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A Case of Plasmodium Falciparum Malaria Presentation

Editor(s): Naveed, Khan.

From the Lincoln Medical and Mental Health Center, New York, New York, USA.

Correspondence: Osman Nawazish Salaria, Lincoln Medical Center, New York, New York USA (email: [email protected] ).

Abbreviations: BPb = lood pressure, bpm = beats per minute, BUNb = lood urea nitrogen, CDC = Center for Disease Control, cm = centimeters, Creatc = reatinine, DOHMH = Department of Health and Mental Hygiene, ED = Emergency Department, Hb = hemoglobin, Hct = hematocrit, ICU = intensive care unit, IV = intravenous, IVP = intravenous push, Plt = platelet, WBC = white blood cell, WHO = World Health Organization, y/o = year old.

Methods: Ethical approval was not necessary for this study as the study was focused on the patient hospital course and did in no way alter or affect her treatment. Informed Consent was taken from the patient regarding the publishing of this case report and the patient accepted.

The authors have no conflicts of interest to disclose.

This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0

Received April 20, 2015

Received in revised form July 11, 2015

Accepted July 27, 2015

New York City is a multicultural city where people of different ethnicities and backgrounds from all over the world live together. Of the different ethnicities, it is home to a large population of Western African immigrants. This case report is that of an elderly female of Western African descent presenting to Lincoln Hospitals Emergency Department with fevers and fatigue.

The patients travel history to Togo, along with her symptoms, resulted in a differential diagnosis which included Ebola as well as Malaria. New York City's Department of Health and Mental Hygiene was contacted for further clarification of presence of Ebola in Togo. The present case report is meant to educate about the presentation, hospital course, and differential diagnoses of a patient traveling from Western Africa with fever and chills.

INTRODUCTION

Malaria is a frequent parasitic infection prevalent in Africa. Around 300 million are infected annually in Africa by malaria and 1 to 2 million will die from the disease. 1 Of the 4 human parasitic species that have been identified, Plasmodium falciparum has been known to cause significant morbidity and mortality, particularly in children and pregnant women. 1 Strategies to counteract malaria incidence, such as community health workers outreach and insecticide treated nets have been instituted in recent years; however, their effect has not been of much significance. 2

Ebola virus disease has caused much concern with its global rise in incidence and prevalence recently. The current epidemic which has centered mainly in Western African nations of Guinea, Sierra Leone, and Liberia has now spread outside of borders of Africa to involve the United States. 3 Much of the presenting symptoms and signs of the disease mimic other diseases such as typhoid fever and malaria. 3,4

There is much overlap between presentations of both P. falciparum malaria and Ebola virus disease. Without confirmatory blood tests searching for malaria parasites or viral RNA and viral antibodies a diagnosis is very difficult to achieve.

CASE REPORT

A 67 y/o (year old) female from Western Africa initially presented to the Emergency Department (ED) complaining of fatigue and subjective fevers for the past 2 days. Patient complained that her fevers were associated with headaches, but not chills, rigors, or chest pain. Index of suspicion for malaria was high as patient had recently traveled from an endemic region. Patients travel history to Western Africa and the presenting symptoms also made us consider a possibility of Ebola virus disease.

Past medical history included diabetes, hypertension, and a history of recent travel to her home country of Togo for 5 months. Patient had returned 5 days ago from her travel and started to develop symptoms of fevers and fatigue. Patient denied any immunizations received before traveling. Past surgical history included a left breast mastectomy done back in France 1987. Medication history included Amlodipine, Aspirin, Calcium Carbonate, Synthroid, Pioglitazone, Humalog, Glucovance, Crestor, Januvia, and Lisinopril. After initial presentation to the ED for 2 days of fevers and fatigue, she was accepted by Medicine and transferred to the general medical floors. The patient had a blood pressure of 123/55, pulse of 86 beats per minute (bpm), Temperature of 98.5 °F, and respiratory rate of 16 at the time of admission. Physical examination did not disclose any specific abnormalities.

Labs including complete blood count, chemistry, liver function tests, malaria peripheral smears, and reitculocyte level were withdrawn from the patient. Patient had white blood cell (WBC) count of 12.6, Hb (hemoglobin) 10.7, Hct (hematocrit) 30.6, Plt (platelet) 80, BUN (blood urea nitrogen) 12, Creat (creatinine) 0.3, and blood glucose of 291 consistent with diabetes. Blood smears were positive for P. falciparum malaria at 9.6% and reticulocyte count was reported at 3.2%. New York City's Department of Health and Mental Hygiene (DOHMH), was contacted and Ebola was not considered to be in Togo, most likely diagnosis was malaria from chloroquine resistant region. Patient was started on quinine 648 mg and doxycycline 100 mg, intravenous (IV) fluids, Lantus 21 U, Lispro 7 U, and was monitored in telemetry unit of medicine (Figures 1–3).

Attention was drawn to the patient at 4:45 AM on her 3rd hospital course day after becoming suddenly dyspneic. Patient denied any chest pain but upon pulmonary examination bilateral coarse crackles were heard up to mid lung level. Patient received 60 mg intravenous push (IVP) Lasix and sublingual nitroglycerin. She continued to be dyspneic and was given additional 40 mg IV Lasix and 4 mg Morphine IV were given. Bi-continuous positive airway pressure was started but patient did not tolerate well and decision was made to intubate the patient for acute hypoxemic respiratory failure. Patient was transferred to the medical intensive care unit (ICU) for further care.

Chest X-ray in the medical ICU revealed bilateral alveolar infiltrates; patient was started on Cefepime 2 g IV. Presumption was made that patient had Acute Respiratory Distress Syndrome secondary to sepsis from an unknown source of infection, but possibly from Falciparum Malaria. Abdominal ultrasound showed tiny echogenic foci within the gallbladder, prominent liver measuring 18.7 cm, and a dilated common bile duct measuring 8.2 mm. Choledocholithiasis was questioned although not directly visualized. Decision was made to monitor liver enzymes and if worsening of abdominal status cholecystostomy tube could be placed.

Patient remained in the medical ICU where she was daily monitored. Vital signs monitoring showed daily fever spikes of 101 to 103 °F 2 to 3 times per day. Liver enzymes were down trending after week 1, repeat right upper quadrant ultrasound was negative most probably from passage of a gallstone. On day 9 of hospital course patient was extubated and transferred to medical floors for continuation of care.

Patients of Western African descent presenting with symptoms of fevers and fatigue must be approached with precaution in present day circumstances. The Ebola virus disease outbreak has currently heightened healthcare professional's fears of contracting the virus by exposure to their patients. Furthermore, the impact of the Ebola virus disease in West Africa has left the local population vulnerable to other deadly diseases such as malaria. Control efforts for disease transmission and treatment of malaria have come to a halt. Anti-malaria medication, preventive insecticide bed nets are lying in warehouses far from the people which could benefit from them. International agencies such as the World Health Organization (WHO), US Agency for International Development supported and funded programs malaria control initiatives have virtually been shut down. 5 The similarities of the symptoms and signs of presentation of both diseases intimidates people from seeking treatment for fear of being infected with Ebola.

In face of all these difficulties, Ebola control efforts including government education programs partnered with WHO, travel measures has reduced the incidence significantly. Early identification of symptoms, isolation of contacts, and early monitoring and treatment has played a major role in limiting spread of infection of Ebola. This case report illustrates an example of how a patient with recent travel history to West Africa presenting with typical fevers, myalgias, and fatigue could be considered to have either or both diseases.

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Upper Mustang region of Nepal.

Photo by Christina Warinner

Christy DeSmith 

Harvard Staff Writer

New study of ancient genomes tracks disease over 5,500 years, factors in spread, including trade, warfare, colonialism, and slavery

Today, Malaria represents a major public health problem across much of the globe, killing  more than 600,000  people annually and infecting another 250 million. It is a disease that has been around for millions of years and is undeniably entwined with human history. 

“Malaria has actually shaped the human genome,” said  Megan Michel , a Ph.D. candidate in human evolutionary biology at the  Kenneth C. Griffin Graduate School of Arts and Sciences . She pointed out that certain inherited blood disorders, like sickle cell disease, rose in prevalence because they provide a measure of resistance to the mosquito-borne infection. 

Now a new study led by Michel reconstructs the ancient genomes of the two deadliest malaria parasites, Plasmodium falciparum and Plasmodium vivax, with an eye to understanding the pathogen’s past. The research, published this week in  Nature , tracks the disease over 5,500 years, with trade, warfare, colonialism, and slavery identified as major factors in its global spread. 

The findings represent a feat of collaboration and data-sharing, with 94 co-authors representing 80 institutions and 21 countries. The DNA itself was plucked from genetic sequences collected from more than 10,000 ancient humans, with Michel identifying 36 malaria-infected individuals from 26 archaeological sites on five continents.

“For a graduate student to be coordinating all of this is really, really impressive,” said co-author  Christina Warinner , the John L. Loeb Associate Professor of the Social Sciences and one of Michel’s three advisers. “By reconstructing these ancient Plasmodium genomes and comparing the genetic relationships between ancient and modern parasites, we’re finally able to place malaria in its evolutionary and human history context.”

“By reconstructing these ancient Plasmodium genomes and comparing the genetic relationships between ancient and modern parasites, we’re finally able to place malaria in its evolutionary and human history context.” Christina Warinner, the John L. Loeb Associate Professor of the Social Sciences

Malaria is marked by cyclical fevers that repeat every 48 or 72 hours. Until recently, written records were the only way researchers could track the disease’s progression across time and space. “There are descriptions in Greek and Roman texts that point to the presence of malaria,” Michel said. “But we were able to go back even further than that to show that malaria has been present in Europe for a very, very long time.”

The disease was also common in the U.S. until the arrival of  modern drainage and insecticides  in the 20th century. Warinner, a biomolecular archaeologist, pointed to the high number of  U.S. presidents  to suffer from malaria, including George Washington, Abraham Lincoln, and Ulysses S. Grant. “Teddy Roosevelt and JFK became infected while traveling,” she said, “but earlier presidents contracted it in their hometowns or in the Washington, D.C., area” — which was notoriously swampy. 

The new paper features three compelling case studies, each illustrating the role of mobility in circulating malaria. The first concerns a  Belgian cemetery ,  excavated between 2009 and 2011  and adjacent to the first permanent military hospital in early modern Europe. Historical records document that the Habsburg Army of Flanders recruited its soldiers from the Mediterranean region for its 80 Years’ War against Spain (1568-1648). 

Malaria leaves no visible trace in human skeletal remains, but recent technological advances have enabled scientists to extract DNA from scraps of the pathogen found in teeth. Researchers were able to sequence malaria DNA from 10 individuals buried at the cemetery while also analyzing the genomes of soldiers who had been infected.

“We found that individuals buried at the cemetery have diverse ancestry profiles,” explained Michel, whose Ph.D. research is supported by the  Max Planck - Harvard Research Center for the Archaeoscience of the Ancient Mediterranean . “They’re not just from Belgium. They seem to also be coming from northern Spain and from Italy.”

The two most prevalent malaria parasites in humans are P. vivax and P. falciparum, with the latter limited to warm climates and causing a more severe form of the disease. Analyses of pathogen DNA turned up a couple of P. vivax cases in the Belgian site’s local population, buried at the cemetery prior to the hospital’s construction in the mid-16th century. 

Six cases, including several of the more virulent P. falciparum, were found in non-local individuals, all interred following the military hospital’s construction. Malaria cannot be transmitted through human contact, but mosquitos may have picked up these infections — and kept up the spread from there. “It’s even possible they ignited a local outbreak,” Michel said.

A bite from an infected mosquito transmits malaria.

Liz Zonarich/Harvard Staff; source: Mayo Clinic

The parasites travel to your liver where they lie dormant, usually about 10 days to four weeks.

Parasites leave the liver and infect red blood cells. Malaria signs and symptoms typically develop.

Malaria is transmitted to an uninfected mosquito when it bites someone with the disease.

Another case study came from Peru, where a single P. vivax case was found in a person who lived at high altitude (more than 9,300 feet) in the Central Andes. “This individual was associated with the  Chachapoya culture ,” Michel said, “and  the site we were working with  spanned the period of European contact.”

For years, scientists have debated how the disease arrived in the Americas, where Indigenous populations lack genetic resistance to malaria. Reconstructing the genome of the Peruvian parasite revealed striking similarities to P. vivax strains found throughout South America today. It also resembled strains circulating in Europe during the 15th and 16th centuries.

“We think this is evidence that the species was transmitted by European colonizers to the Americas,” Michel said.

No ancient P. falciparum was found in the Americas, Michel noted, and P. falciparum strains circulating there today bear little resemblance to the ancient European P. falciparum parasites recovered by Michel and her co-authors. “Instead, American strains today look very similar to strains in Sub-Saharan Africa,” Michel said. “It seems likely that P. vivax was transmitted from Europe, whereas P. falciparum was probably transmitted from Sub-Saharan Africa as a result of the trans-Atlantic slave trade.”

Michel got her biggest surprise from the paper’s third case study. The Himalayan site of Chokhopani , situated more than 9,100 feet above sea level in Nepal’s Mustang region, yielded the  earliest known case of P. falciparum . 

“It’s the last place on Earth I would expect to find a malaria infection,” Michel shared. “It’s rocky and dry and too cold for malaria-transmitting mosquitoes to survive.”

