments of the economic evaluation methodology were also used for full economic evaluations.

Participants

Populations impacted by the COVID-19 pandemic, including those in health services, the health care system, and society at large. Populations and patients with COVID-19 infection and those causing outbreaks.

(a) Full economic evaluations: CEA, where results were expressed in monetary units per case averted or life year saved; CUA, where results were expressed in monetary units per QALY or DALYs; CBA or CMA, where results were expressed as an intervention’s total saving or loss in monetary units. Primary research was preferred.

(b) Peer-reviewed review articles and books concerning broad methodological issues addressing pandemic impacts such as welfare economics and MCDA. All published 2020 and 2021.

All contexts including all countries of origin. The context should relate to COVID-19 evaluations and methodologies concerning government policies suppressing or mitigating transmission, reducing disease, impacting national income loss, health system innovations, and models of care.

Exclusion criteria

Cost of illness studies, studies not adopting a comparator for full economic evaluations, conference abstracts, newspaper articles, and dissertations. Studies not reported in English were also excluded.

Assessing quality of studies

The methodology to grade full economic evaluations, discussed in Antioch et al. ( 2017 ), was used to assess the quality of the full economic evaluations. This included the Consolidated Health Economics Evaluation Reporting Standards (CHEERS) checklist, updated in 2022 (Husereau et al. 2022 ) in conjunction with Drummond’s 10-point checklist (Drummond et al. 2005 ; Drummond et al. 1997 ) which is included and scored in Antioch et al.’s ( 2002 ) assessment tool published in the “European Journal of Health Economics.” Cost benefit analysis studies were also assessed using the foregoing checklists and NICE ( 2012 ) Cost Benefit Analysis Checklist. A total score achievable for each study was 6 for costs and 10 for consequences, for a total composite score of 16 (Antioch et al. 2002 ). Studies graded as strong on cost effectiveness methodology and achieving a composite score of at least 10 out of 16, were selected for the study. The scoring system by Antioch et al. ( 2002 ), which uses Drummond et al.’s ( 2005 , 1997 ) checklist has also been utilized extensively in other studies grading the methodological rigor of health economic evaluations.

Overall 330 records were identified, of which 40 studies met the inclusion criteria. Fifteen (37%) were full economic evaluations and were mainly model based. They achieved scores higher than 10 and were selected for the systematic review. Of these, six (40%) were CUA, six (40%) were CEA, one (7%) was a CMA, and two (13%) were CBA. Six CEAs evaluated health-system innovations using decision tree, Monte Carlo, and other stochastic-models. They concerned COVID-19 workforce-prevention, sheltered homelessness interventions, staffing ICU bed-reserve capacity, epidemic control strategies: testing, contact tracing, isolation centers, screening, quarantine-centers. Five CUAs evaluated new models of care using decision tree and Markov. They evaluated home-maintenance allergen immunology versus clinics, hospitalized COVID-19 patients versus supportive-care, standard COVID-19 care versus telemonitoring for heart-failure patients, COVID-19 patients in public versus private-health systems, COVID-19 testing for diagnosing and discharging patients. Two CBA and a CUA analyzed government policies concerning restrictions, mitigation, and suppression such as social distancing, stay at home orders, institutional closures such as lockdowns. Strategies were generally found to be either cost-saving or cost effective at the study specific willingness to pay thresholds. The remaining 25 (63%) studies addressed welfare economics, social return on investment, social welfare function, multi-criteria decision analysis, and the WHO pandemic economic risk framework. Table 1 presents the characteristics of included full economic evaluation studies on COVID-19, providing overview statistics on the origin (continent) of each study, economic evaluation study type, study design model for estimation, and the study perspective. It includes a frequency count and percentage distribution. Appendix 4 includes the completed data chart of included full economic evaluation studies, providing valuable details of all results. This includes author, year, continent of origin, types of economic evaluation, type of model for estimation, types of interventions and comparators, primary outcome, study perspective, economic evaluation results reported in the relevant currency and economic evaluation ratios, and methodological quality assessment scores. All included studies had high methodological quality scoring 15 (or 94%) or higher. The implications of the most relevant studies relating to government policies on pandemic restrictions, such as mitigation, suppression, health system innovation, and models of care are discussed in the next section. A consolidated overview of all other results from Appendix 4 are also discussed. Methodological studies concerning welfare economics, social return on investment, social welfare function, MCDA, and WHO pandemic decision and economics framework are also analyzed.

Full economic evaluation studies

The results from all the full economic evaluations are included in the table in Appendix 4 . Studies concerning assessments of the value of COVID-19 interventions involving health system innovations and government policies aimed at suppressing or mitigating transmission, reducing disease, and minimizing national income loss are discussed below. The other full economic evaluation studies in Appendix 4 concerning health system innovations and new models of care are also discussed. Methodological issues concerning welfare economics, social return of investment, social welfare function, multi-criteria decision analysis (MCDA) and the WHO pandemic decision and economics framework are also analyzed below.

We turn to three important full economic evaluations concerning government policy to suppress or mitigate transmission, reduce COVID-19 disease, with impacts on national income loss. A promising CBA methodology was undertaken by Broughel and Kotrous ( 2021 ) who estimated the benefits and costs of state suppression policies to “bend the curve” during the initial outbreak of COVID-19 in 50 USA States. U.S. states enforced non-pharmaceutical interventions (NPIs) to suppress COVID-19 transmission by closing nonessential businesses and enforcing stay-at-home orders for all residents. Almost 90% of the population was required to stay at home unless engaged in “essential” activities. They valued benefits and costs in terms of additions or subtractions to total production, using the value of production (VOP) approach. Costs included losses to output associated with the enforcement of nonessential business closure and stay-at-home orders. Indirect costs occurred from increased mortality risks via suicide related to lost income. The benefits valued prevented COVID-19 deaths in terms of total production gained by lengthening lives. Cost-savings of preventing COVID-19 illnesses and health-care utilization were also estimated.

Relative to a baseline where only infected and at-risk populations mitigate the COVID-19 spread, total benefits of suppression policies to economic output ranged from $632.5b to $765.0b from March to August 2020. Relative to private mitigation, output lost due to suppression policies was between $214.2b to $331.5b. Cost estimates were based on length of non-essential business closures and stay-at-home orders, enforced for between 42 and 65 days. Net benefits of suppression were between $301b and $550.8b. The most significant factor was reduced mortality.

Given there is controversy concerning methodologies to valuing benefits of life-saving public health interventions during the pandemic, they also presented mortality benefit estimates using VSL and QALYs saved. Net mortality benefits were between $10.6t and $11.9t using VSL of $11.3m. Gross mortality benefits using QALYs, based on the $50,000 threshold, were between $285b and $530b. Their estimate using the VoP approach falls within this interval suggesting similarities between the QALY and VoP approach (Broughel and Kotrous 2021 ). The study achieved a methodological rigor score of 15 (or 94%) representing high methodological rigor.

Their finding of positive net benefits is consistent with other CBAs of social distancing during the pandemic. However, their net benefit estimates are smaller (see Broughel and Kotrous 2021 for a review). The difference in their findings is attributable to two issues. First, they estimated the costs and benefits associated with the policy response to COVID-19. They did not estimate the costs and benefits associated with social distancing more generally, which includes public and private actions that reduce economic and health impacts of COVID-19. Second, their analysis focuses on the costs and benefits of COVID-19 suppression with regard to its effects on economic output and production (Broughel and Kotrous 2021 ). Their VOP approach to valuing mortality benefits enables more direct comparisons of mortality benefits to other relevant benefits and costs. Healthcare utilization is most easily measured by observed service cost. Similarly, costs associated with policy interventions, such as losses to GDP, are comparable to these production benefits. Their focus on production is similar to other CBAs in the literature, such as evaluations of COVID-19 screening tests (see Broughel and Kotrous 2021 for a review).

Their unique contribution is accounting for potential increases in mortality risks, owing to economic costs associated with income losses stemming from public policies. They found that suppression policies are, on net, cost-saving.

The policies prevented additional deaths through this income-saving channel, in addition to preventing COVID-19 deaths more directly. While the indirect mortality benefits are small relative to benefits overall, it is important to calculate such ancillary mortality risks given concerns about suppression policy impacts on depression that could outweigh the health consequences of COVID-19. Conversely, they found suppression policies had minimal short-run effects on overall mortality through such indirect mechanisms. While economic dislocation is not the only factor impacting mental health during suppression policies, their findings are in accord with a study that found the number of suicides in several US states and high-income countries during the summer and fall months of 2020 did not diverge significantly from pre-COVID-19 trends (Broughel and Kotrous 2021 ). Their analysis has some limitations. There is uncertainty regarding the number of COVID-19 deaths that would have occurred in the counterfactual scenario in which suppression policies were not enforced. Their choice of counterfactual is the forecast of COVID-19’s progression in USA by Ferguson and colleagues, published in March 2020 and based on early evidence about disease transmission and mortality (Broughel and Kotrous 2021 ).

