The aetiology of non-malaria vector-borne diseases in malaria-endemic, forested, rural, and tribal-dominated areas of Dhalai, Tripura, in north-east India, was studied for the first time in the samples collected from malaria Rapid Diagnostic Kit negative febrile patients by door-to-door visits in the villages and primary health centres. Two hundred and sixty serum samples were tested for the Dengue NS1 antigen and the IgM antibodies of Dengue, Chikungunya, Scrub Typhus (ST), and Japanese Encephalitis (JE) during April 2019–March 2020. Fifteen Dengue, six JE, twelve Chikungunya, nine ST and three Leptospirosis, and mixed infections of three JE + Chikungunya, four Dengue + Chikungunya, three Dengue + JE + Chikungunya, one Dengue + Chikungunya + ST, and one Dengue + ST were found positive by IgM ELISA tests, and four for the Dengue NS1 antigen, all without any travel history. True prevalence values estimated for infections detected by Dengue IgM were 0.134 (95% CI: 0.08–0.2), Chikungunya were 0.084 (95% CI: 0.05–0.13), Scrub were 0.043 (95% CI: 0.01–0.09), and Japanese Encephalitis were 0.045 (95% CI: 0.02–0.09). Dengue and Chikungunya were associated significantly more with a younger age. There was a lack of a defined set of symptoms for any of the Dengue, Chikungunya, JE or ST infections, as indicated by the k-modes cluster analysis. Interestingly, most of these symptoms have an overlapping set with malaria; thereby, it becomes imperative that malaria and these non-malaria vector-borne disease diagnoses are made in a coordinated manner. Findings from this study call for advances in routine diagnostic procedures and the development of a protocol that can accommodate, currently, in practicing the rapid diagnosis of malaria and other vector-borne diseases, which is doable even in the resource-poor settings of rural hospitals and during community fever surveillance. Infectious diseases are a significant public health burden in India, causing morbidity and mortality , with feThe availability of sensitive Rapid Diagnostic Kits (RDTs) for malaria diagnosis, either by the regular active door-to-door community-level fever surveillance, at village health camps, or by passive surveillance at the health care facilities serving several villages, has allowed population-level malaria testing in endemic areas. However, once malaria is ruled out, identifying the underlying cause of febrile illness becomes challenging . The impPrevious studies in Asia have identified the causes of several NMF illnesses ,11,12, iIn this context, it is crucial to study the aetiology of NMFs in the malaria-endemic regions, and conduct both rural hospital and community-based studies. Several tribal-dominated forested pockets of the Dhalai District, Tripura in NE India, fall under the malaria-endemic area , with maThe Dhalai district lies in the north-east part of Tripura. The study was conducted on the admitted febrile patients at the Ambassa Primary Health Centre (PHC), which serves the small township area of Ambassa Municipality, Village councils and Autonomous District Council (ADC) villages of tribal people. In addition, community/village surveillance was carried out in the malaria-endemic villages of two Sub Centres (SCs), Gurudhanpara and Shikaribari, in the ADC area, with an average Annual Parasite Incidence (API) of >200 and ~50, respectively. A few samples were also collected from villages under adjacent SCs under Ganganagar PHC.The venous blood samples were collected by project technicians from NMF patients from April 2019 to March 2020.Patients’ names were compiled from respective fever registers by manually checking for duplication. Malaria-negative febrile patients at PHC Inpatient Department (IPD) or village households were contacted for sample collection as described in detail in Less than 1-year-olds, febrile patients whose symptoms did not match the criteria , and thoMalarial RDT negative patients, 192 from the community survey, 64 from Ambassa PHC , and four from IPD of District Hospital, Kulai, were screened for NMVBDs.Fever duration and symptoms were recorded as per predefined VRDL Tripura proforma based on Integrated Disease Surveillance Program (IDSP), Tripura guidelines . The patTM IgM/IgG Kits) as per manufacturer’s instructions. In addition, we tested a small subset, irrespective of symptoms for Leptospirosis, using the PanBio Leptospira IgM ELISA kit at VRDL Dibrugarh, Assam. A subset of samples was also tested outside the recommended symptoms and duration criteria of the IDSP guidelines  IgM antibodies by ELISA (NIV IgM Capture ELISA kits), and Dengue NS1 antigen and ST , possession and usage, livestock, and house wall and roof status were recorded.The study used spatial and 30-min temporal resolution rainfall data from NASA’s GPM project, and temperature and relative humidity data from the MERRA-2 model. The daily maximum, minimum, average temperature, NDVI and relative humidity on a spatial resolution of 50 km × 62.5 km were plotted from the datasets downloaded in NetCDF formats and extracted using software codes.Land use land cover (LULC) mapping was prepared using the orthorectified Indian Remote Sensing satellite data, Cartosat-1 (2.5 m) and LISS-IV (5.8 m), employing on-screen visual interpretation techniques in Geographical Information System (GIS) platform. Major LULC categories, subcategories were delineated and updated using the latest data (2019) on the spatial layer, initially prepared under NRSC/ISRO’s Space-based Information Support at 1:10,000 scales. In addition, field verifications were made by the project team to check for the accuracy of the interpreted data. The symptoms, clinical findings, demographic data and laboratory results were used for descriptive analysis in IBM SPSS Statistics 20. The Chi-square test was used to assess the differences between different age groups in Epi. Yates’ Continuity correction test was applied to chi-square in R version 4.1.0 software environment for statistical computing. As Dengue was tested by both IgM and NS1, these tests were considered separately for calculation. IBM SPSS Statistics 20 and Epi InfoTM version 7, CDC, USA, was used. For calculation of true prevalence values, Epitools, an epidemiological calculator, was used . All then = 46). Leptospirosis was not considered because of the small numbers tested. A k of four was chosen, corresponding to the four diseases. The analysis was carried out using the klaR package in R version 4.1.0 software environment for statistical computing [k-Modes clustering was used to test whether the four NMVBDs  had distinct symptoms. A set of nine symptoms  were used for this analysis, and only cases which tested positive for a single infection were considered  are given in Out of 260 malaria negative febrile samples collected , 61 were found positive—nineteen Dengue, twelve Chikungunya, six JE, nine ST and three Leptospirosis, and mixed-infections, viz., three JE + Chikungunya, four Dengue + Chikungunya, three Dengue + JE + Chikungunya, one Dengue + Chikungunya + ST and one Dengue + ST. The details of positive infections found from PHC and villages, and test positivity rates are shown in Headaches and body ache were found most commonly in all infections, followed by Myalgia in Dengue and Chikungunya . Chills The cluster analysis is shown in A subset of samples tested outside the duration criteria of >4 days of fever for IgM or ≤4 days for NS1 antigen tests were found positive for NMVBDs . In addiChi-square analysis showed the <15-year group had a significantly higher risk for Dengue and Chikungunya. After applying Yates’ continuity correction, the higher risk in <15-year age group in Dengue remained significant. There was no significant difference or trend in JE or ST. For JE and ST, there was no significant difference between different age groups . Higher Jhum cultivation, where villagers slash and burn the forests in one hillock deep inside the forest area and cultivate for a year, staying in temporary Jhum huts or going up and down from villages regularly through dense forest-areas, was the main occupation of the febrile villagers tested for NMVBDs. No pattern for houses with different types of walls and roofs or livestock possession was found among the disease positives.Analysed from the village census data , the majThe ecological maps of Ambassa block plot the distribution of households sampled from the villages a as FiguNMVBDs occurred throughout the year, with significant positivity even in the winter months . For theIn some cases, fever duration at the time of collection was >5 days. Hence, samples collected at the beginning of a month can be the infection of the previous month. Taking together the incubation time in humans, the cycle time in mosquitoes and the time taken from breeding to mosquito maturation, it would be better to interpret the monthly data correlation with meteorological data of the previous month.To the best of our knowledge, this is the first study to diagnose NMF cases collected from the community door-to-door fever surveillance in remote malaria-endemic rural forested regions of India, from the patients termed as malaria negative by the routine surveillance system. It thus points towards gaps in the diagnosis system in malaria-endemic areas and adds a new dimension to the growing knowledge of aetiologies of NMFs in India. Malaria has been the only priority