The infected individual lived 2,800 years ago. “We know from the archaeological record that there was extensive long-distance trade in the region,” explained Michel, who partnered with co-author  Mark Aldenderfer  — an archaeologist  working in the Mustang region for many years  — to analyze the findings. “We think this was probably an individual who moved from low to high altitude, possibly for trade. They must have acquired this infection at a lower altitude where the parasite can be transmitted.”

“The site of Chokhopani is near the Kora La pass, the lowest crossing point through the Himalayas and a key trade route connecting South Asia with the Tibetan Plateau,” added Warinner, who traveled with Michel to the region last spring to share results and solicit feedback from descendent communities. “Fortunately, Nepal has been really successful in eradicating malaria in the last few years. But even as recently as 10 years ago, malaria was endemic in Nepal’s lower elevation regions.”

Making these revelations possible are the emerging tools of  metagenomics , which rely on recovering and sharing as much genetic data as possible with different specialists. “When we analyze an ancient sample, we, by its nature, destroy it in order to retrieve the DNA,” Warinner explained. “We want to get as much information as possible. We really do recover total DNA.”

“Metagenomics and data-sharing allow us to find things we’re not really looking for,” Michel added. “It lets us find disease in unexpected places. I never would have screened samples from Chokhopani for malaria if they hadn’t already been sequenced by Dr. Warinner for another ancient DNA study.”

The research described in this report received funding from the National Science Foundation

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• Research article
• Open access
• Published: 10 June 2024

Expanding community case management of malaria to all ages can improve universal access to malaria diagnosis and treatment: results from a cluster randomized trial in Madagascar

• Andres Garchitorena   ORCID: orcid.org/0000-0001-6225-5226 1 , 2 ,
• Aina Harimanana 2 ,
• Judickaelle Irinantenaina 2 ,
• Hobisoa Léa Razanadranaivo 2 ,
• Tsinjo Fehizoro Rasoanaivo 2 ,
• Dean Sayre 3 ,
• Julie R. Gutman 4 ,
• Reziky Tiandraza Mangahasimbola 2 ,
• Masiarivony Ravaoarimanga 2 ,
• Oméga Raobela 5 ,
• Lala Yvette Razafimaharo 5 ,
• Nicolas Ralemary 6 ,
• Mahefa Andrianasolomanana 7 ,
• Julie Pontarollo 8 ,
• Aline Mukerabirori 9 ,
• Walter Ochieng 10 ,
• Catherine M. Dentinger 11 ,
• Laurent Kapesa 12 &
• Laura C. Steinhardt 4  

BMC Medicine volume  22 , Article number:  231 ( 2024 ) Cite this article

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Global progress on malaria control has stalled recently, partly due to challenges in universal access to malaria diagnosis and treatment. Community health workers (CHWs) can play a key role in improving access to malaria care for children under 5 years (CU5), but national policies rarely permit them to treat older individuals. We conducted a two-arm cluster randomized trial in rural Madagascar to assess the impact of expanding malaria community case management (mCCM) to all ages on health care access and use.

Thirty health centers and their associated CHWs in Farafangana District were randomized 1:1 to mCCM for all ages (intervention) or mCCM for CU5 only (control). Both arms were supported with CHW trainings on malaria case management, community sensitization on free malaria care, monthly supervision of CHWs, and reinforcement of the malaria supply chain. Cross-sectional household surveys in approximately 1600 households were conducted at baseline (Nov–Dec 2019) and endline (Nov–Dec 2021). Monthly data were collected from health center and CHW registers for 36 months (2019–2021). Intervention impact was assessed via difference-in-differences analyses for survey data and interrupted time-series analyses for health system data.

Rates of care-seeking for fever and malaria diagnosis nearly tripled in both arms (from less than 25% to over 60%), driven mostly by increases in CHW care. Age-expanded mCCM yielded additional improvements for individuals over 5 years in the intervention arm (rate ratio for RDTs done in 6–13-year-olds, RR RDT6–13 years  = 1.65; 95% CIs 1.45–1.87), but increases were significant only in health system data analyses. Age-expanded mCCM was associated with larger increases for populations living further from health centers (RR RDT6–13 years  = 1.21 per km; 95% CIs 1.19–1.23).

Conclusions

Expanding mCCM to all ages can improve universal access to malaria diagnosis and treatment. In addition, strengthening supply chain systems can achieve significant improvements even in the absence of age-expanded mCCM.

Trial registration

The trial was registered at the Pan-African Clinical Trials Registry (#PACTR202001907367187).

Peer Review reports

Despite ambitious targets for malaria control and elimination, annual global malaria cases are estimated to have increased by 17 million from 2015 to 2021 [ 1 ]. Ensuring universal access to malaria diagnosis and treatment is a key pillar of the global malaria strategic plan for 2016–2030 [ 2 ], but access remains limited in sub-Saharan Africa (SSA), a region that bears 95% of the global malaria burden [ 1 ]. Community health workers (CHWs) can play a critical role in expanding access to care, especially in rural and more remote areas [ 3 ]. However, CHWs typically only diagnose and treat children under five years of age (CU5) as part of integrated community case management (iCCM), a strategy initially recommended by UNICEF and WHO to reduce mortality from the most common childhood illnesses: malaria, pneumonia, and diarrhea [ 4 ]. Previous studies have shown that CHWs can effectively manage patients for these diseases [ 5 , 6 , 7 ] and that they can improve access to quality care for CU5 [ 8 ]. With evidence of CHWs’ ability to extend the reach of the health system, multiple efforts are trying to expand the scope of their work [ 9 , 10 , 11 ].

Beyond child-focused interventions, CHWs can play an important role in diagnosing and treating malaria cases of all ages. This is already the case in many countries pursuing malaria elimination nationally or sub-nationally [ 12 ]. In moderate to high transmission settings, engaging CHWs in efforts to visit homes at regular intervals, identify febrile household members, and test and treat them according to a standard protocol, a strategy known as proactive community case management (pro-CCM), has shown some success in increasing malaria cases detected [ 13 , 14 ] and improving malaria outcomes [ 15 , 16 ]. However, pro-CCM approaches can be time- and resource-consuming for CHWs, who are often volunteers in many SSA countries due in part to a lack of funding for community health programs. As a less resource-intensive alternative, several countries have expressed interest in expanding malaria community case management (mCCM) to older children and adults, but few countries have formally adopted this policy to date. Rigorous evaluation of the age expansion of mCCM has been limited, although an initial analysis in Rwanda suggested that the incidence of severe malaria in areas where CHWs provided mCCM to all individuals was lower than in those where mCCM was restricted to CU5 during a malaria upsurge, presumably due to increased access to prompt and effective malaria case management [ 17 ].

Expanding mCCM to individuals over five years of age was included in the 2018–2022 National Malaria Strategic Plan in Madagascar [ 18 ]. The country has seen a surge in malaria cases in recent years, with both malaria incidence and mortality increasing by over 75% between 2015 and 2021 [ 1 ]. Malaria transmission on this island-nation off the southeastern coast of Africa is heterogeneous, with an average national prevalence in children under 5 years of 7.5% in 2021 that ranged from very low in the highlands (< 1% prevalence) to high transmission in many coastal areas (> 20% prevalence) [ 19 , 20 ]. Madagascar has a network of approximately 36,000 CHWs who provide iCCM services to CU5, as well as health prevention and promotion services to communities, among other activities [ 21 ]. The population coverage target set by the Madagascar Ministry of Public Health (MoPH) is one CHW per 1000 individuals, and there are generally two CHWs in every fokontany , the smallest administrative unit in Madagascar comprising one or several villages. CHWs are not formally paid, although some receive incentives for attending trainings or monthly meetings at health centers, or for participating in campaigns outside their regular duties (e.g., bed net distribution, mass drug administration, vaccination). Although malaria services are officially free, CHWs are authorized to earn money from the sale of other health commodities and treatments [ 22 ]. Prior to a policy shift that would allow CHWs to diagnose and treat febrile people of all ages for malaria across the country, assessing the effectiveness of expanding mCCM to older ages in one pilot district was deemed necessary by the National Malaria Control Program (NMCP) and its partners. This cluster-randomized study was undertaken in a rural district in southeastern Madagascar to assess the impact of expanding mCCM to all ages in improving access to and use of malaria case management services.

Farafangana is a coastal district in the Atsimo Atsinanana Region in south-eastern Madagascar with a population of approximately 400,000 individuals, 90% of whom live in rural areas [ 23 ]. Farafangana has 38 public health facilities and over 600 CHWs, who receive supplies and supervision during monthly visits to their supervising health facility. Malaria transmission in the district varies seasonally, with increased transmission during the rainy season from October to April. Passive surveillance data from 2015 to 2017 indicated an average annual incidence of nearly 100 cases per 1000 population [ 24 ]. Farafangana benefits from long-term support from the non-governmental organization (NGO) Inter Aide, which has strengthened community health activities for over ten years through monthly supervision efforts, data quality reviews, training of CHWs on iCCM, and community sensitization on a range of health issues, including malaria. Despite regular mass distribution campaigns of long-lasting insecticide-treated bed nets and indoor residual spraying campaigns (before the study, the latest was in 2018 with Actellic® 300CS), Farafangana continued to have high levels of malaria transmission when the study was implemented in 2019.

Study design

The study was a two-arm cluster-randomized intervention trial, randomizing 15 health facilities with their CHW catchment areas to age-expanded mCCM (intervention arm) and 15 health facilities with their CHW catchment areas to standard mCCM for CU5 only (control arm) (Fig.  1 ). Non-rural health facilities were excluded from the study. In both arms, CU5 had access to iCCM through CHWs in their fokontany , and individuals of all ages had access to malaria case management at the nearest health facility, corresponding to the current national policy. The main objective was to evaluate the impact that the expansion of mCCM to all age groups (referred here as age-expanded mCCM) had on rates of care-seeking for fever, and malaria diagnosis and treatment in the study area. Health facilities were assigned by the study team to intervention and control groups using restricted randomization to ensure malaria prevalence in children and rates of care-seeking were balanced between arms. For this, a random subset consisting of 500,000 of the 1.55 × 10 8 possible combinations was generated. For each member of this subset, aggregate group malaria prevalence estimates in children and household-level care-seeking estimates generated during the baseline survey were calculated. For the purposes of this calculation, household-level care-seeking was dichotomized into those with a member seeking care from a health facility or community health worker within the past month and those without a member seeking care from these sources within the past month. The final study assignment was randomly selected from the schemes within the subset (4.2% of the 500,000 combinations) having matching malaria prevalence in intervention and control groups (+ / − 0.01) and matching household-level care-seeking estimates (+ / − 0.02).

Study design of mCCM cluster randomized trial in Farafangana District. A Map of Farafangana district and the health center catchments randomized to the intervention (yellow) and control arms (green). B Summary diagram of data collected at baseline, follow-up, and endline, and main intervention activities implemented. Note: in addition to household surveys, qualitative information was gathered at endline via individual interviews and focus groups (results presented in a separate manuscript)

Outcome measures, hypotheses, and sample size

Our primary outcome was the proportion of individuals 2 months of age or older reporting a fever in the previous 2 weeks who were tested with a malaria RDT by a CHW or at a health facility by a health worker. Secondary outcome measures were:

Proportion of individuals 2 months of age or older reporting a fever in the previous 2 weeks who (i) sought care for that illness and (ii) if tested positive for malaria, received treatment with an appropriate antimalarial.

Proportion of children < 5 years, children 5–14 years, and those aged 15 + years with febrile illness in the previous 2 weeks who (i) sought care for that illness, (ii) were tested for malaria with a malaria RDT, and (iii) were treated with an appropriate antimalarial if tested positive for malaria.

Community-level parasite prevalence in children under 15 years (including subgroup analyses for < 5 years and 5–14 years) of age as measured by malaria RDT.

Proportion of children < 5 years with suspected pneumonia and diarrhea in the previous 2 weeks who sought care and who received appropriate treatment.

These outcomes were evaluated through difference-in-difference analyses of cross-sectional household survey data (primary analysis), and through interrupted time-series analyses with control groups of equivalent health system data from all health facilities and CHWs in the study area (except for malaria prevalence). Both sets of analyses were pre-specified in the protocols approved prior to the beginning of the trial. Details on data collection and analysis for each data source are available in the corresponding sections below. A detailed description of each outcome measure is available in the Additional file 1 : Table S1.

We hypothesized that age-expanded mCCM would lead to an increase in care-seeking by patients with fever, in the proportion of subjects with fever who received a malaria RDT, and in the proportion of cases of malaria confirmed by RDT who received adequate antimalarial treatment. More specifically, for our sample size calculation for the primary outcome (proportion of people with fever in the last 2 weeks who are tested for malaria by a CHW or at a health facility by a health worker) for the cross-sectional surveys, we assumed that on average, 56% of households would have a respondent reporting a fever in the past 2 weeks and that 18% of febrile people are tested for malaria at baseline. Assuming an intraclass correlation coefficient of 0.1 for the primary outcome and an increase in the proportion of people with fever who are tested for malaria from 18 to 22.5% in the control arm, and from 18 to 39.5% in the group with age-expanded mCCM (17 percentage point difference at endline), 80% power, and assuming a 15% non-response rate, we estimated that we needed 56 households per facility, or 28 per sampled EA (total of 838 households in each arm). We also assumed that care-seeking and treatment for children under 5 years of age with pneumonia and diarrhea would not be affected by the intervention.