Miles et al. ( 2021 ) compared the UK population “lockdown” response and outcomes with European countries of comparable income and healthcare resources using a CBA involving macro costing using QALY. They measured estimates of the economic costs as different percentage losses in GDP against possible benefits of avoiding life years lost, for different scenarios where current COVID-19 mortality and comorbidity rates were used to calculate the loss in life expectancy. Adjustments were made for their levels of poor health and quality of life. They then applied a QALY value of £30,000, which is the maximum under NICE national guidelines. The costs of continuing severe restrictions were so high relative to likely benefits in lives saved that an expeditious easing in restrictions was justified. The smallest estimate for lockdown costs incurred was 40% higher than highest benefits from avoiding the worst mortality case scenario at full life expectancy tariff. In more realistic estimations, the lockdown costs were over five times higher. Future scenarios showed in the best case, a QALY value of £220k, which is seven times (x7) the NICE guideline. In the worst-case, £3.7m, which is 125 times the NICE guideline, was required to justify lockdown continuation (Miles et al. 2021 ). The study achieved a methodological rigor score of 16 representing very high methodological rigor.

The economic evaluation methodology used by Zala et al. ( 2020 ) was a CUA using a patient simulation model with attached costs. They calculated the relative cost-effectiveness of hypothetical suppression policies in the Imperial College COVID-19 Response Team model in the UK. Population level disease projections in deaths, ICU bed days, and non–ICU bed days were analyzed. National income loss estimates were derived from a study on the impact of a hypothetical pandemic on the UK economy, with sensitivity analyses based on more recent projections. Individual QALY loss and costed resource use inputs were analyzed. They compared two hypothetical suppression strategies to a mitigation policy and an unmitigated pandemic. An unmitigated pandemic assumed no government control measures. The mitigation aim was to decrease the pandemic impact by flattening the curve to reduce peak ICU demand and overall deaths, assuming (1) individual case isolation, (2) home quarantine (household with a suspected case), and (3) social distancing advice for individuals aged over 70.

There were two suppression strategies. Suppression involves more extensive controls, viz general social distancing, school, and university closures: (1) Suppression 1 , triggered “on” at 100 ICU cases in a week and “off” when weekly cases halve to 50 cases; (2) Suppression 2, triggered “on” at 400 ICU cases in a week and “off” when weekly cases halve to 200 cases. Results for base case settings (R = 2.4) included the following findings. Suppression 1 versus unmitigated resulted in £19,653 per additional QALY. Suppression 1 versus mitigation resulted in £33,346 per additional QALY. Suppression 2 versus unmitigated £20,977 per additional QALY. Suppression 2 versus mitigated £38,314 per additional QALY.

Assuming a maximum reduction in national income of 7.75%, incremental cost effectiveness ratios (ICERs) for Imperial model versus mitigation are below £60 000 per QALY. However, results are uncertain and conditional on the accuracy of the Imperial model projections. They are also sensitive to estimates of national income loss. Nevertheless, it would be arduous to claim that these suppression policies are cost-ineffective relative to the alternatives available. The article provides some early insight into the trade-offs that are involved (Zala et al. 2020 ). The study achieved a methodological rigor score of 16 representing high methodological rigor.

The remaining 12 full economic evaluation studies that used CEA, CMA, or CUA addressed health system innovations and new models of care. All 12 studies achieved high methodological rigor scores of at least 15 (or 94%). The CEAs and a CMA evaluated COVID-19 health system innovations . CEAs using decision tree and simulation models evaluated new forms of sheltered homelessness interventions to reduce disease spread (Baggett et al. 2020 ), universal COVID-19 screening versus personal protective equipment (PPE) for obstetric health workers (Savitsky and Albright 2020 ), and staffing ICU bed reserve capacity in Europe (Gandjour 2021 ). CEAs using Monte Carlo simulation models evaluated health system epidemic control strategies involving testing, contact tracing, isolation centers, screening, and quarantine centers (Reddy et al. 2021 ) and evaluations of health system PPE for health workers in low- and middle-income countries (Risko et al. 2020 ). A CEA using stochastic analyses evaluated COVID-19 testing strategies combined with isolation periods (Du et al. 2021 ). A CMA evaluated the UK National Health Services testing pathways for suspected COVID-19 patients using community versus standard hospital practices (Currie et al. 2020 ).

CUA using decision tree and simulation models such as Markov evaluated new models of care such as home maintenance allergen immunology versus in office clinics (Shaker et al. 2020 ), hospitalized COVID-19 patients versus best supportive care (Sheinson et al. 2021 ), standard COVID-19 care versus telemonitoring for older heart failure patients (Jiang et al. 2021 ) and management of COVID-19 patients in public versus private health systems (Cleary et al. 2021 ). CUA using patient simulation models (SEIR) with attached costs evaluated COVID-19 tests for diagnosing and discharging patients (Jiang et al. 2020 ). Appendix 4 includes valuable details of the results of all full economic evaluations.

An analysis of the foregoing studies raises important issues, especially those by Broughel and Kotrous ( 2021 ), Miles et al. ( 2021 ), and Zala et al. ( 2020 ) that evaluate government policies suppressing or mitigating transmission, reducing disease, and impacting national income loss. Key issues concern the economy-health tradeoff and the equity-efficiency tradeoff and the scope of economic evaluations. To what extent should economically costly lockdowns be imposed to ensure good population health? What are the health and income tradeoffs? How can policies account for societal inequalities and the distribution of policy impacts across the population? To what extent should economic evaluations include a broad array of socio-economic and environmental outcomes such as pollution reduction caused by lock downs when assessing social return on investment? Is there scope to capture health and non-health impacts underpinned by the “triple bottom line” viz social, economic, and environmental issues? What frameworks can assess the intended and unintended economic impact of social and movement measures during the pandemic?

While the intention is to limit virus spread and reduce deaths, unintended consequences involve disrupting access to health care and delays to diagnosis. It can exacerbate economic slowdown, socio-economic inequality, and harm workers unable to telework. How can we facilitate the systematic identification of new, emerging, or obsolete technologies impacting health and society during the pandemic? Are there frameworks to address these issues and facilitate stakeholder engagement in the process? Such methodological issues are explored below.

Methodological issues

Welfare economics

Governments face challenging trade-offs. Flattening the curve and saving lives requires major fiscal economy-wide support. The UK government has committed 20–40% of GDP. Total health, fiscal, and social costs are borne later. The societal perspective is important, with social wellbeing treated as a much broader public health issue. Welfare economics involves an ex-ante, proactive consideration of alternative policies. The economy-health trade-off and the equity–efficiency trade-off are central. Allocative efficiency which maximizes welfare, internalizing positive or negative externalities, is considered. Decision makers should move from a “medical problem” perspective to a much broader array of issues and stakeholders (Chilton et al. 2020 ).

Resource allocation is important and economic evaluation during a pandemic can involve calculating intervention benefits and costs, and the aggregate outcome of many marginal stakeholders’ decisions and trade-offs. Society can choose the best response, identifying social and health related opportunity costs, such as social isolation, inequalities, surgeries cancelled, and treatments displaced. Current scenarios can be costed into future projects, along with the benefits of factors such as additional ventilators, nurses, ICU beds, schoolteachers, and local services. Economic evaluation enables analyses of opportunity cost and health outcomes of alternatives such as contact-tracing, testing, regional versus national approach, random sampling, antigen, and antibody tests (Chilton et al. 2020 )

During COVID-19 “excess” deaths in the UK, including the effects across age cohorts, can be calculated. The impact on life expectancy and quality of life data can be analyzed by decision makers. Willingness to pay (WTP) methods such as value of a prevented fatality (VPF), value of a statistical life year (VLY), and QALY can be used, including the negative externalities of pain and suffering. WTP assumes true preferences and values are used. However, the resulting increases in taxes and associated ethical issues should be considered even where the benefit/cost ratio is positive for a high cost intervention (Chilton et al. 2020 )]. The Regulatory Office of the Australian Department of Prime Minister and Cabinet provides guidance on preparing cost-benefit analysis in Regulation Impact Statements. This includes how to treat the benefits of regulations designed to reduce the risk of physical harm. WTP estimates the value of reductions in the risk of physical harm known as the value of statistical life (VSL). The VSL is $5.0m and the value of statistical life year (VLY) is $217,000 in 2020 Australian dollars (Department of Prime Minister and Cabinet 2020 ). Some USA regulatory government agencies and American economic evaluations of the pandemic use $10m and $11.3m as VSL. This is more than double the value of the Australian VSL of $5m used by the Commonwealth Government for regulatory decisions.