for fever surveillance in these villages, located in a malaria-endemic zone, where the presence of other vector-borne diseases has never been attempted to be diagnosed at the community level. They have been neglected even in the rural PHC level routine surveillance and research studies as well.We have shown that this area is highly malarious, where a substantial number of malaria cases can be seen with an API of ~10 for Ambassa PHC in the study period, and an API of ~122 for Gurdhanpara SC, and ~57 for Shakaribari .Jhum in deep forests  of a ~60,000 population , and 250 forests , poor avFor the PHC febrile cases, NMFs remain undiagnosed, and mostly symptomatic management is done for NMFs unless referred to tertiary care hospitals at the State Capital. There is no aetiological study published so far for rural PHC based NMFs in Tripura. Even in these highly malaria-endemic areas, malaria accounted for only 10–15% of febrile cases. Hence, this study attempted to shed light on the aetiology of NMFs in the PHC admitted cases, also.We detected JE, ST, Leptospirosis, and even Dengue and Chikungunya, and mixed-infections mainly termed urban, semi-urban, or semi-rural, in these forested rural areas a. The abAge group analysis showed a preponderance of Dengue and Chikungunya in the <15 age group , indicatAs this is the first report of these NMVB diseases from this area, there is no baseline information. Hence, the prevalence numbers estimated should be taken with caution, especially for community-based screening. A well-designed study is thus required to cover such areas in Tripura State and the whole of NE India to estimate the actual disease burden, comprising of the determination of the prevalence and seroprevalence for these diseases and other pathogens.Our study also reported several mixed infections. However, we cannot completely rule out the chances of cross-reactivity. Furthermore, the mixed infection cases can be co-infections at the time of collection, or some can be from previous months, as IgMs have been shown to persist for months. Even in the case of co-infections, the causative agent(s) for the fever and other symptoms need to be nailed down. The present study, with its objectives, could not differentiate between these possibilities and requires the designing of further studies. If the screening of NMVBDs comes under the routine diagnostic protocol, it would be easier to resolve the mixed-infections related issues.Leptospirosis was positive in three samples out of 51 tested from the villages, demonstrating the occurrence of Leptospirosis, though screening of significant numbers is required. Our findings also suggest the need for widening the symptoms and duration eligibility criteria as the tribal patients in these areas may not be very accurate in their presentation of various symptoms and fever duration, especially in the community surveillance by grass-root health workers. There was a lack of a defined set of symptoms for any of the Dengue, Chikungunya, JE or ST infections, as indicated by the k-modes cluster analysis. Interestingly, most of these symptoms have an overlapping set with malaria. Therefore, it becomes imperative that malaria and non-malaria vector-borne diseases’ diagnoses are made in a coordinated manner. The reluctance of the febrile patients to give venous blood was faced as many refused to give blood for testing these diseases, which are unknown to them, unlike malaria. Thus, it would be beneficial if routine blood collection for diagnosing malaria and NMVBDs from febrile patients was performed and awareness generated. Two major takeaways of this study are: (i) A routine diagnostic surveillance strategy encompassing NMVBDs along with malaria is required at PHC IPD and OPD, and community levels through the regular collection of febrile samples. Advancements are required to get the point of care diagnostics for NMVBDs with malaria. An integrated fever surveillance and management system are required at the grassroots level; (ii) Exclusive PHC based studies leave a substantial vulnerable population. Hence community-level studies are essential to ascertain the prevalence of NMVBDs and estimate the actual burden. This will be significant in estimating disease burden, preventing any disease outbreak by appropriate control measures and/or treatment, resulting in a decline in disease morbidity and mortality. It is worth mentioning that this study’s findings have prompted some surveillance at the rural health centre and community levels, especially for Dengue, with a rapid kit. Facilities for ELISA testings have recently started in some District hospitals. It helped report a very recent Dengue outbreak in some rural areas of Tripura (unpublished data).With the presence of ST and Leptospirosis infections, a presumptive treatment regimen of Doxycycline for adults and Azithromycin for children and pregnant women can be thought of until the investigation reports come, in the case of malaria negative fever patients, to save them from morbidity and mortality. A study of such treatment for children presented with fever in peripheral health facilities in Gorakhpur, Uttar Pradesh, had shown promising efficacy in preventing AFI progression to AES . ImmunisAedes and Culex vector species that transmit Dengue/Chikungunya and JE, respectively, are found (unpublished). The presence of these vector-borne diseases, even in winter months (December–February)  , suggestebruary) a, withoureported ,22. Reporeported  from somreported ,34,35 mang LLINs . Hence, n = 170) and a Lower Respiratory Tract Infection (LRTI) includes 13% (n = 25). The remaining 2% (n = 4) showed features of jaundice, vomiting, passing of dark urine and abdominal pain. Hence, it is crucial to conduct a study spanning the probable spectra of fever causing pathogens to investigate the aetiology of fevers in an area with a very high fever load. However, we would like to emphasise here, as mentioned before, there is a possibility that some more samples would have been detected for Dengue, Chikungunya, JE, and Scrub Typhus, had all the 260 samples been tested for all these diseases, irrespective of symptoms. Only a small subset of the samples from the community surveillance was tested for Leptospirosis, raising the possibility of increased detection of this infection in the full set. Furthermore, in this study, we have defined NMFs as fevers that are negative for malaria by RDT. It would be worth exploring if they were positive for malaria by microscopy or more sensitive methods, and contributing to fevers. There are several more sensitive diagnostic tools other than the gold standard light microscopy which are now being reported, some of which diagnose only Plasmodium falciparum while there are some for both P. falciparum and P. vivax, which are the predominant species in the study area. To mention a few, 18S nested PCR can detect 1–2 parasites of P. falciparum and 5–10 of P. vivax per microlitre [Cytochrome Oxidase III can diagnose all five human malaria parasites and is rapid with very high sensitivity [P. falciparum and P. vivax with high sensitivity and specificity [Many fevers can also be caused by water and foodborne pathogens, and UTI and respiratory infections, which are not studied here. Of 199 (77%) undiagnosed cases, in whom the aetiology remains unknown after screening for 6 specific aetiologic agents , assessed in the present study, the majority of them showed symptoms of respiratory tract infections, among which an Upper Respiratory Tract Infection (URTI) includes 85% ( 13% n = . The remcrolitre ; micromacrolitre  is an insitivity ; an ultrsitivity  and a rocificity . Recentlcificity . AlthougOne note of caution to be added here, in the highly malaria endemic areas, such as the current study area, a large load of submicroscopic, low-density malaria is found, where a sizeable proportion can be asymptomatic malaria , hence, Due to the ongoing pandemic, overlap in the clinical presentation and shunting of available resources and infection control in suspected COVID-19 patients can cause a delay in diagnosis and management of AFI . As COVIThis is the first study reporting the diagnosis of indigenous non-malarial vector-borne infections in malaria negative fever samples collected from the community fever surveillance in remote malaria-endemic tribal areas of India, indicative of local transmission for even Dengue and Chikungunya in deeply forested localities. Although these villages represent a very high fever load, malaria has been the only priority for fever surveillance in the villages and rural hospitals located in the malaria-endemic zone, where the presence of other vector-borne diseases are usually not attempted to diagnose. With the high positivity rates and many febrile cases not going beyond villages to seek treatment, studies to determine the actual prevalence and routine diagnostic surveillance, both at community and rural hospital level, even in the malaria-endemic region, become imperative. Findings from this study call for advances in routine diagnostic procedures and the development of a protocol that can accommodate currently, in practice, the rapid diagnosis of malaria and other vector-borne diseases, which are doable even in the resource-poor settings of rural hospitals and during community fever surveillance in order to prevent morbidity, mortality and outbreak situations.