Intervention implementation

The intervention was initially planned to begin in March/April 2020 with a duration of 20 months but was delayed for eight months as a result of the COVID-19 pandemic, thus implementation lasted only 14 months. All CHWs in the study area received a refresher training on mCCM for CU5 and data collection tools, and a community sensitization campaign was conducted in October 2020. In addition, CHWs in the intervention arm were trained on age-expanded mCCM. An initial set of supplies was provided to all CHWs at the end of the training, including malaria rapid diagnostic tests (RDTs) and artemisinin-based combination therapy (ACTs), surgical masks for COVID-19 protection, and supplies for waste management. In each commune (grouping of several fokontany ) in the intervention arm, sensitization on mCCM for all ages was provided to local leaders, including village leaders, mayors, heads of fokontany , midwives, and CHWs. Mass gatherings were avoided due to the risk of COVID-19 transmission. In addition, radio broadcasts sensitized the entire study population and included reminders that supplies for malaria diagnosis and treatment were free of charge as part of the current NMCP policy.

The mCCM intervention was implemented from November 1st, 2020, to December 31st, 2021. In both arms, CU5 attending a CHW for febrile illness were managed according to existing iCCM protocols in Madagascar. In brief, CHWs are trained to do an RDT for all CU5 presenting with fever. Children under 2 months of age, CU5 with signs of severe illness (e.g., lethargy, seizures, or inability to breastfeed) are referred to health facilities. Uncomplicated malaria cases should receive artesunate–amodiaquine. In addition, CHWs were instructed to conduct a malaria RDT for all people aged 5 years or older with fever in the intervention arm. RDT-positive individuals were assessed and classified as uncomplicated or severe malaria cases according to national guidelines. All women aged 15–45 years with a positive RDT were asked about their pregnancy status; if women were pregnant or did not know their pregnancy status, they were referred to a health facility in the event of a positive malaria RDT. Individuals presenting with signs of severe illness (e.g., lethargy, seizures, anemia, stroke, abnormal bleeding) were also referred to health facilities regardless of RDT results. All individuals diagnosed with uncomplicated malaria (i.e., RDT-positive, non-pregnant individuals not displaying warning signs) received artesunate–amodiaquine from the CHW. Those with a negative RDT (and CU5 with no other obvious cause of fever according to iCCM) were referred to the nearest health facility.

In both arms, routine monthly reviews with CHWs were conducted at the health center as per standard CHW policy and were supported by a team of study supervisors in partnership with staff from Inter Aide during intervention implementation. The goal of these reviews was to (i) address challenges in case management and the use of different data collection tools by CHWs, providing additional on-site training where necessary, (ii) collect data from health center registers and from CHW monthly reports, and (iii) support supply chain management at the community level by helping CHWs with the supply ordering process and provision of additional malaria supplies in urgent cases (stock-out or near stock-out). In addition, separate coaching sessions were conducted with smaller groups of CHWs needing additional help. Finally, given significant malaria supply chain challenges at multiple levels of the health system, the study team worked closely with the district, regional, and national bodies responsible for malaria supply management in addition to providing supply chain support at the community level (in both arms) and additional storage capacity. CHWs in both arms were provided a small monetary incentive for their participation in the study, amounting to about 15 USD per CHW every 6 months. More details on health system strengthening support in both arms during age-expanded mCCM are available in the Additional file 1 : Table S2.

Data collection

Survey data.

Two cross-sectional surveys representative of the study area population were conducted prior to (baseline) and after (endline) implementation of the age-expanded mCCM intervention. A random sample of 1680 households without replacement was selected using a two-stage cluster sampling scheme. Prior to the baseline survey, the study area was mapped onto a spatial grid with 2 × 2-km (km) tiles, and two tiles were randomly selected within each health center catchment to serve as enumeration areas (EAs). Sixty EAs were selected, two per health center. Structures mapped through satellite imagery prior to fieldwork were visited by the enumeration team to determine which structures represented inhabited households, and simple random selection was used to select 28 households from each EA. The same EAs were used in both the baseline and endline surveys; baseline and endline sampling of households within each EA were done independently. More details on the study survey design are available at [ 25 ].

The baseline cross-sectional survey was conducted between October and December 2019. Interviews were conducted with an eligible household respondent (18 years or older and usual resident of the household) of sampled households. Data collected included a listing of household members; basic socio-economic and demographic information; history of illness in the previous 2 weeks among all household members; care-seeking behaviors, diagnosis, and treatment received for common illnesses (including fever, cough, and diarrhea) and associated costs among all household members; and perceptions of treatment from CHWs and health facilities. In addition, a capillary blood specimen was collected from children aged 2 months to 14 years by finger prick. Blood specimens were used to perform a malaria RDT at the site of collection. Children with a positive RDT were treated with artesunate-amodiaquine and paracetamol. Adults provided written informed consent for the household interview. For the capillary blood collection, parents or guardians provided written consent for children under 15 years of age, and children 7–14 years also provided written assent.

The endline survey was conducted between October and December 2021 in the same EAs. Twenty-eight households were sampled from the baseline sampling frame, and a list of ten replacement households was also generated to account for selected households that had moved since the baseline listing. Households refusing to participate or those absent during three attempted visits by survey teams were not replaced. All other protocols for data collection were the same as during baseline surveys. In addition to the cross-sectional surveys, qualitative data collection was conducted at the endline to gain in-depth knowledge on the acceptability of mCCM, as well as knowledge, attitudes, and practices towards malaria in the study area. Qualitative data and results are not included here.

Health system information

Consultation data at the CHW and health center levels were collected from January 2019 to December 2021, including the number of consultations, patients with fever, RDTs done, RDT-confirmed malaria cases, and ACT treatments delivered per month for each fokontany . At the CHW level, these data were retrieved from CHW registers and aggregated monthly. At health facilities, patient-level data were retrieved retrospectively from each health facility register prior to study start, and prospectively every month. Registers were photographed and data were entered into a patient-level, de-identified database. Health center data included new visits only and key information abstracted included demographics, patient village or fokontany of residence, illness, malaria diagnosis, and treatment. Overall, 8576 months of CHW data out of 9,036 expected (95.0%), and 1055 months of health center data out of 1080 expected (97.7%) were collected. Population data for each fokontany were obtained from the Ministry of Public Health and were calculated by applying a constant population growth estimate of 2.7% per year to data collected in the 2018 national census [ 23 ]. Using the total population of each fokontany , the populations of different age groups were estimated using population structure in our household surveys, where 22.7% were children 0–5 years, 26.1% were children 6–13 years, and 51.2% were individuals 14 + years old.

To estimate the average distance of a fokontany’s population to the nearest health center, we built on work developed by Ihantamalala et al. [ 26 ]. Briefly, all footpaths, residential areas, and buildings in the district were mapped between July 2021 and October 2022 using very high-resolution satellite images available through OpenStreetMap (OSM), resulting in 174,675 buildings, 11,592 residential areas, 628 km of non-paved roads and 27,699 km of footpaths mapped. When mapping was completed, the Open Source Routing Machine (OSRM) engine was used to query OSM data and estimate the shortest path between each building in the district and the nearest health center. The aggregated health center distance for a fokontany was the average distance from all buildings in the fokontany .

Data analysis

Analysis of survey data.

Descriptive analyses of individual and household characteristics for the baseline and endline surveys were performed. To estimate the impact of age-expanded mCCM, the proportion of individuals who sought care at a public health provider among those with a fever in the previous 2 weeks, the proportion receiving an RDT, and the proportion of RDT-positive cases receiving an antimalarial treatment were estimated for the intervention and control areas. Difference-in-differences (DiD) analyses were conducted via multivariate logistic regressions to evaluate the impact of age-expanded mCCM while controlling for differences between study periods (endline vs. baseline) and between the two arms (intervention vs. control). Analyses were done by type of care accessed (health facility, CHW, or both), by reported travel time to a health facility (< 1 h, 1–2 h, > 2 h), and by age group (0–5 years, 6–13 years, 14 + years). These age groups were selected instead of the initially pre-specified groups (under 5 years, 5–14 years, 15 + years) to correspond to categories in CHW reports used in health system analyses (next section), which were based on age groups for ACT medications used in Madagascar. Sampling weights adjusting for unequal probabilities of selection were calculated for each household. All estimates used applicable design weights and survey commands available in the R package survey [ 27 ].

Analysis of routine health information system data

Data collected from health centers and CHWs included key indicators (e.g., numbers of consultations, fever cases, RDTs, RDT-confirmed malaria cases, and antimalarial treatments) and were aggregated by fokontany , month, and age group of patients. Together, health center and CHW datasets allowed us to obtain precise estimates of the spatio-temporal evolution of health-seeking behaviors, malaria diagnosis, and case management at the primary care level (health centers and CHWs).

The impact of the intervention on key indicators was modeled using interrupted time-series analyses, with fokontany as the unit of analysis. Negative binomial regressions were used in generalized additive mixed models, with a random intercept for the fokontany and the logarithm of the fokontany population as offset. Outcome variables included the number of consultations with febrile illness, RDTs done, and antimalarial treatments delivered, both at health center and CHW levels. For each model, the intervention impact was estimated by assessing both the level of change and the slope of change associated with it, controlling for differences between study arms (intervention vs. control) and periods (after vs. before the intervention began). The level of change is the interaction between study arms and periods and represents the average change associated with the intervention, equivalent to a difference-in-differences estimator. The slope of change is the interaction between the level of change and time and represents the change in intervention impact over time after accounting for its average impact. The interaction between the intervention level of change and the average distance from the fokontany to the nearest health center was studied to assess whether the impact was different for more remote populations. The analysis controlled for temporal trends in utilization rates during the study period, including linear (i.e., time since January 2019), seasonal ( sine function), and lagged (1-month lag) trends. It also controlled for the non-linear effect of distance from a fokontany to the nearest health center using a cubic regression spline. Consistent with survey analyses, healthcare facility, and CHW data consultations were first modeled together and then separately, and separate models were carried out for each age group. Supplementary analyses were carried out to assess the impact of the intervention on the rates of acute respiratory infections (ARI) and diarrhea cases among children under 5 years seen at the CHW level, as well as treatment rates. Moreover, in order to understand whether the COVID-19 pandemic was responsible for the increase in fever care-seeking cases, we assessed the evolution of malaria RDT positivity at both levels of care, assuming that an increase in COVID-19 fevers would result in a decrease in overall malaria RDT positivity during the 2020 and 2021 waves. All analyses were done using R software version 4.2.1 and time-series analyses were done using R package mgvc [ 28 ].

Population characteristics

The study population comprised over 350,000 people evenly distributed into the two study arms (Table  1 ). Children under 14 years represented half of the population, and nearly one in four people lived further than 5 km from the nearest health center. From January 2019 to December 2021, 462,215 consultations and 382,187 RDTs were done in the 30 health centers in the study area. Similar numbers (464,440 consultations and 370,267 RDTs) were done by the 502 CHWs. The numbers of RDTs done and ACTs administered were similar for health facilities in both arms but were higher for CHWs in the intervention arm. For populations living further than 5 km from a health center, the number of consultations at health facilities was substantially lower than at CHWs (Table  1 ).

During the baseline and endline household surveys, 1458 (86.8%) and 1631 (97.1%) households participated, respectively (Table  2 ). The study population had low levels of basic education, was primarily agricultural, and had largely low socio-economic levels (e.g., lacked electricity or toilets). Households were located over two times farther from health centers on average (over 1 h walking) than from CHWs (less than 30 min). The proportion of households with one or more members who sought care for any reason at the CHW increased during the study period (from 73.9 to 81.4%) and decreased at health centers (from 83.2 to 73.3%). Fever was the main reason for seeking care, but the proportion was much larger at the CHW level (baseline: 82.4%, endline: 91.8%) than at health centers (baseline: 52.1%, endline: 57.7%). Of 8,050 individuals of all ages listed at baseline and 9046 at endline, only 6.2% and 4.7% reported being ill in the previous 2 weeks, respectively. RDT prevalence of malaria in children under 15 years increased from 22.4 to 27.1% from baseline to endline (Table  2 ). Children 5–14 years had about twice the malaria prevalence as CU5 in both surveys but were less likely to report recent fever.

Impact of age-expanded mCCM

Rates of care-seeking for fever, malaria diagnosis, and treatment substantially increased across the study area after implementation of the intervention (Table  2 ). Of 717 individuals who reported a fever in the 2 weeks prior to the survey, the weighted average of care-seeking and malaria RDT diagnosis more than doubled in both arms from less than 25% at baseline to over 60% at endline (Table  2 and Fig.  2 A). Similarly, the percentage of ACT treatments provided by health facilities or CHWs among survey individuals who reported having an RDT + diagnosis doubled from 50% to nearly 100%. In the control arm, these improvements were driven equally by increases at the health center and at the CHW level, whereas in the intervention arm, they were mostly driven by increases at the CHW level (Fig.  2 A). Results from difference-in-difference analyses found that age-expanded mCCM was associated with an increase in malaria diagnoses at the CHW level and a decrease at the health center level, but none of these effects were significant (Table  3 ). Malaria prevalence slightly increased between baseline and endline, although the proportion of symptomatic malaria declined, especially in children 5–14 years old (Table  2 ).