Chilton et al. ( 2020 ) indicate that allocative efficiency analyses are important and smaller-scale decisions such as rationing ventilators or Do Not Attempt Resuscitation guidance to care homes could be established before an epidemic. Costs can be incurred now and benefits identified later, which are likely inter-generational. High discount rates for future consequences and the rationale for optimal responses should be considered.

An ex-ante, viz “before the event” approach can identify low up-front cost interventions with significant future benefits, such as life expectancy and lower inequalities. Alternatively, costly interventions with uncertain or low benefits can be articulated. Previous UK policy involved comparatively fewer ICU beds than Germany and austerity, implying a low present value (high discount rate) on the future of a potential pandemic. Would such a policy for future pandemics accurately reflect the country’s preferences? (Chilton et al. 2020 ).

The benefits and costs of future programs should be re-evaluated and include crucial areas such as public service, safety nets, population health, inequality, health services strength, and essential workers. Smaller, extra expenditure or redistribution in future, reflecting these priorities and benefits, may prevent higher costs of future crises (Chilton et al. 2020 ). Analysis of these economic issues during a global pandemic can be further assisted through Social Welfare Function, Social Return on Investment, the WHO’s decision and economics framework, and MCDA.

Social welfare function

The SWF approach can explicitly account for societal inequalities and the distribution of policy impacts across the population. It may therefore be more appealing than more traditional approaches. In the design of vaccine prioritization strategies, trade-offs can emerge between protecting the health of high-fatality-risk individuals, such as older adults and those with comorbidities, and the health of high-exposure-risk individuals undertaking essential societal activities or in economically critical sectors. Methodologies to adequately evaluate health-related interventions that can have differential socioeconomic and health consequences in the community are challenging (Ferranna et al. 2021a ).

Traditional evaluation methods, such as CEA and CBA, are restricted to some extent in dealing with the complexity of these issues. CEA has a health-centric approach focusing on benefits involving the changes in mortality and morbidity and healthcare cost savings. It does not permit differential socioeconomic benefits across different units of health. Where health is measured in QALYs, CEA assumes that each additional QALY has equal value regardless of the individual characteristics experiencing the QALY such as income level or age.

On the other hand, CBA analysis evaluates an intervention by converting its health and non-health benefits into monetary equivalents and summating them (Hammitt 2020 ; Greenstone and Nigam 2020 ). Unlike CEA, CBA can include differential socioeconomic benefits across different units of health through defining individual-specific WTP measures. However, WTP is dependent on ability to pay, and CBA analysis can therefore inflate benefits accruing to rich individuals relative to similar benefits attributable to poorer counterparts. Since CBA attributes the equivalent value to currency paid by the wealthy and those paid by the poor, an intervention’s value is independent of whether its cost burden falls on wealthy or poorer individuals. This is a consequence of CBA using an unweighted sum of monetary equivalents. An alternative approach to policy evaluation is social welfare function (SWF) analysis (Adler 2019 ). SWF measures an intervention’s health and non-health effects on individual well-being. It then aggregates individual well-being impacts to calculate an overall measure of the intervention’s value. The aggregation is calculated through a SWF, including concerns for the distribution of well-being across the population.

Like CBA, SWF analysis allows for differential socioeconomic benefits across different units of health. Unlike CBA, it does not necessarily inflate the value of health benefits accruing to wealthy individuals relative to the poor, given the criterion of evaluation is well-being and not currency. Further, it is sensitive to the population distribution of burdens and benefits (Adler et al. 2014 ).

SWF is a generalization of CBA. Operationally, it is equal to an equity-weighted CBA, where the configuration of the weights is based on the specific SWF (Ferranna et al. 2021b )

The choice of the COVID-19 intervention value framework is a significant issue (Ferranna et al. 2021a ). The issues of whether to impose a lockdown, its level of restrictiveness and duration is pertinent. A permissive lockdown policy can result in an uncontrolled pandemic with harms tending to be excessively endured by the worse off and poor. Contributing factors include working and living conditions, which put them at above average risk of infection. Some may also experience reduced access to quality health care when infected.

Lockdowns can impose costs, such as job and income losses, that can be disproportionately borne by the worse off. They have less savings and more limited re-employment potential, especially where social safety nets are lacking. This is important in developing countries with less ability to provide public income support.

The optimal lockdown stringency and duration is based on interacting empirical and normative issues. A first empirical likelihood is that the burdens to the worse off from an uncontrolled pandemic are higher than the burdens of a lockdown. In this scenario, interests of the worse-off will be served by a stringent lockdown policy. The second possibility is that the burdens to the worse-off from a lockdown are greater than the burdens from an uncontrolled pandemic. Here, the interests of the worse-off are better served by less stringent lockdowns.

The optimal policy for CBA occurs where the sum of individual WTP is highest. This WTP will reflect willingness to both avoid pandemic harms and avoid policy harms. However, CBA weighs every dollar of WTP equally, even across the rich and less wealthy with differential ability to pay. It therefore underweights the interests of the worse off, rendering it insensitive to the abovementioned considerations compared with an SWF approach. For the first empirical scenario, CBA will recommend a lockdown policy that is too permissive considering equity concerns. When the second empirical possibility holds, it will recommend a lockdown policy that is too stringent. Across the two empirical scenarios, the worse off do better under the SWF function approach compared to the CBA method (Ferranna et al. 2021a ).

Ferranna et al. ( 2021a , b ) discuss their studies of lockdowns whose burdens are disproportionately borne by the worse off. In America, CBA may support policies that eliminate infection spread even if they cause a 30% GDP loss. SWF analysis will assess these policies to be unacceptable if low-income groups pay a disproportionate amount of net costs. In this scenario, applying plausible levels of inequality aversion, SWF would recommend only policies that cost a maximum of 10–15% of GDP. The larger the decision makers’ aversion to inequality, the lower the support for strict lockdown policies when their costs are regressive.

Vaccine prioritization highlights important differences between traditional evaluation methods and SWF analysis. Modeling the best allocation of vaccines (e.g., Bubar et al. 2021 ) is often based on epidemiological outcomes such as deaths, years of life lost, or numbers of infections and possibly on the costs of delivering such outcomes.

However, they can neglect structural inequities, such as concentrating vaccinations in socially vulnerable areas, the economic benefits of alternative vaccination rules that consider linkages between vaccination and relaxing nonpharmaceutical interventions; and the impact of characteristics such as age. Contrastingly, SWF can include imperatives for social equity and socioeconomic impacts of alternative vaccine allocation strategies (Ferranna et al. 2021b ).

Assume the risk of severe COVID-19 outcomes increases with age and decreases with socioeconomic status. This may occur since rich individuals can more effectively protect themselves from infection risk and obtain more effective treatments. Older adults in low socioeconomic groups are the most exposed to risk of severe outcomes. Assume the vaccine enables very good protection but is less effective at reducing transmission. Where a policy goal is to decrease the number of severe cases, the vaccine would be administered initially to older adults in low socioeconomic groups. It would subsequently be administered to older adults in high socioeconomic groups. Where the policy goal is to maximize social welfare, older adults in low socioeconomic groups would still be prioritized given their high risk. However, if social equity is the imperative, younger adults in low socioeconomic groups would come next, rather than older wealthy adults given the former are in a less privileged position from a socioeconomic perspective and are younger and have not lived a full life yet (Adler et al. 2021 ), (Ferranna et al. 2021b ).

The SWF approach is more data intensive compared with more traditional methods, given it requires information on the distribution and correlation of the populations’ different attributes. It also requires data on the distributional effects of the policy on the attributes. Social welfare analysis takes a consequentialist perspective. It therefore does not fully capture other ethical issues, such as human rights, individual responsibility versus luck, or the restitution principle. Nevertheless, because SWF analyses the distribution of policy impacts across the population and the correlation with background inequalities, it is more attractive than CBA and CEA. It can also potentially include equity and justice issues in policy evaluation (Ferranna et al. 2021a ). Social return on investment is also important during a pandemic and is discussed below.