Zambia continues to advance on the path to elimination with significant reductions in malaria morbidity and mortality. Crucial components that have contributed to progress thus far and are necessary for achieving the national malaria elimination goals include properly identifying and treating all malaria cases through accurate diagnosis. This study sought to compare and assess the diagnostic performance of Rapid Diagnostic Tests (RDT) and Light Microscopy (LM) with photo-induced electron transfer polymerase chain reaction (PET-PCR) as the gold standard using 2018 Malaria Indicator Survey (MIS) data across Zambia to better understand diagnostic accuracy metrics and how these vary across a transmission gradient.Cross-sectional samples collected in a nationally representative survey from 7 provinces in Zambia were tested for the presence of malaria parasites by light microscopy (LM), rapid diagnostic test (RDT) and the gold standard PET-PCR. Diagnostic performance was assessed including sensitivity, specificity, negative- and positive-predictive values across a wide malaria transmission spectrum. Diagnostic accuracy metrics were measured, and statistically significant differences were calculated between test methods for different outcome variables.Plasmodium falciparum malaria was 32.9% by RDT, 19.4% by LM, and 23.2% by PET-PCR. Herein, RDT and LM diagnostic performance was compared against gold standard PET-PCR with LM displaying a higher diagnostic accuracy than RDTs (91.3% vs. 84.6% respectively) across the transmission spectrum in Zambia. However, the performance of both diagnostics was significantly reduced in low parasitaemia samples. Consistent with previous studies, RDT diagnostic accuracy was predominantly affected by a high rate of false positives.From the individuals included in the MIS, the overall prevalence of RDTs and LM both perform well across a range of transmission intensities within their respective target applications, i.e., in the community, for the former, where ease of use and speed of result is critical, and at the health facility, for the latter, where accuracy is prioritized. However, the performance of both diagnostic methods is adversely affected by low parasitaemia infections. As Zambia moves towards elimination more sensitive tools may be required to identify the last cases.The online version contains supplementary material available at 10.1186/s12936-021-03917-6. Although significant progress has been made globally to reduce malaria burden through a coordinated international effort focused on vector control, accurate diagnosis and appropriate treatment, malaria continues to be a major global public health problem with devastating impacts on human health and livelihood, especially in sub-Saharan Africa . In 2019To this end, many countries throughout Africa conduct Malaria Indicator Surveys (MIS), i.e. comprehensive and nationally representative household surveys to collect key malaria data . MeasureIn Zambia, the main malaria control interventions include vector control and effective case management . With coP. falciparum specific histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) and light microscopy (LM) [P. falciparum trophozoite-derived HRP2, which accounts for 98 % of malaria cases and morbidity in Zambia and the region at large [Currently, Zambia uses two main diagnostic tools for malaria parasite detection: the opy (LM) . RDTs deat large , 9, 11. at large –14. In cat large , 16. As Plasmodium species can be simultaneously identified with PET-PCR, and in areas of low transmission that are approaching elimination, these other malaria species may become more relevant [Molecular methods can detect parasitaemias below LM and RDTs limit of detection (LOD), making them excellent gold standards to assess diagnostic performance –19. Likerelevant , 20, 21.P. falciparum malaria using PET-PCR as the gold standard. Understanding how these three different diagnostics perform and quantifying diagnostic accuracy will provide insights on prevalence of malaria infection and how these metrics vary according to transmission intensity.As Zambia continues to progress toward malaria elimination, it is essential to diagnose all malaria cases accurately to enable appropriate treatment. Understanding how RDTs, LM, and PET-PCR diagnostics compare across the Zambian transmission gradient will be crucial to achieving this goal. This study, therefore, aimed to assess the diagnostic performance of RDTs and LM for diagnosis of In 2018, a MIS was performed that randomly surveyed a total of 4177 households across 179 standard enumeration areas from ten provinces in Zambia [Before performing the MIS, training was provided for health workers on how to perform an RDT , prepare a DBS and thick smear slide as well as how to interview community members and collect survey responses . RDT tesPlasmodium parasites were more than 10, or 500 WBC when Plasmodium parasites were less than 10, and then converted into a parasite concentration [Thick smear microscopy slides were stained in 10% Giemsa at the NMEC laboratory and read independently by two malaria microscopy-competent technicians. Arbitration of discordant results was performed by a third reader. A blood smear was considered negative when no parasites were detectable after examining 100 high power fields. For positive smears, parasites were counted in reference to 200 white blood cells (WBC) when ntration .DNA was extracted from a single 6-mm punch  from each DBS using the QIAamp DNA mini kit  and eluted in 100 µL of Elution buffer. Punchers were cleaned by making 5 blank punches on clean filter paper between samples. A subset of blank punches was extracted for testing to ensure that there was no cross-over between samples. Extracted DNA was stored at 4 °C for immediate analysis or at − 20 °C for longer term storage.Plasmodium spp. and P. falciparum primers labelled with FAM and HEX fluorophores, respectively, as previously described [P. falciparum genomic DNA , obtained through BEI Resources, National Institute of Allergy and Infectious Diseases, National Institutes of Health, contributed by David Walliker, of a known parasitaemia was assayed three times in duplicate by PET-PCR. The standard curves generated from this series established a comparable LOD, as previously published [Extracted parasite DNA was detected by real-time PET-PCR, on a LightCycler 480 . In brief, all samples were tested in duplicate  in a duplex reaction with escribed , 23, 24.ublished , and werwww.graphpad.com) and a P value of ≤ 0.05 was considered statistically significant.Number of DBS samples per province were counted and compiled using dplyr and tidyverse function R package , 26. UsiP. falciparum by RDT, LM, and PET-PCR respectively across seven provinces. 17.0% (537/3152) of RDT results and 9.9% (274/2758) of LM results were discordant  when compared to PET-PCR , 19.4% (535/2758), and 23.2% (733/3153) of study participants were positive for P. falciparum malaria prevalence and burden across the examined transmission gradient in Zambia.Diagnostic prevalence per province was highly heterogenous as expected given the transmission gradient across Zambia. Specifically, RDT prevalence ranged from 25.4% to 44.7%, LM from 11.3% to 32.6%, and PET-PCR from 15.4% to 38.0%  and specificity (the probability that a test result will be negative when the disease is not present) for RDTs showed higher sensitivity 84% (95% CI = 81–87), but lower specificity 83% (95% CI = 81–84) when compared to LM at 71% (95% CI = 67–74), and 96% (95% CI = 95–97) respectively. Positive Predictive Value (PPV) (the probability that the disease is present when the test is positive) and Negative Predictive Value (NPV) (the probability that the disease is not present when the test is negative) were also measured and showed that RDTs had very low PPV 59% (95% CI = 56–62) compared to LM at 84% (95% CI = 81–87)  vs. RDT (84.6 %) across all seven provinces. Furthermore, there was no obvious variation in diagnostic accuracy with prevalence.Other metrics found that LM had a statistically significantly higher specificity range = 94–98 %) compared to that of RDT (range = 68–85%). In contrast, RDT showed high sensitivity (range = 76–96 %) but very low PPV (range = 36–75 %) compared to the sensitivity of LM (range = 54–78%), PPV (range = 71–90%)  and LM PPV , respectively. No other statistically significant correlations between other diagnostic metrics  and parasite prevalence were identified.A total of 116 false negatives i.e., PET-PCR positive/RDT negative were identified. The parasitaemia in these samples (median = 7.31 parasites/µL) was significantly lower (P < 0.001) than the parasitaemia (median = 106.1 parasites/µL) in true positive (TP) samples, i.e., PET-PCR positive/RDT positive Fig. A. A simiTo assess whether individuals may have had a recent malaria infection, self-reported fever or taking drugs for a fever in the past 2 weeks was used as a proxy. In this group of individuals, the RDT false positive rate of 28.2% (140/496), was almost double that of those not reporting recent fever at 14.6% (281/1923).Plasmodium antigens using RDTs is widely used for malaria diagnosis. RDTs are inexpensive, do not require advanced sample preparation or specialized training, and rapidly generate results [Malaria was placed at the forefront of the global public health agenda in 2000 when the Roll Back Malaria Partnership announced a commitment to halving malaria cases by 2015 . A decad results . This co results . RDTs ar results . However results –35. RDT While both diagnostics performed well, overall LM had a higher diagnostic accuracy 91.3%) than RDTs (84.6%), supporting the historical use of LM as the gold standard diagnostic .3% than , and is A key question this study set out to address was how diagnostic performance varies across a wide transmission/prevalence range, and in the main, the performance was consistent Fig. . HoweverOverall, the findings from this study suggest that to more accurately monitor malaria transmission dynamics, countries in pre-elimination settings require more sensitive diagnostic tools to detect asymptomatic and low parasitaemia cases. Molecular techniques, such as nested polymerase chain reaction, quantitative real-time PCR, and ligase detection reaction fluorescent microsphere assay have been developed and have shown greater sensitivity for a broad range of parasitaemias , 42. HowPlasmodium antigens