Average changes in key malaria indicators before and after mCCM implementation in each study arm. A Results from household surveys, estimated among all individuals who reported a fever (for care-seeking and RDT diagnosis) or an RDT+ (for ACT) in the 2 weeks prior to the survey. B Results from health system information, estimated from monthly primary care consultations at health centers and CHWs among the total population in the study area. Results for both levels of care (top panels) in both analyses (survey, health system) represent the sum of percentages or rates from each level of care (health center and CHW level)

In analyses of health system data, which included information from the 926,655 primary care consultations occurring between January 2019 and December 2021, rates of fever care-seeking (consultations) and malaria diagnosis and treatment increased in both intervention and control arms, but these increases were smaller in the control arm (Fig.  2 B). For instance, the annual number of per capita RDTs performed in the intervention arm increased from 0.45 before the intervention to 1.16 after the intervention was implemented, and from 0.44 to 0.91 in the control arm. Similar to survey analyses, consultation increases in the intervention arm were driven by large increases at the CHW level. In contrast with survey analyses, increases at the health center level in the control arm were very small. Interrupted time-series analyses revealed that when considering both levels of care, age-expanded mCCM was not associated with a significant increase in malaria diagnoses for people of all ages across the intervention area (RR level  = 0.96; 95% CI 0.88–1.06), but was associated with a significant increase in malaria diagnosis for populations living further from health centers (RR km  = 1.08; 95% CI 1.06–1.09), particularly among individuals older than 5 years. Moreover, age-expanded mCCM was associated with a significant increase in malaria diagnosis at the CHW level both for the level of change (RR level  = 1.28; 95% CI 1.08–1.5) and the slope of change (RR slope  = 1.30; 95% CI 1.12–1.51).

When considering specific age groups, rates of malaria testing at both care levels increased particularly for children 0–5 years and 6–13 years, tripling in both arms according to survey analyses, while they doubled for individuals 14 + years (Fig.  3 A). About 50% of all children 0–5 and 6–13 years in the survey who reported a recent fever in the intervention arm were tested at the CHW level at endline, from levels around 10% at baseline, while individuals 14 + years experienced a modest increase of about 20 percentage points (Fig.  3 A). Analyses of health system data revealed that these improvements occurred immediately after intervention implementation and were sustained throughout the study period (Fig.  3 B). Malaria diagnosis for individuals older than 5 years also occurred before age-expanded mCCM and rates increased substantially at the CHW level in the control arm according to survey data (Fig.  3 A), even though age-expanded mCCM was not officially in place, and therefore, this was not reported in health system data (Fig.  3 B). None of the difference-in-difference results from survey data was significant for malaria diagnosis for specific age groups (Table  3 , Table S3). In contrast, results from interrupted time-series analyses (Table  4 ) revealed that age-expanded mCCM was associated with significant increases in the level of change for malaria diagnosis children 6–13 years (RR level  = 1.65; 95%CI 1.45–1.87) and for individuals 14 + years (RR level  = 1.46; 95%CI 1.3–1.63), although this effect decreased slightly over time (RR slope  = 0.88 and RR slope  = 0.87 per year, respectively). For CU5, large improvements were seen in both arms, but the improvement was larger in the control arm (Table  4 ), reflected in an RR level of 0.76 (95%CI 0.68–0.84) for age-expanded mCCM on the rates of malaria diagnosis in this age group. Similar results were observed in analyses of rates of fever consultations and ACT treatments (Additional file 1 : Table S4). The time-series models using health system data predicted well the spatio-temporal trends observed in the data and explained about 40–70% of the variance in the data (Additional file 1 : Figures S1–S2).

Changes in rates of malaria diagnosis (RDTs) by age group before and after mCCM implementation in each study arm. A Results from household surveys, comprising individuals who reported a fever in the 2 weeks prior to the survey. B Results from health system information, comprising monthly primary care consultations at health centers and CHWs. Dotted vertical line indicates the beginning of HSS support and age-expanded mCCM. Equivalent figures for fever care-seeking and malaria treatments are available in the Additional file 1

Analyses of geographic inequalities revealed that populations living closer to a health center had higher overall rates of malaria diagnosis (Fig.  4 ). There was an exponential distance decay in the rates of malaria diagnosis at the health center level, which was more pronounced in the intervention arm and which was exacerbated after intervention implementation. In contrast, rates of malaria diagnosis by CHWs, which were low in both arms pre-intervention, increased for all populations regardless of their distance to a health center (Fig.  4 ). The effect was larger in the intervention arm, where malaria diagnosis reached an average of nearly 1 RDT per person per year for nearly all distance groups, versus less than 0.5 RDT per person per year in the control arm (Fig.  4 B). Results from interrupted time-series analyses (Table  4 ) revealed that the intervention impact was significantly larger overall for every additional km that populations lived from the health center (RR km  = 1.08; 95% CI 1.06–1.09), and this effect was particularly high for children 6–13 years (RR km  = 1.21; 95% CI 1.19–1.23) and individuals 14 + years (RR km  = 1.18; 95% CI 1.16–1.19).

Changes in rates of malaria diagnosis (RDTs) by population distance to health centers before and after mCCM implementation in each study arm. A Results from household surveys, comprising individuals who declared being ill in the previous 2 weeks and reported travel time to the nearest health center. B Results from health system information, comprising monthly primary care consultations at health centers and CHWs and estimated distance to the nearest health center via OSRM. Each dot represents the average of one fokontany , with solid lines representing the fitted smooth from a general additive model and its 95% confidence intervals (gray area). Note that y -axis scales are different. Equivalent figures for fever care-seeking and malaria treatments are available in the Additional file 1

The dramatic increases in the rates of care-seeking for fever observed during the study period seemed unrelated to the COVID-19 pandemic. We observed that there was a sudden and sustained increase in care-seeking at the community level (as well as in malaria RDTs done and treatments given) coinciding with the beginning of intervention implementation in November 2020 (Fig.  3 , Additional file 1 : Figures S3–S5), while the first COVID-19 waves in Madagascar occurred in July–August 2020 and in April–May 2021. Moreover, malaria positivity rates remained fairly stable over the whole time series and even increased after 2019 both at health facilities and at the community level (Additional file 1 : Figure S13).

Rates of ARI and diarrhea cases seen at the CHW level among CU5 increased in both arms following the intervention, as well as rates of antibiotic treatments given for ARI and oral rehydration salts given for diarrhea (Additional file 1 : Figure S7 and Table S6). However, these increases were significantly smaller in the intervention arm than in the control arm (Table S6). Analysis of stock data gathered from CHWs during the study period revealed that stocks of key malaria commodities increased at both health center and CHW levels, and stock-outs reduced during the intervention period (Additional file 1 : Figures S8–S12).

This randomized trial in rural Madagascar assessed how expanding mCCM to all ages impacts access to malaria diagnosis and treatment. Our results demonstrate that age-expanded mCCM led to significant increases in rates of care-seeking for fever, malaria diagnosis, and treatment for individuals over 5 years. The impact of age-expanded mCCM was larger for remote populations, effectively reducing geographic inequalities in the study area. Substantial increases were also observed in the control arm following the CHW program and supply chain enhancements that were done in support of the trial. The increases in fever care-seeking observed did not seem associated with the COVID-19 pandemic. Thus, while expanding mCCM to all ages could facilitate universal access to malaria diagnosis and treatment, strengthening current iCCM programs and malaria supply chains could achieve significant improvements in access to malaria care even in the absence of age-expanded mCCM.

Our study fills a critical gap in the evidence for expanding the role of CHWs in the provision of uncomplicated malaria care to individuals over 5 years. Although retrospective observational evidence suggests that in Rwanda age expansion of mCCM improved access to malaria diagnosis and treatment [ 17 ], most countries with high malaria burdens have not yet adopted this approach, which could be due to concerns about feasibility, limited resources, acceptability, and/or impact. In our trial, age-expanded mCCM resulted in an immediate and sustained uptake of this intervention by individuals of all ages, resulting in over 85,000 RDTs done and 60,000 ACT treatments provided for individuals older than 5 years of age at the community level during the 14-month implementation period, equivalent to 1.2 additional RDTs done by CHWs per workday. Overall, annual rates per capita roughly tripled in the intervention arm for RDTs done (from 0.41 to 1.16) and for ACTs given (from 0.21 to 0.77), an increase comparable to that observed in a recent study of proactive (home-based) malaria CCM in south-eastern Madagascar [ 16 ]. Survey results revealed that CHW diagnosis and treatment of older ages for fever was already taking place before the intervention started, and this practice increased in the control arm following implementation (Fig.  3 ). This suggests there is an underlying demand for age-expanded mCCM, especially in remote populations (Fig.  4 ). This could have limited the impact we observed with age-expanded mCCM, which was smaller than the impact associated with strengthening the CHW and supply chain systems in both arms and was not statistically significant in survey analyses. Despite this, analyses of health system data show that age-expanded mCCM was independently associated with an overall increase of about 50% in the rates of malaria diagnosis and treatment for individuals over 5 years (RR level  = 1.65 for individuals 6–13 years and RR level  = 1.46 for individuals 14 + years; Table  4 ). The decrease in symptomatic parasitemia seen between the baseline and endline surveys might be due to increased rates of care-seeking for febrile illness among older children.

The goal of community health programs is to increase access to quality care for populations who live far from health centers. Health system data revealed an exponential decrease in health center utilization the farther people lived from a health center. However, CHW utilization remained stable or even increased with populations’ distance to health centers because the CHWs were embedded in their communities (Fig.  4 ). As a result, age-expanded mCCM was associated with an additional relative increase of about 20% in rates of malaria diagnosis among individuals older than 5 years for every extra kilometer that they had to travel to the nearest health center (Table  4 ). These results are consistent with a previous study in rural Madagascar, which showed that community health programs largely compensated for the distance decay in health center utilization and reduced geographic inequalities in access to primary health care [ 29 ]. Using an ingredients-based costing approach to evaluate the budgetary impact of implementing the age-expanded mCCM program in Farafangana district from a health system perspective (Additional file 2 : Table S7), we estimated the total cost of running the expanded program at $794,270 per year in the district’s study area, which translates to approximately $2.55 per suspected case of uncomplicated malaria diagnosed and treated in the community (Additional file 2 : Table S8). Drugs and consumables accounted for 94% of the cost, and the estimate included initial costs of training and sensitization, as well as capital and supervision costs of the strengthened system (e.g., purchase of a vehicle and motorcycles) but not research-related costs. This represents less than half the cost of outpatient care of uncomplicated malaria cases at health facilities estimated in other settings [ 30 ].

The largest observed impact on care-seeking and malaria case management in our study occurred in both arms and was attributed to strengthening community health systems in a setting with low baseline access to care. Prior to the mCCM study, limited stocks of malaria supplies were distributed at the community level, which resulted in frequent stock-outs (Additional file 1 : Figure S12). By providing strong support to the malaria supply chain during the intervention (at national, district, and community levels; Additional file 1 : Table S2), monetary incentives to CHWs, and widespread sensitization on the availability of free malaria care, our study may have simultaneously increased demand while allowing CHWs to provide more services given increased supplies. For instance, the proportion of people who paid for malaria care among those who sought care from a CHW decreased from 93 to 60% (Additional file 1 : Table S5). In addition, qualitative research (data not shown) indicated that local populations began to appreciate that malaria could affect individuals over 5 years of age, and communities put pressure on CHWs and health center staff to conduct RDTs upon consultation. As a result of these mCCM implementation strategies, rates of malaria diagnosis for individuals of all ages more than doubled according to health system data (RR = 2.3), and this effect was even larger (OR = 8.5) in survey data. Improvements in malaria care at the CHW level did not result in a worsening of care for acute respiratory infections or diarrhea among children under 5 (both of which are part of standard iCCM), although the increases seen in the rates of diagnosis and treatment for these two diseases after the intervention was implemented were smaller in the intervention arm than in the control arm (Additional file 1 : Figure S7 and Table S6).

Our study had several limitations. First, we powered the household survey assuming a 15% prevalence of reported fever in the previous 2 weeks, in accordance with previous studies in south-eastern Madagascar [ 31 ], but reported fever was much lower at under 5% in both baseline and endline surveys. This resulted in very large uncertainty in our estimates and no statistically significant impact was observed for the age-expanded mCCM in survey analyses. However, survey results were consistent with those observed in our analyses of nearly one million primary care consultations at health centers and CHWs (Figs.  2 , 3 , and 4 ), which found the impact of age-expanded mCCM to be statistically significant (Table  4 ). Second, the intervention was initially planned to be implemented for nearly 2 years, but the COVID-19 epidemic shortened the duration of intervention to 14 months. This could have affected our ability to detect medium-term changes in intervention uptake over time. Moreover, the COVID-19 pandemic could have resulted in an increase number of non-malaria febrile illness and consultation rates. However, consultation rates remained stable during the first 8 months of the Madagascar COVID-19 epidemic and only increased upon beginning the intervention in November 2020 (Fig.  3 ), which suggests the pandemic had little effect on the results observed. Moreover, malaria positivity rates remained stable throughout the study period (Additional file 1 : Figure S13). Third, we strengthened the malaria supply chain to limit stock-outs (Additional file 1 : Table S2) during study implementation, since this is known to be an obstacle for delivery of mCCM. This, among other health system strengthening activities, had a larger effect than anticipated, resulting in a doubling in the rates of per-capita fever cases presenting for care and RDTs done in the control arm (Fig.  2 B). Although this effect is accounted for in our statistical analyses, it is unclear how a setting of frequent stock-outs and lack of external support to community health programs would influence the impact of age-expanded mCCM.