Social Return On Investment (SROI)

The objective of SROI is to assess if an intervention is worth the investment. Costs are analyzed in monetary value and benefits can be linked to health and broader social improvements. Compared to traditional health economic evaluation tools, SROI is an extension of CBA, including a broader array of socio-economic and environmental outcomes. It captures health and non-health impacts, underpinned by the “triple bottom line” viz social, economic, and environmental. There is broad stakeholder engagement in valuing outcomes, unlike more traditional approaches. SROI evaluates and places proxy values on personal, social, and community outcomes where necessary, capturing social impact at the societal level. It also values the potential negative effects (Banke-Thomas et al. 2015 ).

During a pandemic there is a need to capture social, economic, health, environmental costs and benefits given the nature of the impacts globally. The total health, fiscal, and social costs may be borne later. In this societal perspective, social wellbeing should be seen as a broader public health issue. It requires expanding the traditional scope of health economics beyond health care interventions to include government policies to suppress or mitigate transmission, suppress disease, and direct economic support addressing the consequences of policies involving prolonged lockdowns.

It can also capture environmental impacts such as reductions in CO 2 emissions and pollution which are environmental and health benefits of lockdowns that can be included in the analysis. It is reported as monetary value or welfare benefit. Financial proxies are used to estimate the monetary value of benefits not easily monetized. SROI is the ratio of discounted value of benefits (social value) divided by total investment. SROI > 1 is worthwhile. The SROI ratio 3:1 means $3 of social value created for $1 invested after discounts. The main output of analysis is an SROI ratio, net present value, and payback period. It can be used for priority setting, resource allocation, and stakeholder building. Its strengths involve use of a singular ratio which captures positive and negative outcomes with stakeholder engagement. The challenges involve difficulty attaching financial values to “soft outcomes” and the “counterfactual.” There is poor comparability of SROI ratios across interventions (Banke-Thomas et al. 2015 ).

During the pandemic, the environmental impact of lockdowns can be included. These led to a reduction in human activities, energy use, CO 2 emissions, and pollution impacting on health outcomes. There was an abrupt 8.8% decrease in global CO 2 emissions in 2020 compared to the same period in 2019. The timing of emission decreases corresponds to lockdown measures in each country. Substantial differences in emissions persist between countries, with continuing emission declines in USA (Liu et al. 2020 ),

Some relevant studies have analyzed SROI in health services, involving methodologies that analyze both health and social impact of policies, interventions, and services (Ashton et al. 2020 ), SROI from public health policies to support implementing the Sustainable Development Goals by building on Health 2020 (Dyakova et al. 2017 ), and the methodological challenges facing economists, health services planners, and policy experts (Edwards and Lawrence 2021 ; Hutchinson et al. ( 2019 ); Leck et al. 2016 ; Yates and Marra ( 2017 ); Gibson et al. ( 2011 ). SROI is relevant to pandemic scenarios.

WHO decision framework for social and movement measures and economics

The aim of public health and social measures during COVID-19 was to limit the virus spread and reduce deaths. Public health and social measures can be implemented together. It is difficult to measure their individual impact. The WHO’s decision framework for calibrating social and movement measures during the COVID-19 pandemic (WHO 2020) can assist in addressing societal impact and can be used for economic evaluation studies. It can be helpful when undertaking an analysis using CEA, CBA, SROI, and SWF.

There is evidence that social, physical distancing, and international travel-related measures which WHO calls social and movement measures can decrease face-to-face interactions/movement, reduce pressure on health services, and protect the most vulnerable. There can be unintended consequences if this disrupts access to care and delays diagnosis, treatment, and impacts on mental health and behavioral risk factors. The measures can also exacerbate economic slowdown, socio-economic inequality, harm workers unable to telework and those with precarious employment conditions and limited social protection (WHO 2020 ).

Complex decisions are required to sustain lives, livelihoods, and protect the vulnerable. A delay in calibrating social and movement measures during widespread transmission and risk of overwhelmed health services could increase morbidity and mortality, and the need to sustain stringent measures for longer.

Further, easing social and movement measures too quickly can jeopardize health and economic recovery. Strong, sustained policies mitigating harmful economic consequences of COVID-19 are necessary to support workers and businesses. Health, economic, and social welfare may be valued differently in different settings. It is challenging to collect context-specific evidence on multiple dimensions in a rapidly evolving situation. A five-step framework to support decision-making can assist in this process (WHO 2020 ). This framework includes the following steps which can facilitate comprehensive economic evaluations.

Assess the situational level and optimize health system response.

Identify possible social and movement measures for each context and possible calibration options and assess their health impacts.

Develop and populate an “Extended Assessment Matrix” of important health and non-health dimensions including implementation costs, economic cost, equity impact, and political barriers.

Establish a dialogue and a decision-making process.

Monitor, adapt, and communicate regularly throughout steps 1–4 (WHO 2020 ).

Step 3 above involves developing and populating an “extended assessment matrix” which involves WHO’s social and movement measures and their impact on health and non-health dimensions (WHO 2020 ). This framework can facilitate broad economic evaluation studies and could assist in conceptualizing the broad framework around analyses in CEA, CBA, SROI, and SWF. Such analyses can involve extensive collaboration with stakeholders, facilitated through steps 1 and 2, the extended assessment matrix in step 3, dialogue and decision making for steps 4, and communication for step 5. WHO ( 2020 ) indicates that the extended matrix in step 3 includes situation levels 3 and 4. For each situation level there are subclasses. Level 3 involves community transmission with limited capacity to respond and risk of overwhelming the health system . The subclasses are partial closure of businesses, school, e-learning, gathering size limitation, and no additional measures. A matrix analysis of health and non-health dimension for each sub-class can define the impact as low, medium, and high. The health dimensions impacts are COVID-19, non-COVID-19, and health system. The non-health dimension impacts are implementation cost, economic cost, equity impact, and political barriers. The same matrix framework is applied to level 4, involving uncontrolled pandemic requiring extensive measures to avoid overwhelming the health services . Subclasses include complete closure of businesses and institutions, prohibiting gatherings, and no additional measures. The abovementioned health and non-health dimensions are also applied to level 4 and with impact defined as low, medium, or high (WHO 2020 ).

Multi Criteria Decision Analysis (MCDA)

Mcda for horizon scanning of health innovations: hta during pandemics.

Horizon scanning involves the systematic identification of new, emerging, or obsolete technologies impacting health and society. Brief assessments can be undertaken using MCDA. This supports a full Health Technology Assessment (HTA) for innovative, potentially affordable technologies. Robust assessments and transparency principles without conflicts of interest are central. They can be used to rapidly identify technologies and interventions such as diagnostic, therapeutic, vaccines, and technology innovation. They assist in containing risks and ensuring high effectiveness, safety, ethics, with economical outcomes (Ruggeri et al. 2020 ).

MCDA can assist governments in decision making in supporting new models of care dependent on new technologies such as vaccines, medicines, diagnostic tools, and contact tracing systems. A tool for the early medical technology assessment using MCDA for horizon scanning was developed and used in Italy by the National Centres for HTA and Innovative Technologies. In the model, each HTA domain is attributed a score reflecting pros and cons along with opportunities and threats. Scores, which are weighted according to different perspectives, are plotted on a Cartesian graph, and positioned according to the potential value and perceived risk. Results are included in a table with a matrix of potential recommended outcomes such as that shown in Table 2 (Ruggeri et al 2020 ).

The approach can be demonstrated using a case study on the early assessment of a contact tracking system App. A brief assessment was undertaken using MCDA. A Panel involving medical, health, economics, statistician medical engineer and IT experts reported their views on the App, which were included on a matrix by scoring the balance between strengths and limits, and threats and opportunities. This included perceptions of effectiveness, safety, economic, legal, social, and ethics for each HTA domain. Scores on the Likert scale ranged from 1 (min added value or min risk) to 7 (max added value or max risk). Total score assigned to the value and risk was the sum of scores assigned to each domain of the HTA. Total scores were weighted using MCDA. There were three perspectives used, including health, decision-makers, and citizens/patients. The weights system was derived from the literature. The weights were varied using Monte Carlo simulation assuming 1000 scenarios for each perspective. Overall values and risk weights were included on a scatter plot graph. The ratio of risk/value was placed in one of four areas in the graph and Table 2 . The recommendation was for full HTA and was compliant with Core Model of European Network for Health Technology Assessment (EuNetHTA) (Ruggeri et al. 2020 ). The recommendation was a consequence of the positioning in the comfort zone for low risk and high value. This scenario is considered a “no negative scenario.”