after treatment and contribution of non-malaria illness on RDT false positivity.This study had a number of limitations. Firstly, the MIS sampling design limited enrollment to children preventing the evaluation of diagnostic performance outside this age group. Moreover, there was a marked variation in sample size per province with oversampling from some high transmission areas and under sampling in low transmission provinces, which thus were excluded from this analysis. This study also was not able to address treatment status of study subjects and other non-febrile illnesses among children to assess longevity of P. falciparum malaria diagnostic performance evaluation within the nationwide 2018 Zambia Malaria Indicator Survey supports the utility of malaria RDTs for community screening based on their low rate of false negatives and their ease of implementation. In contrast, LM remains the diagnostic method of choice for confirmation of active infections, and accurately treating patients. Notably, the parasitaemia of an infection is one of the main determining factors impacting diagnostic performance and, therefore, accurate determination of malaria parasite prevalence. These findings further suggest that to improve malaria prevalence estimates and case detection in low transmission settings, more sensitive and rapid molecular diagnostic tools to detect asymptomatic and low parasitaemia infections may be necessary to achieve and sustain malaria elimination.This Additional file 1: Table S1. Comparison of RDT and LM diagnostic metrics per province in Zambia.


Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission . Genetic identity  was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts. This heterogeneity is evidenced by hotspots of malaria transmission which can sustain and amplify the malaria transmission chain6. Targeting and eliminating malaria hotspots can play an important role in malaria elimination6. Different studies using conventional malaria epidemiologic tools such as malaria incidence and prevalence rates, malaria morbidity and mortality rates, and entomological inoculation rates (EIR) have identified hotspots of malaria transmission; however, some of these metrics are better suited for more highly endemic regions9 and may become less useful as malaria transmission declines. As some regions strive for malaria elimination, along with the decline of the disease incidence some of these conventional malaria metrics may become less informative10.As malaria transmission declines, and as population level immunity wanes, spatiotemporal variation in malaria incidence is likely to become more pronounced11. Genomic epidemiology has been used to detect associations between malaria parasite genetic diversity, dynamic changes in transmission intensity, and malaria programmatic impact15. We have previously validated a 24-SNP molecular barcode for monitoring changes in transmission intensity as well as for tracking specific parasite types in the population16. More specifically, genomic tools can reveal whether specific genotypes dominate hotspots from focal local transmission of individual strains, or whether the malaria transmission landscape is characterized by increased genetic diversity with significant potential for outcrossing resulting from sustained transmission or importation of multiple genotypes17. Genomic data can be coupled with mapping data, such as geographic information system (GIS), for visualizing spatial epidemiology. These combined data types can be informative for evaluating control measures. For example, GIS and epidemiologic data were used for mapping clusters of malaria transmission in Gambia, Mali and Senegal and used to guide optimal malaria control intervention18. GIS information can also give important information at the household level for studies in micro-epidemiology and ecology19. This combined approach was used in Papua Indonesia by coupling genetic information of Plasmodium falciparum and P. vivax from microsatellite data and household level GIS information to study malaria micro-epidemiology20. In Senegal, few studies have used genomic data to understand Plasmodium parasite genetic diversity and spatiotemporal dynamics. Here, we seek to bridge this gap by using genomic epidemiology and ecology at the city, neighborhood, and household levels.Genomic data from sensitive molecular tools are capable of detecting low level parasitemia and of providing additional information on parasite genetic population structure to measure the dynamic changes in malaria transmissionP. falciparum parasite population structure in Thiès, Senegal. We determined the spatio-temporal parasite haplotype distribution, and the association between physical distance and parasite genetic distance and the interconnectivity between parasites using a recently developed hierachical Bayesian regression model21. These analyses helped generate hypotheses on possible reasons for transmission hotspots. The overall goal of this study is to help inform malaria control by integrating genomic data into decision making.The aim of this present study was to apply the 24-SNP molecular barcode in a longitudinal cohort enrolled between 2014 and 2017 and followed for 2 years after enrollment to understand P. falciparum monogenomic infection. Patients were residents of 6 different neighborhoods in Thiès  and 10 different houses . The majority of the participants were from Diakhao 51/70 (72.8%), and the majority of shared household participants were in household MS; 37/70 (52.8%)  and followed for two years post-enrollment. Patients were recruited through passive case detection upon presenting at the Service de Lutte Anti Parasitaire (SLAP) clinic with malaria-like symptoms and testing positive by malaria rapid diagnostic test (Pfhrp2 antigen RDT) and microscopy for 14. The majority of polygenomic infections were observed in 2015 (5/7). More than 64.8% (48/74) of parasite genetic types were shared within participants of the cohort overall, and when shared by year, 2014 = 0% (0/2), 2015 = 66% (21/32), 2016 = 67% (18/27), and 2017 = 62% (8/13).In comparison with cross-sectional barcode data from Thies from clinical cases identified in 2015, 2016 and 2017, the proportion of shared genetic types between isolates were 48% (80/165),50.4% (62/123) and 35% . The prevalence of shared genetic types in the cohort was just significantly different from the overall percentage in the population (p =.03) for 2015 and 2017, by Z-test for two population proportions; 2016 was not significant (p=0.06). Of the 74 infections, 32 distinct monogenomic distinct genotypes (haplotypes) were identified. Twenty-four haplotypes previously described in Thiès were detected in 57 isolates (57/74); eight unique genotypes were observed in this cohort and detected in ten participants (10/70). Among the 24 haplotypes we found 8 clusters (shared parasite haplotypes between at least two participants); these were haplotypes 25, 83, 759, 796, 804, 846, 873, and 1001. Among the 10 unique parasites, 2 clusters (U2 and U4) in a total of 4 infections were found . The participants’ infections were distributed across time as follows: 2014 (2 infections), 2015 (32 infections), 2016 , 2017 (13 infections). Of the 74 infections genotyped, monogenomic infections were predominant 90.5% (67/74) and polygenomic infections were rare, 9.5% (7/74). This finding is predicted for the regionund Fig. . In thisGenetic types were shared within a transmission season but also across transmission seasons (lineage persistence). The dominant haplotypes that persisted for multiple seasons were haplotypes 759 and 796. Haplotype 759 (11/70) was detected in 2015 in Diakhao in the MS household 5/32) and in 2017 in Nguinth in the GB household (5/13). Haplotype 796 (11/70) was observed in 2014 (1/2), 2015 (both in MS) and 2016 (8/23) in the neighborhood of Diakhao in three different households .Those two haplotypes are also the predominant haplotype persistent over year  in the Thies barcode data base (data not published), with haplotype 759 detected all 3 years. Haplotype 83 (6/70) was found in 2016 in two different neighborhoods (Diakhao and Takhikao) in three different households   were re-infected in the following year during the peak of the malaria transmission period. Unscheduled visits in which study subjects had symptomatic infections are designated as “re-infections” or R1 . Re-infected participants were all from the same household (MS). Parasite genotypes from the first infection were genetically distinct from the re-infected parasites , we observed a significant positive association between physical and genetic distance in 2015 and 2016  and time (transmission seasons) Fig. . For sam24. In this study we combine parasite genetic diversity indices, individual global position system (GPS) information at the neighborhood and household level, and a hierarchical Bayesian regression model to understand parasite diversity and connectivity over time and space in Thiès, Senegal. The main findings of this study were household clustering of genetic types, association with genetic distance and physical distance, as well as parasite sharing between participants from either the same household or different households which were geographically proximal. This study provides additional data from a well characterized low transmission setting at very focal spatial scales and with precise mapping of malaria in households and neighborhoods, specifically in daaras. This fine spatial and temporal scale is not always possible with large cross-sectional datasets; and interestingly, in past analyses from cross-sectional studies in Thiès, this spatial clustering of identical genotypes was not observed25.As malaria control progresses towards elimination, genomic data has proven to be essential in assessing control and surveillancePlasmodium parasite genetic diversity and the high frequency of monogenomic infection observed over years are generalizable and consistent with previous observations from cross-sectional sampling over time in Thiès25 and Dielmo and Ndiop in Senegal16. Average expected heterozygosity  in 3 years  in three different households . Similarly, haplotype 759 was observed in two different neighborhoods, in 3 successive years (2014-2017) and in three different households . When observing identical genotypes in households, there are two possibilities: 1) continued local transmission of a single parasite