Our results suggest that an age-expanded mCCM can have a positive impact on access of older individuals to malaria diagnosis and treatment, especially for children 6–13 years of age and for populations living far from health facilities. Moreover, simultaneously strengthening community health activities and supply chains for malaria in rural settings where baseline access to iCCM is low can lead to substantial improvements even in the absence of age-expanded mCCM. A national scale-up of age-expanded mCCM is underway in Madagascar following the results from this pilot study, and a second randomized trial is being conducted in Malawi. Together, these can inform community health policies for malaria control in other sub-Saharan African countries.

Availability of data and materials

Data are available upon request to the address [email protected].

Abbreviations

Artemisinin-based combination therapy

Acute respiratory infection

Community health worker

Confidence interval

Children under 5 years

Enumeration area

Integrated community case management

Malaria community case management

Madagascar Ministry of Public Health

Non-governmental organization

National Malaria Control Program

OpenStreetMap

President’s Malaria Initiative

Proactive community case management

Rapid diagnostic test

Sub-Saharan Africa

United States Agency for International Development

World Health Organization

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Acknowledgements

The authors acknowledge the contributions and support of Laurence Baril, Daouda Kassie, Agathe Legrand, and Nicole Prada in the initial stages of the study. They are grateful to the field staff at IPM and Inter Aide in Farafangana for their support with field activities. Thanks are due to the Madagascar Ministry of Health, at the district, regional, and central levels, for their continuous support and valuable insights. The authors also thank all data collectors involved in the surveys. Finally, the authors extend a particular acknowledgement to the CHWs of Farafangana for their study efforts and their ongoing care in the communities they serve, and to the community leaders for their support.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention, PMI, or IPM.

This work was supported by the United States Agency for International Development (USAID) Research, Innovation, Surveillance and Evaluation (RISE) Program Cooperative Agreement no. 72068719CA00001. Financial support for this study was provided by the US President’s Malaria Initiative (US PMI). Employees of the sponsor worked with the investigators to prepare the study protocol, follow-up study implementation, statistical analyses, interpretation, and writing of the manuscript but the work was carried out by IPM. USAID and US PMI teams were permitted to review the manuscript and suggest changes, but the final decision on content was exclusively retained by the authors.

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Andres Garchitorena

Unité d’épidémiologie et de recherche clinique, Institut Pasteur de Madagascar, Antananarivo, Madagascar

Andres Garchitorena, Aina Harimanana, Judickaelle Irinantenaina, Hobisoa Léa Razanadranaivo, Tsinjo Fehizoro Rasoanaivo, Reziky Tiandraza Mangahasimbola & Masiarivony Ravaoarimanga

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Contributions

Conceived and designed the study: AG, AH, JI, JG, LCS. Coordinated data collection and study implementation: AG, AH, JI, HLR, TFR, LCS. Contributed to data collection/management: AG, AH, JI, HLR, TFR, RTM, MR. Performed statistical analyses: AG, HLR, WO, LCS. Wrote the initial draft of the manuscript: AG, LS. Revised the manuscript and accepted it in its final form: AG, AH, JI, HLR, TFR, DS, JG, RTM, MR, AVR, VR, OR, LYR, NR, MA, JP, AM, WO, CMD, LK, LCS. All authors read and approved the final manuscript, and agree to be accountable for all aspects of the accuracy and integrity of the work.

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This study was approved by the Madagascar National Ethics Committee for Biomedical Research (authorization no. 59-MSANP/SG/AGMED/CNPV/CERBM, amendment no. 95-MSANP/SG/AGMED/CNPV/CERBM) and by the Centers for Disease Control and Prevention’s institutional review board (CDC Protocol no. 7230). Consort 2010 checklist is available as additional file linked to this article (Additional file 3 ). The trial was registered at PACTR (#PACTR202001907367187). Adult participants provided written informed consent for the household interview during baseline and end line surveys. Parents or guardians provided written consent for children under 15 years of age for the capillary blood collection during surveys, and children 7–14 years also provided written assent.

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Supplementary Information

12916_2024_3441_moesm1_esm.docx.

Additional file 1: Table S1. Details on primary and secondary outcomes used to evaluate the impact of age-expanded mCCM. Table S2. Health system strengthening activities and solutions implemented in both arms during mCCM expansion period. Table S3. Impact of mCCM expansion to all ages on the proportion of febrile individuals seeking care, and the proportion of RDT+ individuals receiving an ACT. Table S4. Impact of mCCM expansion to all ages on the number of febrile individuals seeking care, and the number of ACTs delivered. Table S5. Reported cost of malaria care at different levels of care for individuals who sought care. Table S6. Impact of mCCM expansion to all ages on the number of children under 5 years seeking care for diarrhea and pneumonia from CHWs. Fig S1. Comparison of observed temporal utilization patterns and multivariate model predictions. Fig S2. Comparison of observed geographic utilization patterns and multivariate model predictions. Fig S3. Changes in rates of fever care seeking by age group before and after mCCM implementation in each study arm. Fig S4. Changes in rates of fever care seeking by population distance to health centers before and after mCCM implementation in each study arm. Fig S5. Changes in rates of ACT treatments by age group before and after mCCM implementation in each study arm. Fig S6. Changes in rates of ACT treatments by population distance to health centers before and after mCCM implementation in each study arm. Fig S7. Changes in rates of ARI and diarrhea case management at community level before and after mCCM implementation in each study arm. Fig S8. RDT stocks at health facility level, before and after mCCM implementation. Fig S9. ACT stocks at health facility level, before and after mCCM implementation. Fig S10. RDT stocks at CHW level, before and after mCCM implementation. Fig S11. ACT stocks at CHW level, before and after mCCM implementation. Fig S12. Monthly stockout days at CHW level for ACTs for children <5 years, before and after mCCM implementation. Fig S13. Evolution of RDT positivity over time in Farafangana District, 2019–2021.

12916_2024_3441_MOESM2_ESM.docx

Additional file 2: Supplementary analyses on intervention costing. Table S7. Data Sources for the different categories included in the costing analysis. Table S8. Average costs of diagnosis and treatment of suspected cases of uncomplicated malaria at the community level.

Additional file 3. Consort 2010 checklist.

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Garchitorena, A., Harimanana, A., Irinantenaina, J. et al. Expanding community case management of malaria to all ages can improve universal access to malaria diagnosis and treatment: results from a cluster randomized trial in Madagascar. BMC Med 22 , 231 (2024). https://doi.org/10.1186/s12916-024-03441-9

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Malaria surveillance, outbreak investigation, response and its determinant factors in Waghemra Zone, Northeast Ethiopia: unmatched case–control study

• Habtu Debash 1 ,
• Marye Nigatie 3 ,
• Habtye Bisetegn 1 ,
• Daniel Getacher Feleke 4 ,
• Gebru Tesfaw 2 ,
• Askale Amha 5 ,
• Megbaru Alemu Abate 6 , 7 &
• Alemu Gedefie 1  

Scientific Reports volume  13 , Article number:  9938 ( 2023 ) Cite this article

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Malaria is a major global public health concern, with around half of the world's population at risk of infection. It is one of the most common epidemic-prone diseases, resulting in on-going epidemics and significant public health problems. On September 12, 2022, Waghemra Zone malaria monitoring data revealed that the district was suffering an unusually high number of malaria cases. Therefore, the aim of this study was to assess the occurrence of malaria outbreaks and investigate contracting factors in Waghemra Zone, Northeast Ethiopia. A community-based case–control study with a 1:1 ratio was employed at Waghemra Zone from September 14 to November 27, 2022. A total of 260 individuals (130 cases and 130 controls) were included in the study. A structured questionnaire was used to collect the data. Malaria cases were confirmed by either microscopy or malaria rapid diagnostic tests. The magnitude of the outbreak was described by place, person, and time. A multivariable logistic regression analysis was conducted to identify malaria risk factors. A total of 13,136 confirmed cases of malaria were detected in the Waghemra zone, with an overall attack rate of 26.5 per 1000 and slide positivity rate was 43.0%. The predominant species was Plasmodium falciparum accounting for 66.1%. Children under five years old (AOR = 5.1; 95% CI 2.6–23.0), the presence of artificial water-holding bodies (AOR: 2.7; 95% CI 1.340–5.420), intermittent rivers closer to the living house (AOR = 4.9; 95% CI 2.51–9.62), sleeping outside a home (AOR = 4.9; 95% CI 2.51–9.62), and a lack of knowledge about malaria transmission and prevention (AOR: 9.7; 95% CI 4.459–20.930) were factors associated with malaria contraction. The overall attack rate for malaria during this outbreak was high. Children less than five years, the presence of mosquito breeding sites, staying outdoors overnight, and a lack of knowledge on malaria transmission and prevention were predictors of malaria. Early management of local vector breeding places, as well as adequate health education on malaria transmission and prevention methods, should be provided to the community to prevent such outbreaks in the future.

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Introduction.

Malaria is a widespread and debilitating tropical disease caused by Plasmodium species and transmitted through the bites of infected female Anopheles mosquitoes 1 . According to the World Health Organization's (WHO) 2021 malaria report, the WHO African regions continue to suffer the greatest burden of malaria. The African Region accounted for 95% of all malaria cases (228 million) and 96% of all malaria deaths (602 000) in 2020, with children under the age of five accounting for 80% of all malaria deaths in the region. Malaria services were hampered beginning in 2020 because of the Covid-19 epidemic, adding to the region's malaria load 2 .

Malaria is a major public health issue in Ethiopia, where it is estimated that 68% of the population resides 3 . Despite widespread deployment of malaria prevention strategies such as early diagnosis and treatment, indoor residual spraying, and mass distribution campaigns of long-lasting insecticide-treated bed nets 4 , Ethiopia has the highest incidence of malaria cases. Malaria is mostly an endemic disease in the country, and outbreaks sometimes happen. Its transmissions peak between September and December, following the main rainy season, and between June and August 3 .

Recurrent outbreaks and epidemics are linked to cyclical weather fluctuations in the country, which lead to enhanced vector survival. Other triggering factors include exceptional local weather events and activities that result in environmental alteration, increasing vector populations, and increasing population vulnerability to famine, starvation, and conflict 3 , 5 . More than 542,000 people have been displaced as a result of internal conflict in Amhara region Ethiopia. The Waghemra zone has been severely affected by this internal conflict 6 . The conflict has led to the deterioration of health services, the interruption of anti-malarial treatments, and the movement of people, which has resulted in the failure of efforts to keep malaria under control and the likelihood of an outbreak 7 .

The Waghemra zone is one of the most malaria-prevalent areas in the Amhara region of northeast Ethiopia. On September 12, 2022, malaria monitoring data obtained from the Zone Health Office revealed that the districts were experiencing an exceptionally high number of malaria cases. In WHO epidemiologic week 36 of 2022, a total of 190 malaria cases were registered, compared to only 122 cases in the same epidemiologic week during the threshold period (2016–2020). On September 14, 2022, a rapid response team was dispatched to the affected districts to confirm the existence of the outbreak, identify risk factors, and aid in intervention actions.

Understanding the causes of outbreaks in these areas allows for early case management, identification of variables that maintain the disease, and the design of more effective preventative and control methods to facilitate malaria elimination by 2030. As a result, the goal of this study was to confirm the occurrence of the outbreak, identify gaps and risk factors that contributed to the outbreak's existence, and provide appropriate public health intervention for the outbreak in the Waghemra zone.

Materials and methods

Waghemra Zone is one of eleven zones in Amhara region of Ethiopia. The Waghemra zone is defined by the following latitude and longitude coordinates: 12° 45′ 54" N, 38° 50′ 34.8"E and has an elevation of 1498 m. In terms of health care, it has 136 health posts, 34 health centers, one general hospital, and two primary hospitals. This zone is divided into eight districts with a total population of 536,129 people. Data was collected from Ziquala, Sahala, Abergelie, Dehana, Sekota Zuria, Sekota Town and Gazgibla districts. However, due to the presence of war during data collection in the Tsagbji district and some kebeles in the Abergele district were excluded. The outbreak occurs in all districts, but the severity varies. The area's average yearly temperature and rainfall are 26 °C and 786 mm, respectively. The climate and topography of the study areas are conducive to Anopheles mosquito breeding, and malaria transmission is prevalent.

Study design and period

Community based unmatched case–control study was conducted from September 14 to November 27, 2022.

Source population, study subject and variables

People living in the Amhara region's Waghemra zone who are at risk of malaria are the source population. And the specific study subjects for these cases were febrile patients who tested positive for malaria parasites by either Rapid Diagnostic test (RDT) or a microscope. Controls, on the other hand, were classified as having no signs and symptoms of acute febrile illness one month before data collection. A non-febrile, apparently healthy person living in the same village as the active case patient from September 14 to November 27, 2022, was studied as a control subject. Controls were selected regardless of their age, gender, educational status, physiological status, and socio-economic status. The independent variables were socio-demographic and economic characteristics, behavioral factors like Insecticide-Treated Nets (ITN) use, Indoor Residual Spray (IRS), sleeping area at night and environmental factors.

Descriptive and analytical epidemiology

Confirm the diagnosis and verify the existence of the outbreak.