During a pandemic, MCDA can facilitate vaccine prioritization, equitable health access (Roy and Kar 2022 ), and technology evaluation.

The present systematic review has some potential limitations. The results were limited to articles published in English, which represents a potential limitation. The model structures, sources of information, and time horizons in the full economic evaluations varied across studies, and consequently, it was difficult to generalize the results of a study to other settings. Most full economic evaluation studies were conducted in North America and the United Kingdom, contributing to 60% of the studies included. Only 13% of studies concerned Asia and another 13% related to Africa. Another 7% concerned 139 low-and middle-income countries. An additional 7% of studies were from Europe. Cost of illness studies, conference abstracts, newspaper articles, and dissertations were excluded, and some relevant information might be omitted as a result.

The studies using cost utility analysis and cost benefit analysis, and analyzing mortality, morbidity, QALY gained, national income loss, and value of production approaches have effectively evaluated government policies to mitigate or suppress COVID-19 transmission, disease, and national income loss. Stakeholder engagement and the quality and relevance of economic evaluations could be improved by using the WHO’s pandemic decision-making and economics framework, social return on investment methods, and multi-criteria decision analysis. The WHO’s model facilitates economic evaluations of social and movement restrictions. SROI links benefits to health and broader social improvements. MCDA facilitates vaccine-prioritization, equitable health-access, and technology evaluation.

Unlike CEA, CBA can incorporate differential socioeconomic benefits across different units of health through individual WTP measures. However, WTP depends on ability-to-pay and can inflate benefits accruing to rich relative to less wealthy counterparts. Social welfare function can account for social inequalities and population-wide policy impact. It is a generalization of CBA and operationally, it is equal to an equity-weighted CBA. Welfarist frameworks, evaluating social value of mortality-risk, such as value of a statistical life are often used by governments for regulatory decisions.

Economic evaluations of health system innovations and new models of care during the pandemic have involved high quality studies using CEA and CUA. Cost effectiveness analyses utilizing decision tree and Monte Carlo models have been used to evaluate health system innovations. Cost utility analyses have effectively utilized decision trees and Markov models to evaluate new models of care.

The entire range of foregoing methodologies are instructive for government decision-making internationally, in addition to their current use of value of a statistical life and CBA in regulatory decisions. Social welfare function is noteworthy as it can represent prospective patterns of collective choice as to alternative social states. It can provide governments with a guideline for achieving the optimal distribution of income, which is vital during pandemics.

Data availability

Not applicable.

Code availability

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Antioch, K.M. The economics of the COVID-19 pandemic: economic evaluation of government mitigation and suppression policies, health system innovations, and models of care. J Public Health (Berl.) 32 , 1717–1732 (2024). https://doi.org/10.1007/s10389-023-01919-z

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Oxford University Press - PMC COVID-19 Collection

The economics of the COVID-19 pandemic: an assessment

Daniel susskind.

2 Balliol College and Economics Department, Oxford

David Vines

2a Institute for New Economic Thinking, Oxford

The COVID-19 pandemic has created both a medical crisis and an economic crisis. As others have noted, we face challenges just as big as those in the Spanish Flu Pandemic and the Great Depression—all at once. The tasks facing policy-makers are extraordinary. Many new kinds of intervention are urgently required. This issue of the Oxford Review of Economic Policy has two objectives. The first is to explore these new interventions: evaluating their use, suggesting how they might be improved, and proposing alternatives. The second is to show that the challenges facing us are global and will require international cooperation if they are to be dealt with effectively. This short introductory essay positions the papers in the issue within an overall conceptual framework, with the aim of telling an overarching story about the pandemic.

I. Introduction

Just 6 months ago we all knew very little about any of this. Aspects of the story have emerged with greater clarity as more information has been revealed, and as the results of different policy experiments over the past few months have started to become clear. But the stakes are high and the time for decisions is greatly compressed.

II. The medical crisis and its economic effects

(i) the medical crisis.

Where to begin? Only 6 months ago few economists knew anything about SIR models. Now we all know that the central framework for studying the spread of any infectious disease is the SIR model. And we know that the only way to control a pandemic is to keep the reproduction number, R, the expected number of cases directly generated by an infectious case, below 1. When that happens, each infected person will infect less than one new person on average and the epidemic will come to an end ( Cleevely et al. , 2020 , this issue). But despite the central nature of the SIR model in the epidemiological literature, until recently most versions of that model did not adequately capture the economic costs associated with the interventions that are being made to control the disease.

There are now any number of papers available which begin to do this (see, for instance, Acemoglu et al. , 2020 and Eichenbaum et al. , 2020 ). Rowthorn and Maciejowski (2020 , this issue) make another welcome contribution to this set of ideas. At the core of these papers is the challenge of how to understand the trade-off between the cost of, on the one hand, the likely illness and deaths—however valued—and, on the other hand, the costs of the policies being adopted to reduce such illness and death. This trade-off is not simple to understand because it is an intertemporal one. Policies adopted now, with immediate costs, have implications for future infections and future deaths, and these implications work themselves out in highly non-linear ways. Clearly how one thinks about this depends on the value which one places on human life. The particular attraction of Rowthorn and Maciejowski (2020) ’s paper is that it provides a mapping from the value attached to human life to the severity of lockdown that is justified, after allowing clearly for the intertemporal nature of the problem. And it does this in an intuitively clear and elegant manner. (See Figure 8 of Rowthorn and Maciejowski (2020) .)

The paper argues that that the optimal response to COVID-19 would have been to lock down the economy very swiftly, to bring R down below 1, before the infection had taken hold; just one week of delay makes a huge difference. But when saying this we need to be clear how little was known at the beginning. Would it have been optimal to lock down so swiftly, knowing what we knew at the time and given the enormous uncertainty around the parameter estimates? This is difficult to judge, as experience of previous epidemics has shown. For instance, Neil Ferguson and his modelling team at Imperial College, who have played a critical role in influencing the UK’s response to COVID-19, were also responsible for shaping the decision to cull several million UK cattle to bring the 2001 foot-and-mouth disease outbreak to an end: but a more recent study, which found the disease had a shorter infectious period, suggested that such an aggressive approach may not always be optimal ( Cressey, 2011 ; Charleston et al. , 2011 ).

Lockdowns can only eliminate the transmission of disease if they remain in place more or less for ever, i.e. until a vaccine is available. That is because many people will go on being susceptible to infection 1 so that, if lockdown is abandoned, the unstable spread of the disease will again become likely. But because of the enormous economic cost associated with lockdowns, they cannot be allowed to continue more or less for ever. Rowthorn and Maciejowski (2020) argue that how long lockdown should be made to last depends fundamentally on the valuation attached to life: a lower value implies that a shorter lockdown is desirable. The study is based on a standard but simple epidemiological model, and should be regarded as presenting a methodological framework rather than giving actual policy prescriptions. They argue that a full lockdown of even as little as 10 weeks would only be optimal if the value of life for COVID-19 victims exceeded £10m ( Rowthorn and Maciejowski, 2020 , Figure 8). This number is much larger than the figure implied by official guidelines for drug evaluation, which is £200,000 to £300,000. 2 A robustness check, performed by changing the parameter values in the social welfare function used in the policy optimization algorithm, reduces this number to £4m. But that is still a larger number than the numbers used in the official guidelines. The paper also suggests that it would be optimal to dispense with lockdown altogether if the value of life were to drop below £1.68m (see Figure 8). 3

It is clear that this troubling trade-off between reducing the number of lives lost and rising economic costs raises significant questions about how exactly life should be valued. Colmer (2020 , this issue) discusses just how hard these questions are. He argues that efforts to engage with this issue have lacked clarity. He argues that the choice of numbers used to represent the ‘value of lives saved’ from COVID-19 interventions, more than likely, substantially understate the social benefits. In light of what are very large uncertainties over how much larger the social benefits could be, this raises concerns about how useful traditional benefit–cost analyses can be in contexts such as the current crisis.

If a full lockdown cannot continue indefinitely, it is obvious that alternative interventions will be required to keep R below 1. The ultimate goal must be to discover, manufacture, and distribute a vaccine so as to eliminate the threat of COVID-19 altogether. And as Brown and Susskind (2020 , this issue) argue, countries must cooperate much more actively than at present in their pursuit of this common objective. But before a vaccine or an effective treatment is available for widespread use, another strategy will be necessary to control the spread of the disease in the meantime.