genotype that maintains genomic identity through selfing, or 2) the same infected mosquito biting multiple individuals within the household or neighborhood. The spatial and temporal nature of the infections can help distinguish which hypothesis is more likely; but additionally, this is an area where IBD has added value. Clonal propagation of identical parasites in households over short temporal scales (days) would favor infection of multiple individuals by the same infected mosquito, yielding identical parasites by both IBS and IBD. Continued focal transmission of identical parasites in households observed over longer temporal scales (weeks to months to years) would favor local household transmission of inbred parasite lineages, and here we may expect more heterogeneity in IBD even in parasites that are IBS due to limited outcrossing in the mosquito. We observe both scenarios in our study. An increase in genetic diversity and limited clonal propagation would imply imported parasites followed by outcrossing or co-transmission, with outcrossing resulting in genetically diverse monogenomic infections and co-transmission resulting in an increase in polygenomic infections. This study has also demonstrated that household transmission of the same genotype is frequent in Thiès, and that cross-neighborhood and cross-year transmission of the same genotype is also common, again implying a relative lack of outcrossing in the overall population27.Consistent with previous studies in Thiès, we also observed the existence of haplotypes persisting over several years28, genomic surveillance by longitudinal sampling can provide valuable insights into changing malaria ecology and transmission dynamics. Interestingly, but perhaps not unexpectedly, the genetic similarity of parasites identical by barcode (IBS) breaks down a bit when assessing genetic similarity at the whole genome level through IBD. IBD analysis shows that for haplotypes persisting for multiple years, identical parasites which are clonal by IBS most often are identical at the whole genome level, but can share from 70 to 100% of their whole genome, with those more distantly related in time sharing less overall genomic identity. We observed this notably in two instances, one of a haplotype spanning a two year gap and identified in a more distant household , and the second in a haplotype spanning multiple years (2014–2015–2016), and multiple households, but yet IBD was only decreased in the isolate from the highly diverse household MS. This finding implies that some of these barcode clonal parasites experienced some degree of out-crossing, and this was more likely over time and in households with a large and diverse pool of parasites serving as a potential recombination reservoir.As the overall degree of genetic variation can vary depending on the season of transmission, the intensity of transmission, and also the degree to which new strains are introduced into the population32, followed by genetic recombination (outcrossing) within the Anopheles mosquito33, and the subsequent transmission of new genetic combinations17 resulting in a hotspot of local intense transmission17. The predominance of polyclonal infections in this household would also favor this hypothesis. A similar study of malaria incidence and prevalence has demonstrated the existence of malaria transmission hotspots at the village level in Senegal8. In such villages, human density, human behavior, infrequent malaria bed-net use, substandard housing construction, and a favorable ecological environment for mosquito proliferation (presence of mosquito breeding sites) have all been identified as risk factors for a household to be in a hotspot34. The added value of our approach is being able to identify hotspots of transmission, but also to determine the genotypic nature of these hotspots - adding further to implications for control measures. If hotspots are populated by similar genotypes, it is more likely that local transmission of selfing strains is occurring. If multiple diverse monogenomic genotypes are present, the hotspot could serve as a hub of human or mosquito imported infections. If polyclonal infections increase, it implies a combination of both: importation following by increased local transmission. Identification of the transmission clusters at the household level will play an important role for interrupting malaria transmission chains35. Identifying neighborhoods or households with high malaria transmission can assist malaria control programs with focal interventions to reinforce malaria prevention and control.We observed household clustering and genetic differences between parasites to increase with distance between individuals. During this study, a particular household (MS) served as an example of a malaria hotspot of transmission at the household level, both in number of cases as well as genetic diversity of the parasites. Having such different parasites in the same household could be the result of importation of diverse genotypes due to human or mosquito mobilityP. falciparum is a sexually recombining organism, precise mapping of phylogeny and transmission chains is not possible; however, the 24-SNP barcode has been shown to be a proxy for whole-genome that allows resolution especially of highly similar parasite types14. While the 24-SNP barcode does not provide as complete information about genetic relatedness (identity by descent) as whole-genome sequencing or large SNP arrays36, it has been estimated that the 24-SNP barcode can confidently detect parasites that share greater than 70% genome similarity (identity by state)14. While the pairwise genetic distance in the 24-SNP barcode is not linearly associated with whole-genome genetic distance, our finding of significant associations with physical distance is even more noteworthy. Our statistical model demonstrated that genetic variation between parasite pairs increases with physical distance. Here we used the number of SNP differences between paired individuals as genetic distance, or identity by state. Studies in The Gambia and Kenya have demonstrated that variation between parasite genotypes increases with geographical distance38. Such findings will help in understanding how the parasite population is structured in Thiès and the connectivity between parasites, despite some studies in Thiès having suggested a mixed parasite population with no hidden population structure27. In this study, sampling biases (number of limited samples) may not reflect the overall parasite population that is captured by passive case detection, and notably, we found no asymptomatic infections in any of the follow-up time points in the cohort.Because daara”s, religious boarding schools where “talibe” (resident student followers) live together in large numbers. One particular daara, arbitrarily termed “MS” had a very large proportion of cases, a diverse haplotypes and all re-infected participant were from that household. As a specific population, little is known regarding the malaria burden in this specific community of children, although it has been proposed that this population is considered more vulnerable and may have higher risks of parasitic infectious diseases, due to living conditions39 The high malaria burden in this community may be explained by the household size, close living and sleeping quarters, socio-demographic factors, and less consistent compliance with long-lasting insecticidal net (LLIN) use40. The Senegal national malaria program control (NMCP) has recently established a malaria case management at the level of daraas (PECADARA) to screen and treat students living in these boarding residences with the ultimate goal of preventing morbidity, mortality, and transmission in this demographic. Our findings of malaria burden, evidence of multiple infections of the same parasite in the same household, as well as some households with highly diverse infections, implying a “melting pot” for imported types and recombination23, all support the notion that extended malaria surveillance specifically in the daaras could be an important strategy to prevent continued malaria transmission chains in the community. Daaras also represent an attractive opportunity for intervention for NMCPs as there is the opportunity to systematically reach many children living in the same household.All of the enrolled participants in our study live in “daaras, thus our results would be generalizable to other male residents of daaras; however not to the general population. Yet, this study is the first to provide a detailed genetic characterization of the parasite populations in daaras in Senegal and will provide valuable information to the Senegalese NMCP which is implementing specific interventions in daaras this year. Going forward, studies prospectively designed to specifically investigate malaria transmission dynamics and population genetics in daaras should intentionally include and enroll daaras with male children and an equal number of daaras with female children. Future studies could also apply the same methodologies, but in a population-based cross-sectional sampling approach, in both the high and low transmission periods, and outside the clinical setting, to capture the genetic complexity of both symptomatic and asymptomatic infections throughout the general population.Our study has some limitations. Our cohort was completely male, although enrollment was open and encouraged for both male and females. The ages of participants were children and adolescents, sampling was limited to the high transmission season, and malaria infections were all symptomatic and detected by passive case detection. As the participants were enrolled in a longitudinal cohort and followed over time, we may have observed selection bias for more solitary individuals as those who intended to travel may have opted not to participate. As previously described, all of the samples from participants in this study came from residents of 14, the mean number of samples (monogenomic and polygenomic) across years was approximately 170 and the mean number of monogenomic samples was approximately 125. Based on this data, we estimate that 100 monogenomic samples would be sufficient to detect subtle changes in transmission intensity over time. This sample size is ideal, but as malaria transmission declines in pre-elimination zones, it might prove difficult to achieve, highlighting the need for complimentary measures of