Malaria data from the last six years (2016–2021) were analyzed at the Waghemra zone health office to determine the epidemic threshold level. However, because of the inadequacy of the most recent year's (2021) data, the previous five years' (2016–2020) weekly malaria case reports were utilized. Then epidemic threshold level was defined by comparing weekly data with similar weeks in 2022, and an epidemic curve was produced. A rise beyond the weekly threshold was recorded, indicating an outbreak. On September 12, 2022 (week 36), an early warning alarm was received from the Waghemra zone. The Zonal public health emergency management case team decided to investigate or confirm the outbreak and intervene after receiving a request from the zone health office and analyzing regular surveillance data. A number of malaria cases have been recorded; the slide positivity rate and attack rate were calculated as the number of confirmed malaria cases per 100 and 1000 population, respectively.

Sample size determination and sampling technique

The sample size was calculated using Epi-Info version 7.2.1 by taking an 80% power,, an odds ratio of 3.32 for the presence of artificial water holding bodies near the home, the percentage of exposed controls of 21.3% 8 , and the case-to-control ratio of 1:1. The total sample size was 118. Considering a design effect of 2 and 10% non-response rate, the final sample size became 260, with 130 cases and 130 controls .

A multi-stage random sampling method was used to enrol the study participants. Waghemra zone has eight districts, and of them, three (Ziquala, Sahala, and Abergelie) were purposefully selected. In each district, two kebeles were selected randomly using a lottery method. Accordingly, Tsitsika and Netsawork, Silazge and Meharit, and Saka and Debre-brihan kebeles were selected from Ziquala, Sahala, and Abergele districts, respectively. The total households for each village were available at their nearest health center or health post, which is stored as a family card folder. Based on this, the total sample size was proportionally allocated as 60, 43, 52, 33, 47, and 25 to Tsitsika, Netsawork, Silazge, Meharit, Saka, and Debre-brihan kebeles, respectively. All cases and controls were selected from the same community or neighbour for the controls at the same time. The lottery method was applied to select individual participants in the selected household.

Data collection

Six health extension workers and six laboratory technologists collected data using a structured questionnaire under the supervision of the principal investigator and the zonal public health emergency management case team. The questionnaire utilized in the study was prepared by reviewing the literatures 7 , 8 , 9 . Data collectors and supervisors received one day of training to ensure data quality. A review of weekly Integrated Disease Surveillance and Response (IDSR) reports at various levels (district health office and health facilities) was done. For adults, selected cases and controls were interviewed directly; for children, parents were involved in the interview process. But each participant gave blood for malaria diagnosis.

Laboratory methods

At Waghemra Zone health facilities, laboratory technologists utilized a light microscope to detect malaria parasites. During power outages, RDTs were used in healthcare facilities. Furthermore, at time of outbreak investigation, health extension workers and surveillance teams employed RDTs to identify confirmed malaria cases at health posts and the community level.

Environmental and vector control assessment

The environmental impact, as well as the ownership and use of ITNs were assessed. Selected case patients and controls were asked questions regarding the existence of mosquito breeding places in and around their compound. The potential breeding sites of Anopheles mosquitoes, such as uncovered plastic water containers, old tires, stagnant water, and broken glasses in the home or outside the home were evaluated. Furthermore, we assessed for the presence of anopheles’ larvae in stagnant water.

Data processing and analysis

Data were entered into Epi-Info 7.2.0.1 and analyzed using Statistical Package for Social Science version 26 (SPSS-26). The outbreak's scope was described in terms of person, place and time. The significance of risk factors for the outbreak was determined using logistic regression. Variables with p-value < 0.25 in bivariate analysis were entered in multiple logistic regression analysis to examine the effect of an independent variables on the outcome variable. The association between dependent and independent variables was determined using Odds Ratio (OR) of 95% Confidence Interval (CI) at p-value less than 0.05 was regarded as statistically significant.

Ethical consideration

Ethical clearance was obtained from the ethical review committee of College of Medicine and Health Sciences, Wollo University on the date 16/8/2022 with a protocol number of CMHS/201/2022. Supportive letters were also obtained from the Waghemra Zone Health Office. Written informed consent and assent were obtained from participants or caregivers. Positive cases were treated according to national malaria guidelines. The information obtained was made anonymous and de-identified prior to analysis to ensure confidentiality. The study was also conducted in accordance with the Helsinki Declaration.

Socio demographic characteristics

During the study period, 260 eligible study participants were selected and interviewed, making the response rate 100. The study included 155(59.6%) males and 105 (40.4%) females. The majority of the participants were between the ages of 15 and 45. In terms of occupation and education, 124 (47.7%) were farmers, while 227 (68.8%) were illiterate (Table 1 ).

Descriptive result

Description of cases by person and place.

During the outbreak investigation period from WHO weeks 29 to 47, a total of 13,136 confirmed cases of malaria from the Waghemra zone were detected. Total slide positivity rate (TPR) and attack rate (AR) were 43.0% and 26.5%, respectively. From all malaria confirmed cases, the most affected age group was > 15 years (65.6%), followed by 5–14 years (24.0%), and below 5 years (10.4%). The districts with the largest proportions of malaria-confirmed patients were Ziquala, Sahala, and Abergele, with 37.9%, 37.2%, and 10.2%, respectively. On the other hand, the highest attack rate was observed in the Sahala, Ziquala, and Abergele districts, with rates of 172.2, 113.2, and 28.9, respectively. Plasmodium falciparum responsible for 8681 (66.1%) of the infections, while P. vivax responsible for 3875 (29.5%) (Table 2 ).

Description of cases by time

The Waghemra Zone Health Department was informed that the number of malaria cases had exceeded the threshold in the WHO epidemiologic week 36/2022. The number of malaria patients steadily increased and peaked in week 42. Then it steadily decreased from week 43 to week 47 but was not controlled till this investigation was completed (Fig.  1 ). The intervention began with mass diagnosis using RDT and microscopy, and the positive cases were treated with artemisinin-based combination therapy and chloroquine for infection with P. falciparum and P. vivax , respectively. Health education, environmental management, distribution of ITN and the use of Abet chemicals to larvicide stagnant water were also applied.

Malaria outbreak line graph by WHO epidemiologic week in Waghemra zone, Northeast Ethiopia, 2022.

Analytic results

Factors associated with malaria outbreaks.

In a multivariable analysis, children under the age of five were five times more likely than those over the age of 45 to contract malaria (Adjusted Odds ratio (AOR) = 5.1; 95% Confidence Interval (CI) 2.6–23.0). People who were living in households where artificial water-holding bodies were thus 2.7 times more at risk of getting malaria infection than their counterparts (AOR: 2.7; 95% CI 1.340–5.420). Similarly, the presence of intermittent rivers closes to the community within 1 km distance increased the likelihood of getting malaria than those far away from it (AOR: 9.4; 95% CI 4.8–18.0). Likewise, children who stayed outside at night had an almost five-fold greater risk of acquiring malaria compared to those who did not (AOR = 4.9; 95% CI 2.51–9.62). Furthermore, higher odds of malaria were noted among those who had no knowledge on malaria transmission, prevention and control mechanisms (AOR: 9.7; 95% CI 4.459–20.930) (Table 3 ).

Public health interventions

Early diagnosis and treatment.

During the investigation period, an active case detection was conducted using RDT or microscopy, as well as early case management in accordance with national malaria treatment standards 9 . Temporary diagnosis and treatment sites were established to control and prevent further transmission through early treatment.

Environmental assessment

There were many mosquito breeding sites detected in the districts, which could be the source of the outbreak. In most of houses, unnecessary weeds, fake water-holding containers, especially damaged gutters, unused cans, unused old ties and stagnant waters were observed. Environmental management such as filling, draining, and clearing were carried out in an area larger than 432,157 square meters in a selected Anopheles mosquito breeding site. The community was involved in both the opening of temporarily stagnant water and the administration of larvicide (abet insecticide) at the breeding location. In this environmental management a total of 8,654 people were participated.

Vector control activities

The zone fast response team assessed and provided vector control activities in the study area. In all households in the Waghemira zone, indoor residual spray chemicals were not sprayed due to conflict in the last year. The fast response team, sprayed anti-larval chemical (abate) on stagnant water with an approximate area of 432,157 square meters. Fifty homes from each affected kebeles were randomly selected and visited to look for new malaria cases and assess the use of insecticide-treated bed nets at night. Even though every household had at least one insecticide-treated bed net, only 42.6% of them hung it directly on the bedding, with the rest hanging it underneath the beds and elsewhere in the house Moreover, about 22.6% of the household nets were damaged. The response teams then distributed over 3100 ITNs to the community.

Health education and communication

Health professionals were mobilized and assigned to the affected village for an active case search and early case management in the community. In addition, health education was given to 15,890 people about the cause, transmission, prevention, and control of malaria. Communicating and discussing the trend of the malaria situation with health facilities, Woreda, and zone health departments, and there was also multi-sectorial integration for social mobilization and prevention of malaria.

Based on five years of epidemiological records of malaria cases, the study findings showed the presence of a malaria outbreak in the study area. The malaria outbreak investigation included WHO weeks 36 to 47. Overall, the outbreak decreased but was not controlled due to inadequate environmental and vector control interventions in affected areas. For the past year, there has been an internal conflict in the study area, which has resulted in the deterioration of the health system and the interruption of malarial prevention measures, which have kept malaria under control.

The national malaria prevention and control strategies recommend the application of the IRS at least once a year with 100% coverage and at least one ITN per two people in high malaria-risk areas 10 . Despite this fact, prior to the outbreak, IRS was not applied, early replacement of ITN was not done, and there were multiple mosquito breeding sites. Households that had been using the ITN for purposes other than their intended purpose were also observed. This could be due to poor monitoring of the communities after distributing the ITN. The districts were also inadequately prepared for the outbreak, leading to a shortage of resources. This negatively affected outbreak control and resulted in the outbreak taking longer to contain. A similar finding was reported in Binga district, Zimbabwe 11 .

The overall attack rate (AR) was 26.5 cases per 1000 population; this finding was higher than a study done in Argoba district, South Wello Zone (AR: 1.8) 12 , Laelay Adyabo district, Northern Ethiopia (AR: 12.1) 13 , and India (AR: 15.1) 14 . However, this finding was lower than a study done in the Abergelle district, North Ethiopia (AR: 33.1) 15 , Simada district, Northwest Ethiopia (AR: 200) 8 , Afar region, Ethiopia (AR: 36.7) 16 , Bolosso Sore district, Southern Ethiopia (AR: 36.4) 17 , BenaTsemay district, Southern Ethiopia (AR: 114) 18 , and Kole district, Uganda (AR = 68) 19 . This difference might be attributed to prevention and control efforts, community level of awareness, internal conflict, and area differences in the burden of malaria and duration of the disease.

The AR was highest in Sahala, Ziquala, and Abergele districts, with rates of 172.2, 113.2, and 28.9 per 1,000 populations, respectively. This might be due to the presence of multiple mosquito breeding sites near residents of these districts compared to the other districts. Moreover, these districts are extremely hot and low-land areas with a high malaria burden. This was in line with a study done in the Metema district and in the Amhara Regional State, Ethiopia 20 , 21 . This could be due to high temperatures in the area, which are conducive to mosquito development rates, biting rates, and parasite survival within the mosquito 22 .

The greatest number of malaria cases was found in patients above the age of 15 (8621 out of 13,136). This finding was in line with studies from Abergele district Northeast Ethiopia 23 , Ankasha district, North Ethiopia 9 , and BenaTsemay district, Southern Ethiopia 18 . This might be due to the fact that the majority of the adolescents were spending more time outdoors in this area for farming, livestock-keeping, and fishing activities that exposed them to mosquito bites. This implies that the regional health bureau needs to give more focus and extend medical services to people who are engaged in farming, livestock keeping, and fishing.

The predominant Plasmodium species detected in this study was P. falciparum (66.1%), followed by P. vivax (29.5%). This was in agreement with other previous studies done in Argoba district, Northeast Ethiopia 12 , and Abergele district, Northern Ethiopia 15 . However, it disagreed with the national malaria parasite distribution pattern of Ethiopia, which showed that P. falciparum and P. vivax accounted for 60 and 40% of the malaria cases in the country, respectively 24 . This variation could be due to the fact that this study was limited to a small malaria-endemic setting in the country, which could have caused the species prevalence to vary. In addition, P. falciparum is a common species in the lowlands.

Malaria outbreaks are frequently complicated and multi-factorial, including both natural and man-made causes 25 . This case–control study verified the occurrence of a malaria outbreak in the Waghemra zone. Age, the availability of artificial water-holding bodies, nearby stagnant water, sleeping outside overnight, and a lack of knowledge about malaria transmission and prevention all contributed to the epidemic's existence. As a result, children under the age of five were nearly five times more likely than individuals over the age of 45 to contract malaria. This finding was congruent with research undertaken in the Bena Tsemay district of southern Ethiopia 18 . Malaria immunity develops slowly after multiple infections, and it takes at least five years for children to establish immunity 26 .