In part, this strategy must involve bottom-up measures adopted by individuals: social distancing, decisions by the most vulnerable to shield themselves, wearing masks, and washing hands. But it must also involve additional top-down interventions imposed by governments. The two are closely related: it is becoming clear that the use of compulsory lockdowns—by the end of March 2020, over 100 countries had one in place—had an important signalling effect at the start of the pandemic, making clear how critical it was for individuals to change their behaviour. Indeed, these behaviour changes may explain why fears at the start of the pandemic about prolonged draconian intervention might have been misplaced ( Rowthorn and Maciejowski, 2020 ). Alongside a full lockdown, though, there are other important interventions available to governments.

To begin with, it is clear that targeted lockdowns, as per Acemoglu et al. (2020) , will need to become part of the strategy: rather than lock everyone down, the lockdown is instead stratified by, for instance, location, age group, or other risk factor. Another important intervention is an effective testing strategy: testing individuals for the infection and isolating those who test positive. However, such a strategy must also be workable: countries have finite testing resources and testing capacity can be difficult or impossible to ramp up ( Kasy and Teytelboym, 2020 , this issue). In Cleevely et al. (2020) , the authors question the viability of universal random testing, a strategy in which a random fraction of the entire population would be selected each day for testing. They show that, on reasonable assumptions, this would not be a feasible strategy; it would require testing about 27 per cent of the population every day (or everyone, every 4 days). Instead, the authors argue for stratified period testing: stratified because it is focused on at-risk groups, and periodic because tests would be conducted on each person at regular intervals. The authors show that this approach dramatically reduces the required testing resources. Following on from this, Kasy and Teytelboym (2020) examine the trade-offs involved in allocating testing resources to some individuals but not others; the so-called ‘shadow cost’ of a test. They explore the difficult dynamic balancing that policy-makers face, between using tests to protect people today, versus using tests to identify the prevalence of the disease in the population to benefit people in the future.

If the number of infections in a population is sufficiently low, or is brought down to a sufficiently low level, then a test-and-trace strategy can be used as an important part of a strategy. With such a policy, infectious individuals and their contacts are identified and isolated so they cannot infect others. The effect of such a policy will enable lockdown to be abandoned much earlier, even although the threat of unstable spread of the disease remains present. Such a policy becomes possible because an effective test-and-trace operation will quickly remove from public circulation anyone who is shown to be infectious. Such an individualized (and very costly) form of intervention enables R to be kept well below 1, even though, without it, and without lockdown, R still remains well above 1. The model in the paper by Rowthorn and Maciejowski (2020) illuminates this process very clearly.

It now appears from both theory and repeated experience that the two best investments a country could have made in the run-up to the COVID-19 pandemic are the production and distribution of ‘personal protective equipment’ (PPE), including face masks, and an effective test-and-trace regime. Looking ahead, there are important concerns about the consequences of existing safety regulations for such a regime: it appears that some businesses, for instance, are not testing their employees with sufficient frequency for fear of being shut down (this explains large but localized outbreaks at, for example, German abattoirs, at the time of writing). More of these outbreaks should be anticipated and can be dealt with, providing that businesses are encouraged to test and isolate their employees, rather than being encouraged not to do this by the threat of being punished ( Galeotti et al. , 2020 ).

(ii) The economic effects

What we have just said explains why the economic impact of COVID-19 has been so enormous. The deaths, and the reduction in the work which can be done by those who fall ill, are costly enough. But that is true of any infectious disease, like the flu. What is special about COVID-19 is that it is both very infectious and very deadly. That is why the policies adopted to deal with it—which we have been discussing—have needed to be so radical. At the start of the pandemic, del Rio-Chanona et al. (2020 , this issue) estimated that, in the US, the first-order effect of the virus would threaten 22 per cent of GDP, 24 per cent of employment, and reduce wage income by 17 per cent. These figures initially looked almost fantastical. But their predictions have turned out to be surprisingly close to the mark—not only in the US but around the world. But the details of how these costs have played themselves out have varied enormously from country to country. Evidence from Pakistan, for instance, suggests that microfinance in low-income communities now faces a drastic crisis ( Malik et al. , 2020 , this issue). Rapid-response surveys suggest that on average, week-on-week sales among microenterprise owners and household income both fell by about 90 per cent, households’ primary immediate concern in early April became how to secure food, and about 70 per cent of the sample of current microfinance borrowers reported that they could not repay their loans.

Significantly, the economic impact of COVID-19 has also been extremely unequal. Again, Rio-Chanona et al. (2020) correctly predicted that certain sectors would be hit by demand shocks (transport, for instance), others by supply shocks (manufacturing and mining, for instance), and others by both (entertainment, restaurants, and tourism), while some—and in particular, high-wage occupations—were relatively immune. But there are further very significant inequalities too. For instance, there are substantial gender inequalities associated with the pandemic: the requirement to stay at home, for instance, created a major shock to the demand and supply of home childcare ( Sevilla and Smith, 2020 , this issue). Couples with young children in the UK, for example, now find themselves performing a working week’s worth of additional childcare. The pre-COVID-19 characteristic—that women do the majority of such childcare (on average, about 65 per cent)—has continued, and women have been more likely than men to lose employment due to the pandemic ( Sevilla and Smith, 2020 ). In turn, there appear to be important age inequalities, too: the International Labour Office (ILO), for instance, argues that young people have been ‘disproportionately affected’ by the pandemic, which has disrupted their education and training, and forced them out of work; one in six young people surveyed by the ILO, for example, had stopped working since the start of the COVID-19 crisis ( ILO, 2020 ). And finally, there is growing evidence that the health impacts of COVID-19 are particularly harmful for black, Asian, and minority ethnic (BAME) communities; the UK government, for example, is launching a review to better understand this very troubling feature of the pandemic ( Kirby, 2020 ).

III. The economic interventions

Alongside the dramatic actions taken to mitigate the medical crisis are the extraordinary interventions that have been taken to tackle the economic crisis. Unprecedented discretionary fiscal policies have been adopted around the world. Governments have put forward swift and significant emergency lifelines to protect workers and businesses. The International Monetary Fund (IMF) first measured these interventions in April 2020, but as countries have stepped up their efforts it has updated its calculations: in May, the total was about US$9 trillion ( IMF, 2020 ). 4 This is a staggering sum: what has been spent or promised amounts to about 10 per cent of world GDP. 5 The breakdown looks like this: direct budget support is currently estimated at $4.4 trillion globally, and additional public-sector loans and equity injections, guarantees, and other quasi-fiscal operations (such as non-commercial activity of public corporations) amount to another $4.6 trillion ( IMF, 2020 ).

These interventions have had an important impact in mitigating the economic crisis. In the UK again, for instance, on some measures it appears that the fall in household incomes is more evenly spread across the income distribution than the loss of jobs is distributed across the earnings distribution ( Brewer and Gardiner, 2020 , this issue). In turn, unlike during the financial crisis of 2007–8, the financial system has remained strong and stable during the pandemic. As Giese and Haldane (2020 , this issue) explain, this was not the case a decade ago, when both bank balance sheets and the prudential regulatory standards that banks had to follow were very different from what they are now. Furthermore, monetary and financial policy have been able to support fiscal policy; the Bank of England, for instance, has expanded its balance sheets by almost a third in 3 months during the crisis ( Hauser, 2020 ).

In the UK, the policy centrepiece has been the Job Retention Scheme (JRS) or ‘furlough’ scheme, where employers receive 80 per cent (up to a limit £2,500 per month) of the wages of employees who are temporarily asked to stop working ( Mayhew and Anand, 2020 , this issue). This intervention not only reflects the scale of those seen in other countries, but also their imperfections. By early May, 6.3m workers had been furloughed, and it was expected it would rise further to 9m, about a quarter of the UK workforce. Yet as Mayhew and Anand (2020) explain, this bold policy still leaves large gaps and has significant flaws: the scheme, for instance, failed to cover 20 per cent of the UK’s workforce; the data were not available to judge if 80 per cent was the right figure; and it is unsustainable in the longer run.

This final point is key: around the world, many of these remarkable economic interventions were intended to be temporary emergency measures. There was a moment at the start of the pandemic when some commentators appeared to think the crisis might be relatively swift: lockdown would be imposed, but once the peak in infections had passed in a matter of weeks, extraordinary but temporary measures could be relaxed, economies would go through a swift v-shaped recovery, and economic life as it was before the pandemic would return. Historians would look back at the ‘great panic’ of 2020. This now seems extremely unlikely without an effective vaccine. A reasonable base case is that the virus and its consequences will be with us for some time. And so, the coming months are likely to be dominated by continued responses to both the medical and economic crises.