transmission intensity such as serological markers of recent compared to historical past malaria exposure.Additionally, our sample size of 70 participants with 74 infections over 3 years is relatively small. From previous cross-sectional studies in Thiès spanning detectable signals of declining and rebounding transmission intensity41, the 24-SNP barcode can be a useful, and importantly field-deployable tool for rapid assessment of Plasmodium genomics. It can be useful in distinguishing polygenomic infections from monogenomic infections for measures of complexity of infection (COI)16, which increases with transmission intensity, even if it is unable to distinguish the identities of parasite genotypes within these complex infections. However, these simple genetic metrics still have value in the context of real-time genomic surveillance efforts and can provide useful and actionable data on transmission hotspots, probable importation or local transmission, as well as assessment of the impact of specific interventions aimed at decreasing malaria transmission. While whole genome sequencing and identity by descent provide a wealth of high-resolution genomic information to clarify population genetic connection and potentially transmission chains; at the moment, measures such approaches have not been actionable in real time. Taken together, our study provides important information in the micro-epidemiology of parasite population structure in space and time in daaras in Thiès. The study also provides evidence of the feasibility and power of including genomic analyses, with field-deployable methods performed on site, in making public health decisions.While the 24-SNP molecular barcode does have limitations in its ability to infer transmission levels and population connectivity, especially on highly local scales; as evidenced by this study and othersPlasmodium spatial-temporal clustering at the household and neighborhood level were observed along with increasing genetic distance between parasites as a function of physical distance. The longitudinal study shows the importance of applying molecular surveillance along with spatial and temporal modeling to detect hotspots of malaria transmission at fine spatial scales.The value of genomic data is especially powerful when traditional epidemiologic measures of transmission are not available or are limited. Taken together, this work emphasizes the added value of combining traditional epidemiology data, including case investigation, household surveys, climate data, and travel history with genomic data and high-resolution temporal and spatial (GPS) data. Combined, they provide powerful insights into local transmission dynamics. These local patterns can have practical implications in providing data to NMCPs on ways to better target local interventions in a way to maximize impact. Identifying the degree to which sustained local transmission or continuous importation of cases from outside a community can influence the specific policy approach adopted, from a focus on specific household or neighborhood malaria prevention efforts to a focus on human mobility as the dominant driver of transmission. Such insights are facilitated by the rapid, real-time acquisition, analysis, and reporting of genetic data to malaria policy makers and represent an attractive model for integrating malaria genomics into decision-making strategy.In conclusion, Ethical approval for this study was granted by the National Ethics Committee of the Ministry of Health in Senegal (Protocol SEN 14/49), the Institutional Review Board of the Harvard T.H. Chan School of Public Health (IRB 14-2830), and the Human Investigation Committee of Yale University (Protocol 2000023287). All samples were collected with informed consent and in accordance with all ethical requirements of the National Ethics Committee of Senegal, Institutional Review Board of the Harvard T.H. Chan School of Public Health, and the Harvard, and the Human Investigation Committee of Yale University.P. falciparum malaria confirmed by a peripheral blood smear and rapid diagnostic test (RDT) by the local health officer of the health clinic of Thiès (SLAP). Patients were asked to return to the health post, regardless of health status, at days 1, 2, 3 and after 2 weeks, 4 weeks, 3 months, 6 months, 12 months, 18 months, and 24 months. Information on intention to travel and number of months in residence at the household was collected, both as part of the enrollment questionnaire, and also as an optional reason an eligible participant decided not to participate. Patients were also asked to return for an unscheduled visit if they experienced malaria-like symptoms. At the visit on days 1-3, the patient was monitored for the clearance of parasitemia by finger prick and a microscopy slide and an RDT was evaluated. At scheduled follow-up visits at 2 weeks, 4 weeks (1 month), 3 months, 6 months, 12 months, 18 months, and 24 months, 5 mLs of blood was drawn for plasma and PBMCs. On Day 0 and at unscheduled visits where a patient was confirmed to be positive with P. falciparum, blood was also cryopreserved, and parasite DNA was extracted from whole blood with the QIAamp DNA blood mini kit .Samples were collected through passive case detection from patients greater than 6 months of age with symptomatic uncomplicated 41. Barcode assays were run on the LightCycler 96 Roche system. SNPs were amplified as follows; P. falciparum strains  was used for assay validation and as genotyping controls for all reaction plates. Molecular barcode assays 10, 11, 13, 21, and 24 were performed optimally under asymmetric forward to reverse primer ratios of 5:1; all other assays required a 1:5 primer asymmetry. Amplification conditions were 95 P. falciparum genomes was present (a polygenomic infection).Polygenomic infections was established in the parasite population by examining the number of heterozygous SNPs (N) in each sample assayed. Infection was classify as polygenomic, when the barcode has at least two (2) heterozygous SNPs (N). Samples were classify monogenomic infections if they have at no more than one (1) heterozygous SNPs (N) in the barcode. Ambiguous calls and calls with “X” were repeated 3 times in independent experiments before validation41. All barcoding was performed in Senegal.24-SNP molecular barcodes were identified using a previously described assay42; on total extracted DNA. Amplified material was sequenced using Illumina technology with paired-end reads after library construction with a NEBNext Ultra II library prep kit. We aligned reads and called variants following best practices established by the Pf3k consortium. In short, we aligned reads to the P. falciparum 3D7 reference genome (PlasmoDB v. 28) using BWA-mem, marked duplicate reads with Picard Tools, and called variants using HaplotypeCaller in GATK v.3.5. We performed variant and base score recalibration in GATK using variants from a set of lab-generated crosses. We prioritized 23 isolates for whole genome sequencing representing the following characteristics: 1) Same barcode, same year, same household; 2) Same year, same barcode, different household; 3) Same barcode, different year, same household; and 4) Same barcode, different year, different household to preliminarily investigate IBD across space and time. Of these, we retained 17 samples that had at least 20% of the genome covered at a read depth of 5x or greater for downstream analysis . For each sample, we masked from analysis heterozygous calls and calls with fewer than 5 supporting reads. Identity-by-descent (IBD) was estimated between all pairs of these 17 samples using hmmIBD28. As model input, we used a set of 15,075 SNPs with population-level allele frequencies calculated from a large collection of Senegal samples .We performed selective whole-genome amplification (SWGA)43:Barcode sequences were aligned using Geneious Prime 2021.2.2. Nucleotide diversity .14 using an existing, larger set of barcode data from Senegal. For each year, we performed 1000 independent sampling iterations and have compiled 68% confidence intervals, representing the mean +/− 1 std deviation (1 sigma), and 90% confidence intervals with the fraction of pairs that are related . We used a recently developed hierarchical Bayesian regression model to determine if the genetic similarity between pairs of participants is related to the geographic distance that separates them21. The model accounts for correlation in the genetic distances due to the fact that an individual is involved in multiple paired responses as well as spatial correlation between responses, and has been used in previous work aiming to estimate associations between genetic and spatial distance44. The number of 24-SNP barcode differences between each unique pair of participants was used to describe their genetic similarity. We used two metrics to describe spatial proximity in the analysis. First, for each unique pair of participants we determined whether the individuals were located in the same house and if so, noted which house it was. Next, we calculated the geographic distance between the house centroids for each pair. In this way, we explore the impact of geographic distance on genetic similarity in two ways; whether people clustered in the same house are more genetically similar and whether individuals in houses that are closer together geographically are more genetically similar.GPS coordinates of participants’ households  and neighborhoods were used to make different maps with QGIS 3  is an indicator function that is equal to one if the input statement is true and is equal to zero otherwise, and https://github.com/warrenjl/GenePair) and present posterior inference  for the model parameters using 10,000 samples from the joint posterior distribution after removing the first 10,000 draws prior to convergence of the model and thinning the remaining 100,000 by a factor of 10 to reduce posterior autocorrelation. We present inference for the exponentiated regression parameters which represent the ratio of expected genetic distances per specified change in each covariate value. For example, the distance estimate in Table 21.We then model genetic distance between each pair of participants as a function of the spatial distance between their houses and a clustering indicator for the specific house, where each house has its own specific regression parameter. The model is given asentclass1pt{minimaSupplementary Information.