Furthermore, people who live near artificial water-holding bodies and stagnant water were more likely to be exposed to the malaria parasite than their counterparts. A similar conclusion was reached in research conducted in Simada district, Northwest Ethiopia, which found a link between staying near such water sources and contracting malaria 8 . Stagnant water created by heavy rains provides an ideal breeding environment for mosquitoes and contributes to malaria epidemics 8 , 16 . Similarly, people who stayed outside at night were approximately five times more likely to be infected with malaria than those who did not. This finding was supported by a report from the Ziquala, Armachiho, and Dembia districts of the Amhara region in Ethiopia 27 , 28 , 29 . This could be explained by the exophagic-exophilic biting behaviours of mosquitoes 30 . Moreover, a lack of knowledge regarding malaria transmission and control was a risk factor for disease development. Malaria education is crucial for minimizing exposure to the disease and its negative health consequences 8 , 31 , 32 .

During the investigation period, active case searching, treatment and management were carried out in accordance with national malaria treatment guidelines. Aside from that, environmental management activities such as filing, draining and clearing temporarily stagnant water were done with community involvement. At the time of data collection period, larvicide (abet chemical) was sprayed on Anopheles mosquito breeding sites. Moreover, the malaria surveillance team provided health education on disease transmission and prevention, and distributed over 3100 ITN to the community. However, due to a scarcity of chemicals, indoor residual spraying of houses in impacted kebeles is now being delayed. This outbreak scenario exemplified the critical role of long-term environmental and vector control intervention through well-organized malaria strategies and programs in preventing and controlling malaria infections. Malaria control and elimination require cross-sectoral collaboration as well as close monitoring and assessment of prevention and control initiatives.

Conclusion and recommendations

Following a year of internal conflict, a malaria outbreak was confirmed in Waghemra Zone. The predominant Plasmodium species identified was P. falciparum , and the outbreak was linked to being under five age, the existence of vector-breeding areas, people staying outdoors overnight, and a lack of knowledge about malaria transmission and control. The response to the outbreak included early diagnosis and treatment, environmental change, vector control, and awareness raising, which resulted in a reduction but not complete control of the outbreak. To prevent future malaria outbreaks in the study area, we recommended that the Waghemira Zone health office, Amhara regional health bureau, and other concerned sectors implement the following malaria prevention and control techniques: Those include raising community knowledge about malaria, mobilizing to disrupt mosquito breeding areas, scheduling indoor residual spraying activities, and monitoring malaria case trends on a weekly basis.

Ethical approval and consent to participate

Ethical clearance was obtained from the ethical review committee of College of Medicine and Health Sciences, Wollo University on the date 16/8/2022 with a protocol number of CMHS/201/2022. Permission was obtained from Waghemra Zone Health Office and each district health office where the study was conducted. This study was conducted in accordance with the Declaration of Helsinki. After briefly describing the significance of the study, the participants or children’s parents or guardians signed informed written consent. Confidentiality of the data was maintained. Finally, participants who were infected with the Plasmodium parasite received antimalarial treatment according to the national malaria treatment guidelines.

Data availability

All relevant data are included in the published article.

Abbreviations

Attack rate

Confidence interval

Indoor residual spray

Insecticide-treated nets

Plasmodium falciparum

Plasmodium vivax

Rapid diagnostic test

Statistical Package for Social Sciences

Total slide positivity rate

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Acknowledgements

The authors thank the study participants, data collectors, Waghemra Zone Health Office. The authors would like to also thank district health offices, kebele leaders, health extension workers, health facility administrative and medical laboratory staffs for their support and unreserved cooperation in making this study to be a fruitful work.

The research project was not funded by any organization.

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Department of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

Habtu Debash, Habtye Bisetegn & Alemu Gedefie

Department of Internal Medicine, School of Medicine, Wollo University, Dessie, Ethiopia

Gebru Tesfaw

Department of Medical Laboratory Sciences, College of Health Sciences, Woldia University, Woldia, Ethiopia

Marye Nigatie

Department of Microbiology, Immunology and Parasitology, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

Daniel Getacher Feleke

Waghemra Zone Health Department, Sekota, Ethiopia

Askale Amha

Department of Medical Laboratory Sciences, College of Medicine and Health Sciences, Bahirdar University, Bahirdar, Ethiopia

Megbaru Alemu Abate

The University of Queensland, School of Public Health, Brisbane, Australia

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Habtu Debash, Marye Nigatie, Habtye Bisetegn and Daniel Getacher Feleke conceived and designed the study, prepared the proposal, supervised data collection, analyzed, and interpreted the data. Habtu Debash, Gebru Tesfaw, Askale Amha, Megbaru Alemu, and Alemu Gedefie had participated in data collection, data analysis, and interpretation of the result, collecting scientific literature, critical appraisal of articles for inclusion, analysis, and interpretation of the findings. Habtu Debash drafted and prepared the manuscript for publication. Habtye Bisetegn, Marye Nigatie, Daniel Getacher Feleke and Alemu Gedefie critically reviewed the manuscript. All the authors have read and approved the final version of the manuscript and agreed to be accountable for all aspects of the work.

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Debash, H., Nigatie, M., Bisetegn, H. et al. Malaria surveillance, outbreak investigation, response and its determinant factors in Waghemra Zone, Northeast Ethiopia: unmatched case–control study. Sci Rep 13 , 9938 (2023). https://doi.org/10.1038/s41598-023-36918-3

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DOI : https://doi.org/10.1038/s41598-023-36918-3

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An Imported Case of Severe Falciparum Malaria with Prolonged Hemolytic Anemia Clinically Mimicking a Coinfection with Babesiosis

Young ju na.

1 Department of Internal Medicine, Korea University Anam Hospital, Seoul 136-705, Korea.

Jong-Yil Chai

2 Department of Parasitology and Tropical Medicine, Seoul National University College of Medicine, Seoul 110-799, Korea.

Bong-Kwang Jung

Hyun jung lee, ji young song, sung hun park, ji seon choi.

3 Department of Laboratory Medicine, Korea University Anam Hospital, Seoul 136-705, Korea.

While imported falciparum malaria has been increasingly reported in recent years in Korea, clinicians have difficulties in making a clinical diagnosis as well as in having accessibility to effective anti-malarial agents. Here we describe an unusual case of imported falciparum malaria with severe hemolytic anemia lasting over 2 weeks, clinically mimicking a coinfection with babesiosis. A 48-year old Korean man was diagnosed with severe falciparum malaria in France after traveling to the Republic of Benin, West Africa. He received a 1-day course of intravenous artesunate and a 7-day course of Malarone (atovaquone/proguanil) with supportive hemodialysis. Coming back to Korea 5 days after discharge, he was readmitted due to recurrent fever, and further treated with Malarone for 3 days. Both the peripheral blood smears and PCR test were positive for Plasmodium falciparum . However, he had prolonged severe hemolytic anemia (Hb 5.6 g/dl). Therefore, 10 days after the hospitalization, Babesia was considered to be potentially coinfected. A 7-day course of Malarone and azithromycin was empirically started. He became afebrile within 3 days of this babesiosis treatment, and hemolytic anemia profiles began to improve at the completion of the treatment. He has remained stable since his discharge. Unexpectedly, the PCR assays failed to detect DNA of Babesia spp. from blood. In addition, during the retrospective review of the case, the artesunate-induced delayed hemolytic anemia was considered as an alternative cause of the unexplained hemolytic anemia.

INTRODUCTION

In Korea, the number of cases with resurgent indigenous vivax malaria has decreased to less than 500 cases per year, but imported malaria has been increasingly reported as of late, up to 46 cases per year [ 1 ]. The majority of the imported cases occurred after travel to malaria-endemic countries. Plasmodium falciparum and Plasmodium vivax are the 2 more common etiological agents, accounting for 43% and 39% of the cases, respectively [ 1 ]. Nevertheless, clinicians have difficulties in clinical diagnosis of imported malaria as well as having limited accessibility to effective anti-malarial drugs [ 2 ]. In particular, falciparum malaria is becoming multi-drug resistant and often shows clinical severity, resulting in mortality.

Babesiosis is a malaria-like acute febrile infectious disease caused by Babesia spp., a genus of protozoa found as parasites in red blood cells. Human babesiosis is a worldwide emerging zoonosis, requiring increased medical awareness. Imported human babesiosis has previously been reported in Korea, including a case mixed with falciparum malaria [ 3 ]. Although a peripheral blood smear using Giemsa stain has been widely used for a simple and rapid diagnosis of both babesiosis and malaria, it is sometimes difficult to distinguish clearly between Babesia spp. and malaria because of morphologic similarities, often requiring Babesia -specific PCR tests [ 4 ].

We experienced an interesting case of severe falciparum malaria which was initially treated with a full treatment dose of artesunate and Malarone (atovaquone/proguail); however, his condition became complicated with unexplained prolonged severe hemolytic anemia. On the basis of the clinical similarity of malaria and babesiosis, Malarone and azithromycin were given, with a resultant clinical improvement. However, the PCR assays on the early blood samples were positive only for P. falciparum and failed to detect Babesia species. We report here an unusual case of severe falciparum malaria complicated with unexplained prolonged hemolytic anemia, clinically mimicking a coinfection with babesiosis.

CASE REPORT

A 48-year-old Korean man was admitted to a hospital in France due to intermittent high fever for 2 weeks and a mental change for 1 day. Before coming to the hospital, he went on a business trip to the Republic of Benin in West Africa for 14 days. He exhibited a confused mental state and pulmonary edema. He was diagnosed with falciparum malaria and treated with a combination of intravenous artesunate for 1 day and oral Malarone for 7 days. His supportive treatment included blood transfusions and hemodialysis. After a 12-day hospitalization period, he was discharged with clinical improvement.

Five days after the discharge, he was admitted to our hospital in Korea because of recurrent high fever, jaundice, and abdominal discomfort. He was a businessman and his residence is in Seoul, Korea. He had no specific medical history or surgical operations except for the current attack of falciparum malaria. His family history was unremarkable. On admission, his vital signs were blood pressure 130/90 mmHg, pulse rate 106/min, body temperature 38℃ and respiration rate 20/min. He was alert, but acutely ill. He showed anemic conjunctiva and mild icteric sclera. Other findings were unremarkable except for mild splenomegaly and abdominal tenderness. The initial laboratory findings were as follows: Hb 8.0 g/dl, HCT 23.6%, WBC 4,600/mm 3 , platelet 116,000/mm 3 , PT 86%, ESR 22 mm/hr, CRP 32.4 mg/dl, BUN 17.5 mg/dl, creatinine 1.36 mg/dl, LDH 2,021 IU/L, Na 132 mmol/L, K 4.0 mmol/L, Cl 99 mmol/L, total protein 6.2 g/dl, albumin 3.1 g/dl, total/direct bilirubin 1.74/0.40 mg/dl, AST 55 IU/L, ALT 64 IU/L. In day 3 of his hospital stay, the PCR assay for P. falciparum was positive. A peripheral blood smear demonstrated normocytic normochromic anemia with anisocytosis, poikilocytosis with spherocytes (1-5/HPF), polychromasia, and nucleated RBCs (1/100 WBCs) with presence of a few protozoa of P. falciparum ( Fig. 1 ). The direct Coombs' test was positive; urinalysis showed blood (+2), proteinuria (+1), and hemoglobinuria was positive; serology was negative for HIV, HBsAg, and HCV, and positive for HBsAb. Cultures of blood, sputum, and urine samples were all negative; chest radiography was normal; abdominal CT scan demonstrated splenomegaly with multiple infarctions.

A peripheral blood smear showing a ring form of Plasmodium falciparum (arrow) at the first day of hospitalization. Wright-Giemsa stain, ×1,000.

From day 1 to day 3 of his hospitalization, he was additionally given Malarone (atovaquone/proguail 1,000 mg/400 mg once daily for 3 days) for falciparum malaria. However, a daily spiking fever as high as 40℃ persisted, and the laboratory findings related to hemolytic anemia showed Hb 5.8 g/dl, LDH 2,502 IU/L, plasma Hb 24.4 mg/dl, haptoglobin <5 mg/dl, RPI (reticulocyte production index) 1.0, and total/direct bilirubin 2.78/0.63 mg/dl. FANA was checked; cytoskeletal pattern 1:40 and nucleolar pattern 1:320. ANCA and anti-ENA profiles were all negative. Blood transfusion and steroids were given for severe hemolytic anemia. The high fever subsided with steroid administration for 6 days (1 mg/kg for the first day and then 0.6 mg/kg on the following 5 days), but the hemolytic anemia profiles exhibited little change.

On day 10 of hospitalization, babesiosis was included as an additional suspected diagnosis, although he denied a tick bite during his stay in Benin. For the suspected babesiosis, a 7-day course of Malarone (750 mg/day) and azithromycin (500 mg/day) was started empirically, along with a parasitology expert's opinion. A repeated blood smear on the following day demonstrated the presence of intraerythrocytic ring forms of parasites. Blood samples were sent to the reference laboratories for detection of parasite DNA by the PCR assay ( Fig. 2 ). The high fever that recurred after the cessation of steroids was normalized within 3 days of the treatment.

Relative expression (OD/mm) of Plasmodium falciparum and Babesia microti 18S rRNA genes in blood of our patient using quantitative real-time PCR. Positive results for P. falciparum and negative results for babesiosis ( B. microti ) are seen. Values are from OD/mm of each group (mean±SD of triplicated wells) divided by that of the housekeeping gene (β-actin). Significant differences ( * P <0.05) were noted compared to negative controls.