However, if the pandemic is to be more long-lasting, interventions designed for a short-lived crisis must be revisited. With respect to the medical crisis, as noted before, as lockdowns are relaxed, other interventions to keep R below 1 will need to be intensified. But in a similar way, our economic interventions must change. As Devereux et al. (2020 , this issue) argue, as we move out of lockdown and into a tentative period of recovery, it will be necessary to consider a new set of policy options: extension of short-time work and possible temporary subsidy for re-employment; corporation tax incentives; VAT reductions; and a holiday from taxes on business property. More generally, as noted before, radical fiscal measures that were designed to temporarily keep workers attached to their existing employers must be replaced with alternative, and more sustainable, measures ( Mayhew and Anand, 2020 ).

For instance, with respect to the JRS in the UK, from the beginning of July, the scheme becomes more targeted and is due to finish at the end of October: Mayhew and Anand (2020) argue that, rather than go cold turkey at this point and remove employment subsidies, there is a case for the introduction of a variant of the German-style working time accounts scheme. Nevertheless, there are difficulties ahead here. The structure of the economy which re-emerges may well be somewhat different from what it was in the past. To take one small example, it is likely that much more office work will be done remotely, setting up pressures for change in both the commercial property market and the residential property market. To take another example, some jobs are likely to just disappear, for example in retail. Although cold turkey seems like a bad idea, a generous furlough scheme which keeps workers in place where they have no future is also not a good idea. What is required, Mayhew and Anand, (2020) argue, is a comprehensive active manpower policy in its place to efficiently match job-seekers to available jobs.

IV. Reforming business and finance

Other substantial challenges also lie ahead. Some of the new-found economic interventions have created new risks for the corporate sector. For instance, another key policy in the UK has been the variety of COVID-19 loans which have been made available to firms. It is not clear how these are working: many firms appear to be unable to access them, and time will tell what the default rate on these loans will be—it seems likely that default rates will be high, and the systemic consequences are likely to be large. As Johnstone-Louis et al. (2020 , this issue) argue, massive bailouts of companies may end up being needed. These will impose substantial obligations on the corporate sector to respond and to lead the economy out of the crisis. When similar bailouts were provided for commercial banks after the financial crisis of 2007–8, the banks ended up imposing significant costs on the rest of the society in that they prioritized the rebuilding of their balance sheets ahead of looking after their customers. This is something which needs to be avoided. And there is a more general point: to offset the large debt overhang problem that has emerged and avoid the wave of bankruptcies that threaten economies, financial institutions will be expected to provide substantial amounts of new equity funding as well as accepting dividend cuts.

The COVID-19 pandemic has also led to more fundamental calls to reform business and finance. The last crisis—the financial crisis of 2007–8—was clearly the fault of business, and the financial sector in particular. This time round, business cannot be blamed for causing the pandemic. But it can be blamed for leaving economies so vulnerable to its consequences. With many companies having less than 3 months of reserves to cover their operating costs, 6 they have been forced to cut costs draconianly, be bailed out by governments, and slash their workforces. There is a case for arguing that stress testing should be extended beyond the financial sector as a whole to business more generally, and relate to a broader range of events than the macroeconomic ones on which they have been focused to date, for example pandemics, weather, and technology-related risks ( Giese and Haldane, 2020 ).

To some, the pandemic has exposed a failed system of corporate governance. As economies begin to recover, many are appealing to the idea of ‘building back better’. 7 But this requires a clearer conception of what exactly it is they want to build—and it is unlikely to be a corporate sector that generates profits on the back of environmental degradation, rising inequality, or social exclusion. Fixing this needs a recognition that business’s reason for being is to serve others than itself, its investors, or executives, and that their interests are derivative of, not the determinant of, its success in so doing ( Mayer, 2013 , 2018 , Morris and Vines, 2014 ). Good business can drive profits; profits do not necessarily drive good business, and good regulation does not solve the problem without good business.

But business cannot do this on its own. The pandemic has shown that business needs government, as well as government needs business. Mazzucato and Kattel (2020 , this issue) argue that we should forge new relations between government and the private sector. The innovation and experimentation that will be required to recover must come from the private sector, but this must take place in the context of governance arrangements that address social concerns and avoid the types of problems that have arisen in relation to, for example, data usage. Neither privatization nor public ownership have proven adequate to the task; ‘government actively shaping markets rather than simply fixing failures’ is how Mazzucato and Kattel describe an alternative approach. And as Collier and Mayer (2020 , this issue) note, public-sector funding will be needed alongside private finance, in particular in relation to the small and medium-sized enterprises (SMEs) that are most at risk of failure, especially in the most depressed and disadvantaged areas of a country. Channelling public funding to SMEs in these areas may involve more than the existing banking system can provide. The authors describe why this is the case in the UK and put forward suggestions for the development of new funding institutions to cope with it.

Milton Friedman was prescient when he said that ‘only a crisis, actual or perceived produces real change. When that change occurs, the actions that are taken depend on the ideas that are lying around’. ‘That’, he said, ‘is our basic function: to develop alternatives to existing policies, to keep them alive and available until the politically impossible becomes the politically inevitable.’ 8 The only question is how many crises will it take until we realize that he was quite wrong when he said that ‘there is one and only one social responsibility of business . . . to increase profits so long as it stays within the rules of the game’? 9

V. An emerging-market and developing-country perspective

At the time of writing, COVID-19 had already begun to reach low-income and middle-income countries. Such countries face an enormous challenge in dealing with this crisis, because the institutions of government and of public administration are much less well developed in these countries than in advanced countries. This issue of the Oxford Review of Economic Policy contains only one paper which discusses this challenge, by Gerard et al. (2020 , this issue), but that paper provides an eye-opening account of tasks that policy-makers will face in these countries. It seems that these countries may need to use a much broader patchwork of interventions than high-income countries. And the authors provide a view of what this patchwork might need to look like.

Job retention programmes already exist in some countries; some governments have leveraged id-linked bank accounts opened for financial inclusion purposes to provide direct support to the poor; and even populations that live at the margins of social protection systems—like migrant workers—are being reached through associations that work with them. Yet, as the authors show, any government response will be imperfectly targeted, with important inclusion and exclusion errors: government responses based on social insurance programmes will miss the informal sector; social assistance programmes are always specific to a particular dimension of poverty, and their delivery is often plagued with leakages; and involving local governments or non-state actors runs the risk of resources being diverted by local elites or used for clientelism.

Nevertheless, the authors conclude that fewer even imperfectly targeted transfers will reach some ‘left-behind’ households through family, informal, or formal sharing structures. The paper provides important examples of how, and in what way, this might happen and is already happening.

The authors conclude that the challenge of mitigating the economic effects of the pandemic is enormous in low-income and middle-income countries. Any solution will be flawed in many ways because speed is of the essence. But, they say, governments, donors, and civil societies have made major gains in the last 30 years in building infrastructure to reach the poorest. If internal and external financing can be found—and this is a big if—then developing countries might be able to use this to create the economic space for an effective public health response. But the challenge really will be enormous.

VI. International cooperation

The COVID-19 pandemic has created a global medical crisis, not just a national one. In Brown and Susskind (2020) , the authors show that the international response to the pandemic has fallen short, primarily because of a lack of effective global cooperation. Many of the tasks involved in controlling an infectious disease like COVID-19 are global public goods—a public good that spills across national borders with far-reaching consequences as a result—that can only be delivered through global cooperation. The paper discusses the discovery of vaccines as an example of the kind of cooperation that is needed: only one success, if shared with others, is needed to bring the pandemic to an end. But cooperation would also have to be strengthened because it is not enough just to discover a vaccine: it has to be mass manufactured and, if the disease is to be eradicated in every country to avoid further waves of the disease emerging in the future, distributed equitably. Brown and Susskind (2020) discuss just why many activities like this have been underfunded and under-provided until now, and they discuss how this might be remedied.