E malaria vaccination with seasonal malaria chemoprevention (SMC) substantially reduced the incidence of uncomplicated and severe malaria in young children compared to either intervention alone. Given the possible negative effect of malaria on nutrition, the study investigated whether these children also experienced lower prevalence of acute and chronic malnutrition.A recent trial in Burkina Faso and Mali showed that combining seasonal RTS,S/AS01E alone, or SMC combined with RTS,S/AS01E for three malaria transmission seasons (2017–2019). After each transmission season, anthropometric measurements were collected from all study children at a cross-sectional survey and used to derive nutritional status indicators, including the binary variables wasted and stunted . Binary and continuous outcomes between treatment groups were compared by Poisson and linear regression.In Burkina Faso and Mali 5920 children were randomized to receive either SMC alone, RTS,S/AS01E, but there was stronger evidence of a difference. There was at least a 30% reduction in the point estimates for the prevalence of severe wasting in the combined group compared to the other two groups in 2017 and 2018. There was no difference in the prevalence of moderate or severe wasting between the groups in 2019. The prevalence of stunting, low-MUAC-for-age or being underweight did not differ between groups for any of the three years. The prevalence of severe stunting was higher in the combined group compared to both other groups in 2018, and compared to RTS,S/AS01E alone in 2017; this observation does not have an obvious explanation and may be a chance finding. Overall, malnutrition was very common in this cohort, but declined over the study as the children became older.In 2017, compared to SMC alone, the combined intervention reduced the prevalence of wasting by approximately 12% [prevalence ratio (PR) = 0.88 ], and approximately 21% in 2018 [PR = 0.79 ]. Point estimates were similar for comparisons with RTS,S/AS01Despite a high burden of malnutrition and malaria in the study populations, and a major reduction in the incidence of malaria in children receiving both interventions, this had only a modest impact on nutritional status. Therefore, other interventions are needed to reduce the high burden of malnutrition in these areas.Trial registration: https://www.clinicaltrials.gov/ct2/show/NCT03143218, registered 8th May 2017.The online version contains supplementary material available at 10.1186/s12936-022-04077-x. The malaria burden remains high in sub-Saharan Africa, with an estimated 228 million cases and 602,000 deaths in 2020 . Six of E malaria vaccine is one such possibility. Taking advantage of the vaccine’s initially high but rapidly waning protective efficacy, it has been suggested that RTS,S/AS01E could be used as a seasonal vaccine, with children who have been primed early in life given an annual booster injection shortly before each malaria transmission season, either in addition to or as a replacement for SMC . In 2018, the combined group had approximately 20% lower prevalence of wasting compared to both the SMC and RTS,S/AS01E groups [PRs 0.79  and 0.78  respectively] ], and in the combined group compared to both the SMC and RTS,S/AS01E alone groups in 2018  ] , compared to 4.82/1000 and 4.77/1000 in the SMC alone and combined groups, respectively. However, the confidence intervals were wide, reflecting the relatively small number of events, and all of the confidence intervals overlapped one.Over the three study years, 10 children were hospitalized due to a primary diagnosis of malnutrition, two in the SMC alone group, 3 in the RTS,S/AS01E plus SMC group over the three-year study, compared to children who were randomized to receive only one of these interventions. Children in the trial who received the combined intervention experienced around 60% fewer cases of clinical malaria, and around 70% fewer hospital admissions with severe malaria, compared to children who only received SMC alone or RTS,S/AS01E alone [The trial in which the nutritional data presented in this paper were collected measured a large reduction in cases of uncomplicated and severe malaria in the combined RTS,S/AS011E alone .E alone groups. There was an approximately 20% reduction in the prevalence of moderate wasting and the point estimate for the reduction in the prevalence of severe wasting in the combined group was at least 30% compared to the SMC alone or RTS,S/AS01E alone groups at the time of the end of malaria transmission season surveys in 2017 and 2018, when the study cohort was aged between 11 and 27 months and 23 and 39 months, respectively. However, no difference in the prevalence of moderate or severe wasting between the groups was found in 2019. This may be because there was a slightly lower overall prevalence of wasting in 2019, and the children had passed the age where there is typically the greatest burden of acute malnutrition. Additionally, it is possible that malaria is a less important cause of acute malnutrition in older children.The prevalence of wasting was lower in the first two years of the study in the combined group than in the SMC alone or RTS,S/AS01Acute malnutrition was also assessed through comparison of the prevalence of low or very low MUAC-for-age between the study groups, but there was no evidence of a difference in any of the years. The difference between the results for wasting and MUAC-for-age may be because MUAC is a less sensitive measure of acute malnutrition than weight-for-height, even when age is taken into account. There was some evidence of a difference in mean WHZ and MUAC-for-age z-score between the groups in all three years of the study, but the maximum difference for any of the comparisons was a difference in z-score of 0.12, which is not likely to be clinically relevant. No difference was found between the groups in mean weight or MUAC gain between the study years.E plus SMC trial, these trials generally had much higher incidence rates of malaria in the control groups because in the current trial, all groups received SMC or RTS,S/AS01E vaccine, or both, and were given bed nets. It is possible that malaria has a larger effect on acute malnutrition at higher incidence rates, when it is common for clinical malaria episodes to recur in a short time frame; this was not observed in our study because incidence rates were much lower.These results are in line with many previous malaria prevention randomized controlled trials that have found some effect of a reduction in malaria cases on acute nutritional status. However, there is a lack of consistency between these studies in terms of which specific measures of nutrition were affected by a reduction in malaria. For example, two trials of SMC in Boussé District, Burkina Faso and Kati District, Mali, with identical designs, observed some increased weight gain in children in the intervention group over one malaria transmission season, with one of the trials also finding evidence of a 21%  reduction in the risk of wasting and a 16% 95% CI 0.72, 0.99) reduction in the risk of being underweight in children who received SMC , 18. Add2, 0.99 rE or SMC alone groups.This study found no evidence that the reduction in malaria in the combined group had a beneficial effect on stunting. This is consistent with a recent literature review of observational studies and randomized control trials of malaria interventions that found limited evidence for an effect of clinical malaria episodes or parasitaemia on stunting or growth velocity . A commoE alone group in 2017, and compared to both single intervention groups in 2018. There is no obvious explanation for these results, particularly as there was no effect on moderate stunting in the same period and any non-specific effects of the interventions would have also likely been observed in the single intervention groups. This could be a chance finding given the number of comparisons undertaken. The repetition of this finding in the second year of the study  may be because stunting is, by nature, a long-term condition. Thus, a chance difference in low height-for-age z-score in the combined group may have persisted over these two years.While this study found no evidence of a difference between any of the groups in the prevalence of moderate stunting, mean height-for-age z-score, or mean gain in height, the point estimates for the prevalence of severe stunting were higher in the combined group compared to the RTS,S/AS01E alone group compared to the SMC alone and combined groups. It is possible that this difference