Laboratory findings at the completion of the treatment between days 16 and 17 of the hospitalization revealed Hb 7.4 g/dl, LDH 1,287 IU/L, plasma Hb 5 mg/dl, and haptoglobin <5 mg/dl. The RPI also decreased to 3.6 from 4.1 (day 12). He improved gradually and was discharged on day 20 of hospitalization. Three weeks after the discharge, Hb rose to 12 g/dl, and LDH and plasma Hb levels returned to normal ranges ( Fig. 3 ).

A graph illustrating the clinical course of the falciparum malaria case, showing changes in fever, laboratory values, and medications during the course of illness.

PCR tests for Babesia spp. performed by the Korea Centers for Disease Control and Prevention, Osong, Korea, the Section of Microbiology, Hyogo University of Health Sciences, Kobe, Japan (Prof. A. Saito-Ito), and the Department of Parasitology and Tropical Medicine, Seoul National University College of Medicine, Seoul, Korea all exhibited negative results. Instead, real-time PCR assays performed in Hyogo University of Health Sciences (Prof. A. Saito-Ito) and Seoul National University (JY Chai) ( Fig. 2 ) revealed positive results for P. falciparum . Regarding the PCR protocol to detect malarial DNA ( P. falciparum , P. vivax , and P. malariae ) and B. microti DNA, the procedures of Veron et al. [ 5 ] and Teal et al. [ 6 ], respectively, were followed in Seoul National University College of Medicine.

This case report provides an unusual case of imported severe falciparum malaria that was complicated with prolonged hemolytic anemia, clinically mimicking a coinfection with babesiosis. In this report, we reviewed the protracted clinical course of the case at hand to formulate a differential diagnosis of the unexplained prolonged hemolytic anemia.

Severe falciparum malaria may develop life-threatening complications or death, especially in non-immune travelers of industrialized countries who are returning from endemic areas. The major complications include cerebral malaria, pulmonary edema, acute renal failure, severe anemia, and/or bleeding [ 7 ]. The reported case fatality rate of imported falciparum malaria varies from 0.6% to 3.8% and may exceed 22% even in intensive care unit patients [ 8 ].

Our non-immune Korean traveler infected by P. falciparum had manifested initially as serious complications; confused mentality, pulmonary edema, anemia, and renal failure, but improved with anti-malarial medication and supportive care in a hospital in France. When he presented as having recurrent high fever upon coming back to Korea, we first considered that it might probably be due to an insufficient treatment course for severe malaria and high parasitemia. Several factors associated with treatment failure in malaria might include drug resistance, a short treatment course being prescribed to treat a high parasite biomass, non-adherence to a full course of treatment, or pharmacokinetic factors such as an inadequate dose or oral absorption of artemether-lumefantrine [ 9 ]. In our case, the treatment failure is very unlikely; he completed a full treatment dose in combination with a 1-day course of intravenous artesunate and a 7-day course of Malarone during his stay in the hospital. The regimen administered in combination is being recommended for severe and/or drug-resistant falciparum malaria [ 10 , 11 ]. In addition, he was contracted with progressive hemolytic anemia, and repeated blood smears revealed Babesia -like ring forms (PCR revealed only P. falciparum ).

Babesiosis, transmitted by ixodid ticks, is increasingly gaining medical attention as an emerging worldwide zoonosis in humans. The spectrum of this disease ranges from an asymptomatic infection to a fulminating malaria-like disease, resulting in occasional death. Of more than 100 Babesia spp. identified from small mammals, including rodents and cattle, B. microti and B. divergens are commonly responsible for human cases reported in North America and Europe, respectively [ 12 ]. In addition, cases are now being reported from geographic areas where babesiosis was not previously known to occur, and among travelers and immunocompromised individuals. The diagnosis of potential coinfection with Babesia spp. and other tick-borne pathogens, or with malaria in endemic areas gives a serious challenge to clinicians as well as public health professionals [ 13 ].

Malaria and babesiosis have clinical similarity as well as morphological similarity as blood parasites. The discerning point on Giemsa-stained blood smears can be as follows: Babesia spp. appear as intraerythrocytic ring forms or pyriform inclusions with light blue cytoplasms, whereas Plasmodium spp. present parasitic pigment (hemozoin) and gametocytes, and also intraerythrocytic rings. However, reliable identification of both parasites may not be possible in early stages of infection or in cases with a low level parasitemia [ 13 ]. In addition, Babesia spp. may be easily misdiagnosed as Plasmodium spp. in cases of coinfection with both agents, especially in malaria endemic regions or in travelers returning from areas where malaria is known to occur, but where babesiosis has never been reported before [ 14 ]. In such cases, PCR assays for detection of Babesia DNA in blood should support the microscopic detection of parasites, as a highly sensitive and specific assay [ 15 ].

In our case, the patient denied a tick bite while traveling in Benin of West Africa where epidemiologic information about babesiosis was completely unavailable. As hemolytic anemia can occur due to severe babesiosis for several days to a few months, empirical treatment for babesiosis suspected on clinical grounds was initiated without delay. Concurrently, follow-up blood smears showed the presence of intraerythrocytic ring forms morphologically indistinguishable from Babesia . His clinical course improved with the treatment, but the PCR assay failed to detect Babesia DNA from his blood.

On our retrospective literature review of malaria and hemolysis, there are some studies on severe malaria with prolonged hemolytic anemia asking whether or not the hemolysis is likely a result of severe malaria, and not the treatment itself. Interestingly, there are several reports of newly recognized delayed hemolytic anemia after intravenous artesunate treatment for severe malaria [ 16 , 17 , 18 ]. The relevant 19 cases reported in the literature were summarized in the Morbidity and Mortality Weekly Report in 2013; worsening of hemolysis and anemia occurred 8-32 days after the completion of artesunate therapy, and an initial clinical improvement with the resolution of parasitemia, followed by the resolution of hemolysis within 4-8 weeks after artesunate treatment [ 19 ]. Artesunate is the recommended first-line treatment for severe malaria since 2010, as it more rapidly clears parasitemia and decreases mortality. The mechanism of post-artesunate delayed hemolysis is not fully understood and is still debated; the delayed clearance of infected erythrocytes spared by pitting during artesunate treatment is an original mechanism of hemolytic anemia in malaria, suggesting an indirect role of artesunate [ 20 ]. In addition, there is a concern that these delayed hemolytic events might be the direct toxicity of the non-GMP (good manufacturing practice) artesunate currently used outside of the United States. There are no reported cases of post-artesunate delayed hemolysis in the United States, the only country using the GMP artesunate [ 18 ].

As in the cases of post-artesunate delayed hemolysis reported, our patient manifested progressive severe hemolytic anemia (Hb nadir, 5.6 g/dl) approximately 22 days after intravenous artesunate was given in France, and had hemolysis resolution and Hb recovery to 12 g/dl within 5-6 weeks. As shown in Fig. 3 , a low initial RPI 1.0 followed by a sustained increase in RPI may be consistent with delayed hemolysis reflected in the subsequent changes of the values of Hb, LDH, plasma Hb, and haptoglobin. Therefore, our case may be compatible with post-artesunate delayed hemolysis, if other potential causes of prolonged hemolytic anemia, including babesiosis are excluded.

In our case, an argument for/against a co-infection of falciparum malaria and babesiosis still remains as a limitation of this study. A potential false negativity of conventional PCR assays for detection of various Babesia spp. DNA remains to be evaluated. However, this case report would provide an important data for clinical practice in terms of differential diagnosis of imported malaria and babesiosis, especially in non-endemic countries.

In conclusion, we report a case of imported falciparum malaria complicated with prolonged hemolytic anemia, clinically mimicking a coinfection with babesiosis. What is more, there are growing numbers of travelers returning from areas where the diseases are potentially endemic. Consequently, it must be stressed that either malaria or babesiosis in the particular case of coinfection can be overlooked or misdiagnosed by clinicians of non-endemic countries who have little awareness of the 2 diseases, requiring a comprehensive evaluation of such cases to decrease morbidity and mortality.

ACKNOWLEDGMENTS

A part of this study will be presented at the 32nd World Congress of Internal Medicine, Seoul, Korea, 2014. We appreciate Prof. Atsuko Saito-Ito, Hyogo University of Health Sciences, Kobe, Japan for her kind help in performing real-time PCR assays for P. falciparum and Babesia spp.

We have no conflict of interest related to this work.

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A surprising history of malaria is revealed by clues from ancient bones

Melody Schreiber

In modern times, malaria is thought of as a tropical disease but evidence from ancient bones reveals a different narrative. Above: In Ambowuha, Ethiopia, Birtukan Demissie and her siblings are protected from mosquitoes that carry the disease with a bed net. Joining them is the family cat. Louise Gubb/Corbis Historical via Getty Images hide caption

How old is malaria?

Researchers used to think it was two or three thousand years old at most — a modern disease that appeared long after most humans gave up the nomadic hunting lifestyle and formed towns and cities, making it easier for diseases to spread quickly and efficiently.

But a study published Wednesday in Nature paints a different picture — and may change the way scientists and historians view this ancient pathogen.

Malaria is at least 5,500 years old, the study found and might even be much older, the researchers say.

“We still haven't really figured out where and when it exactly originated,” Johannes Krause , an author of the study and director at the Max Planck Institute for Evolutionary Anthropology, told NPR. “It actually seems that we have to go quite further back in time, maybe 10,000 years.”

Clues from very old bones

For this study, researchers gathered slivers of ancient human bones from archaeologists, museums and their own excavations around the world.

Then they examined the tiny samples carefully and, for the first time ever, found even tinier traces of malaria parasites preserved on them.

That alone was a “big surprise,” Krause said. It’s hard enough to find human DNA in a bone sample that’s thousands of years old, “but what's the chance to find the pathogen that was present in the person when he died?”

Next, the scientists compared the DNA of those older parasites to modern-day versions of malaria and discovered a few more surprises.

The two forms of malaria found in the Americas were both brought by Europeans, the researchers determined.

Plasmodium vivax , a type of chronic malaria, was introduced when Europeans colonized South and North America beginning in the 15th century.

And Plasmodium falciparum — a type of deadly malaria that is “one of the most problematic human pathogens known today,” Krause said — was spread by the slave trade. Slavers and enslaved peoples likely got sick with malaria before their journeys or on the ships, and then mosquitoes in the Americas could pick up the pathogen by biting the infected person, then pass it on to their next victim. (Malaria is spread by mosquito bites, not from person to person.)

That put to rest the theory that malaria was already present in the Americas when Europeans colonized and enslaved other people.

Another surprise: scientists used to think P. vivax was older than P. falciparum – but so far, there’s no evidence of that.

What else they hope to figure out

The relatively new field of archaeogenetics – the study of ancient DNA – has previously examined the history of bubonic plague.

Archaeogeneticists like Krause will continue tracing malaria’s path as far back in time as possible to understand where it emerged and how it evolved.

This study shows how the history of malaria is really a story of human movement – and the ways we shape our environment, including pathogens, experts said.

The researchers were surprised to find malaria in the bones of someone from the Iron Age in Austria – and in bones from Tibet, high in the Himalayas, where malaria-carrying mosquitoes can’t survive. They believe the person contracted the illness elsewhere and then traveled to Tibet — an insight into human mobility using pathogen DNA that’s never been done before, Krause said. And it shows how widespread malaria has been throughout the centuries.

These results were “exciting,” Nathaniel Comfort , a professor of the history of medicine at Johns Hopkins University who was not affiliated with this study, told NPR. “It would suggest that movement, rather than stasis, is the underlying driving force in the spread of malaria.” That means malaria wasn’t spread by the creation of towns and cities, where once-nomadic humans stayed put – it was spread as humans migrated and forced the migration of other people through the slave trade.

By challenging long-held beliefs about the origins and spread of malaria, “it's the kind of scientific result that can change the way we narrate the history,” he said, and “it could transform our understanding of these ancient diseases.”

That understanding could also help us better understand infectious diseases today.

“It can help dissolve some racial stereotypes having to do with medical conditions,” Comfort said, referring to the mistaken idea that people of color in the tropics are more susceptible to diseases like malaria. “It's a reminder that we create a lot of the situations in which diseases flourish, and those are correlated with race and class, and now the poorest and most powerless people tend to have the disease concentrated in that area because of human actions, not because they're naturally more susceptible to disease.”

The study also offers a new insight into malaria’s identity. Today it’s seen as a tropical disease. “As this paper really clearly shows, it's far from that,” he said. “It seems to have spread worldwide, even to the Himalayas – that's astonishing.” The reason that malaria has become a disease of the tropics, he said, is because some countries were able to put considerable resources into wiping it out in their part of the world.

A scary geography lesson

Meanwhile, the history of malaria is still being written. It sickens millions and kills about 608,000 people per year. “It's a huge health burden,” said Krause.

After several decades of progress battling the dangerous parasite, in more recent years cases have gone back up — particularly due to climate change, as the environmental range where malarial mosquitoes can survive expands.

“In parts of the world where it has been already extinguished in the past, now it's actually coming back because of the tropics expanding” as the globe warms, Krause said. For instance, a Maryland man got sick from malaria in 2023 and he had no known history of travel.

“It's something that was actually quite present in the past, in a lot of places that today you wouldn't think about being home to malaria. But that's also kind of the scary bit in some ways, because if it was there 200 years ago, there is also a chance for it to come back.”

Melody Schreiber is a journalist and the editor of  What We Didn't Expect: Personal Stories About Premature Birth .

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