The pandemic has also created a global economic crisis. Indeed, it has caused the greatest collapse in global economic activity since the collapse of the South Sea Bubble in 1720. As noted before, some advanced countries have mounted a massive fiscal response, both to pay for disease-fighting action and to preserve the incomes of firms and workers until the economic recovery is under way. But there are many emerging market economies that have been prevented from doing what is needed by their high existing levels of public debt and—especially—by the external financial constraints which they face. McKibbin and Vines (2020 , this issue) argue that there is a need for international cooperation to allow such countries to undertake the kind of massive fiscal response that all countries now need, and that many advanced countries have been able to carry out. They show what such cooperation would involve and they use a global macroeconomic model to explore how extraordinarily beneficial such cooperation would be. Their simulations of the model suggest that GDP in the countries in which the extra fiscal support takes place would be something like two and a half per cent higher in the first year, and that GDP in other countries in the world be more than 1 per cent higher. And the percentage increase in employment in the countries in which there is extra fiscal support would be very much larger than the percentage increase in GDP.

So far, such cooperation has been notably lacking, in striking contrast with what happened in the wake of the global financial crisis of 2007–8. The necessary cooperation needs to be led by the Group of Twenty (G20), just as happened in that crisis, since the G20 brings together the leaders of the world’s largest economies. But this cooperation must also necessarily involve a promise of international financial support from the IMF, otherwise international financial markets might take fright at the large budget deficits and current account deficits which will emerge, creating fiscal crises and currency crises and so causing such expansionary policies which we advocate to be brought to an end.

McKibbin and Vines (2020) do not discuss the case of the poorest countries in the world. But the problem just described has created huge problems for countries in sub-Saharan Africa. These are discussed in detail by Adam et al. (2020 , this issue). The authors capture quite what a catastrophic external position these countries are now in, something which is likely to require them to embark on massive fiscal austerity at just the wrong time. They show very clearly just how much of an increase in overseas development assistance (ODA) would be required to help these countries deal with the medical and fiscal problems which the COVID-19 pandemic has thrust upon them. In particular, they show that merely keeping the degree of domestic fiscal adjustment within reasonable bounds—i.e. ones which seem politically feasible—would require about an extra $50 billion of ODA. That would, in effect, mean a doubling of the aid which these countries receive. They would need three times as much aid if the aim was to fully isolate them from the COVID-19 shock.

The pandemic is also likely to have dramatic consequences for global progress on mitigating climate change. As Hepburn et al. (2020 , this issue) note, in the short term the policy response has curtailed economic activity and thus also slashed greenhouse gas emissions. But once restrictions are relaxed, emissions will be likely to soar once again. In the medium term, then, there is an opportunity, when designing discretionary fiscal policy, to consider interventions that are likely both to promote economic recovery and displace the current fossil-fuel intensive economic system: Hepburn et al. (2020) identify possible policies that score highly on both economic multiplier and climate impact metrics. In the longer term, COVID-19 could also result in changes to human habits and behaviours, business, and global institutions, which will have impacts—positive and negative—on the likelihood of reaching net zero emissions before temperatures rise to catastrophic levels.

The pandemic raises many other significant international issues. For instance, as Fernández-Reino et al. (2020 , this issue) note, the pandemic has increased public awareness of the extent to which the economy relies on a low-wage workforce. But given that many of these occupations are also heavily dependent on migrant workers, this is likely to have substantial implications for immigration policy: now, and in the future, not just in the UK but elsewhere, too. In turn, there are the enormous problems the pandemic has created for the international trading system. It has had a dramatic impact on international trade between countries: a drop by about 38 per cent in France, and 25 per cent in Turkey and Germany, for instance, relative to historical averages ( Demir and Javorcik, 2020 this issue). And already protectionist pressures have reared their head, as Brown and Susskind (2020) also describe. There is a need to ensure that global cooperation in trade policy goes hand in hand with global cooperation on health and macroeconomic policy.

The last time the world faced challenges as serious as those which we now face was at the end of the Second World War. At that time there was an extraordinary burst of institutional creativity. The Bretton Woods conference in 1944 led to the creation of the IMF, in order to ensure international financial stability. It also led to the establishment of the World Bank as an institution which would lend money to what were then the emerging market economies of Europe and Asia. Soon afterwards the Marshall plan also started to provide money for countries in need. The next year, in 1945, saw the foundation of the United Nations (UN); the World Health Organization became part of the UN in 1948. A 1946 conference in San Francisco led to the establishment of the General Agreement on Tariffs and Trade, which, nearly 40 years later became the World Trade Organization.

After the First World War things were very different. Although the League of Nations was established in 1920, it never really gained the necessary authority. First the world slid into the Great Depression of 1930s. Then the world lurched into the Second World War.

The post-Second World War institutions have served the world remarkably well. Now, following the COVID-19 pandemic, they need strengthening and reinvigorating. But they still provide a framework within which international cooperation can take place. Because the pandemic is such a very large event we need to realize that the world faces a very large choice. We can do what the world did in the late 1940s, when the institutional choices which were made helped to support the golden age of global growth during the 1950s and 1960s. Or we can instead allow what happened in the 1930s to happen all over again. That is the decision which we now face.

The authors are grateful to the other members of the Editorial Board of the Oxford Review of Economic Policy— namely, Christopher Adam, Simon Cowan, Cameron Hepburn, Colin Mayer, Ken Mayhew, Simon Quinn, and Alexander Teytelboym—for very many helpful suggestions.

1 This puts to one side the possibility that herd immunity, or something close to herd immunity, is achieved by allowing the disease to run rampant throughout the community.

2 The National Institute for Health and Care Excellence (NICE) assumes £20,000–£30,000 per quality-adjusted year of life. Office for National Statistics life tables and statistics on the age, sex, and underlying health condition of COVID-19 fatalities suggest that the average person dying from the disease loses about ten years of life.

3 If the authors impose the condition that peak infection must not exceed what the health service can handle, they show that it would be optimal to dispense with lockdown if the value of life were to be below £1.56 million.

4 Also see Fiscal Monitor .

5 World GDP is somewhere between $80 and $100 trillion, depending on how it is measured.

6 British Chamber of Commerce (2020) .

7 See, for instance, https://www.buildbackbetteruk.org/ .

8 Friedman (1982) .

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IMAGES

The Economics of COVID-19
The Economics of COVID-19
楽天ブックス: The Economics of Covid-19
A First for Literature from the Faculty of Economics: COVID-19 Report
Economics in the Time of COVID-19
Economic & Market Impacts

COMMENTS

A literature review of the economics of COVID-19 - PubMed
The goal of this piece is to survey the developing and rapidly growing literature on the economic consequences of COVID-19 and the governmental responses, and to synthetize the insights emerging from a very large number of studies.
A literature review of the economics of COVID‐19 - Brodeur ...
The goal of this piece is to survey the developing and rapidly growing literature on the economic consequences of COVID-19 and the governmental responses, and to synthetize the insights emerging from a very large number of studies.
A literature review of the economics of COVID‐19 - PMC
This article will focus on five broad areas: (i) the measurement of the spread of COVID‐19 and social distancing activities, (ii) the effectiveness and compliance with social distancing regulations, (iii) the economic impacts of COVID‐19 and the mechanisms giving rise to them, (iv) the socioeconomic consequences of lockdowns, and (v) the ...
A Literature Review of the Economics of COVID-19 | IZA ...
IZA DP No. 13411: A Literature Review of the Economics of COVID-19. The goal of this piece is to survey the emerging and rapidly growing literature on the economic consequences of COVID-19 and government response, and to synthetize the insights emerging from a very large number of studies.
A literature review of the economics of COVID‐19 - ResearchGate
This survey: (i) provides an overview of the data sets and the techniques employed to measure social distancing and COVID‐19 cases and deaths; (ii) reviews the literature on the determinants of...
A literature review of the economics of COVID‐19
1 INTRODUCTION. Anik Islam. Suraiya Bhuiyan. Abstract. The goal of this piece is to survey the developing and rapidly growing literature on the economic conse-quences of COVID-19 and the governmental responses, and to synthetize the insights emerging from a very large number of studies.
The economics of COVID-19: a systematic literature review
The objectives of this study are (1) to examine the growing literature on variations of economic factors due to COVID-19 (2) to review the literature on the governmental response to the...
The economics of COVID-19 pandemic: A survey - PMC
Through a survey of the literature on the economics of the coronavirus (COVID-19) pandemic, this study explores the effects of the pandemic and proposes potential policy directions to mitigate its effects.
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The COVID-19 pandemic has impacted the scope of health economics literature, which will increasingly examine value beyond health care interventions such as government policy and broad health system innovations. Aim.
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The COVID-19 pandemic has created both a medical crisis and an economic crisis. As others have noted, we face challenges just as big as those in the Spanish Flu Pandemic and the Great Depression—all at once. The tasks facing policy-makers are extraordinary. Many new kinds of intervention are urgently required.