arose through non-malaria effects of sulfadoxine-pyrimethamine , a benefit that the RTS,S/AS01E alone group would not receive, given the P. falciparum-specific effect of RTS,S/AS01E [Additionally, there was a modest increase in the incidence of clinically diagnosed malnutrition in the RTS,S/AS01,S/AS01E , 28. HowAcute and chronic malnutrition at the end of the malaria transmission season were common in this cohort of children, especially in the first year of the study when the children were the youngest. The prevalence of stunting, wasting and being underweight were largely similar in this study to the national nutrition estimates when comparing data from children of a similar age , 29. HowThough this was a large, well-powered study with a high prevalence of malnutrition and high incidence rate of malaria, a long follow-up period with high study retention and a large reduction in malaria-related outcomes in the combined group, the study had some limitations. The anthropometric measurements were only taken at one time point each year, at the end of the malaria transmission season. These measurements were taken during the period after the hunger season, where children gain weight following the harvest. It is, therefore, possible that the effect of the seasonal changes in acute malnutrition due to the hunger season are much larger than that of malaria infection, which may have hidden part of a smaller effect of malaria on acute malnutrition. Furthermore, it is possible that there could have been some measurement bias due to human error; while efforts were taken to ensure the anthropometric measurements were accurately recorded, there may have been some inaccuracy as the measurements were taken in large numbers of children in a field setting. Weighing children with their clothes on could have been an additional source of measurement error. Additionally, easy access to diagnosis and treatment of malaria in the study children when unwell, may have prevented prolonged infection and limited the potential effect of malaria on nutritional status.Despite a high prevalence of malnutrition and incidence of malaria in the study populations and a major reduction in the incidence of malaria in children receiving both interventions, this had only a modest impact on nutritional status that was not consistent across study years and different nutritional indices. Nutritional status among children in both countries was poor, and thus other interventions are needed to reduce the high burden of malnutrition seen in the study areas.Additional file 1: Figure S1. Prevalence of severe nutritional outcomes in study children Burkina Faso and Mali over the study period 2017-2019 (mITT population). Table S1. Difference in mean Z-scores for nutritional indicators between study arms in Burkina Faso and Mali at the end of the malaria transmission season surveys (mITT population). Figure S2. Cumulative distribution functions of weight-for-height and MUAC-for-age in study children between study arms over the study period 2017-2019, centred on the Z-score cut-off for moderate malnutrition (mITT population). Figure S3. Cumulative distribution functions of weight-for-age and height-for-age in study children between study arms over the study period 2017-2019, centred on the Z-score cut-off for moderate malnutrition (mITT population). Table S2. Difference in mean changes in anthropometric measurements between study arms in Burkina Faso and Mali at the end of transmission season surveys between 2017-2018, 2018-2019 and 2017-2019. Table S3. Test of interaction between country and treatment arm. Figure S4. Prevalence of key nutritional outcomes in study children between study arms  in Burkina Faso (a) and Mali (b) over the study period 2017-2019 (mITT population). Table S4. Prevalence and prevalence ratios of primary outcomes between study arms in Burkina Faso and Mali at the end of the malaria transmission season surveys (per protocol population).


Thrombocytopenia is the most common hematological abnormality in patients with acute malaria. This study aimed to determine the role of thrombocytopenia as a diagnostic marker for malaria in patients with acute febrile illness. P ≤ 0.05 was considered statistically significant.  A cross-sectional health facility-based study was conducted on 423 consecutively selected acute febrile patients at Ataye District Hospital from February to May 2019 GC. A complete blood count and malaria microscopy were performed for each acute febrile patient. ROC curve analysis was performed to calculate sensitivity, specificity, positive predictive value, and negative predictive value of platelet count in predicting malaria. A P. vivax and 18 (24.66%) were P. falciparum. The prevalence of thrombocytopenia among malaria patients (79.5%) was significantly higher than those in malaria negative acute febrile patients (13.7%), P < 0.001. About 67% malaria-infected patients had mild to moderate thrombocytopenia and 12.3% had severe thrombocytopenia. The ROC analysis demonstrated platelet counts <150,000/μl as an optimal cutoff value with 0.893 area under the curve, 79.5% sensitivity, 86.3% specificity, 95.3% negative predictive value, and 54.7% positive predictive value to predict malaria.  Out of the 423 acute febrile patients, 73 (17.3%) were microscopically confirmed malaria cases and the rest 350 (82.7%) patients had negative blood film results. Of the microscopically confirmed malaria cases, 55 (75.34%) were  Malaria is still among the major public health problems in the country. Thrombocytopenia is a very good discriminatory test for the presence or absence of malaria with 79.5% sensitivity and 86.3% specificity. Therefore, this may be used in addition to the clinical and microscopic parameters to heighten the suspicion of malaria. Plasmodium species. Globally, there were an estimated 228 million malaria cases and 405, 000 deaths in 2018, and 93% of the malaria cases and 94% of the deaths were in the African Region [Plasmodium falciparum and Plasmodium vivax [Malaria is a life-threatening infectious disease caused by protozoan parasites of the P. falciparum and P. vivax infections [Malaria parasite is a blood parasite that causes different hematological abnormalities such as anemia, thrombocytopenia, lymphopenia, monocytosis, eosinopenia, and rarely disseminated intravascular coagulation –9. Thosefections . The mecfections –16.There are some studies that reported the presence of thrombocytopenia is a predictor of acute malaria in patients with acute febrile illness in endemic areas –20. HoweP. vivax and P. falciparum are main plasmodium species responsible for malaria infection in the district.A cross-sectional health facility-based study was conducted at Ataye District Hospital from February to May 2019 GC. The Hospital is found in Ataye Town, Ataye District, North Shewa Zone of the Amhara Region, Ethiopia. Ataye Town is located at an elevation of 1468 meters above sea level and about 270 km away from the capital city Addis Ababa. Ataye District is one of the hot and malaria endemic areas in Amhara Region, Ethiopia. Malaria is one of the major health problems of the district. Among the plasmodium species, A total of 423 consecutively selected acute febrile patients were enrolled from Ataye District Hospital. Acute febrile patients with pregnancy, HIV, known hematological malignancies, bleeding disorders, and antimalarial therapy were excluded from the study.Plasmodium was detected in a minimum of 200 oil immersion fields. On thick blood smears, detection of any levels of asexual forms of malarial parasites was considered malaria-positive and if no parasites were seen after examining 1000 white blood cells labeled as negative. The blood smear examination and complete blood count were performed by two experienced medical laboratory scientists. These laboratory professionals had trainings on malaria microscopy. Standard operating procedures (SOPs) were strictly followed in each step to maintain the quality of the laboratory results.Semistructured questionnaires were used to collect sociodemographic and clinical data of the study participants by trained clinical nurses. A complete blood count (CBC) and malaria microscopy were performed for each acute febrile patient. Sysmex KX-21N  automated hematological analyzer was used to determine the complete blood count . Giemsa-stained thin and thick blood smears were used to diagnose malaria. Thin smears were considered positive for malaria if one or more malarial parasites were seen and negative if no asexual form of 3/μL. Thrombocytopenia was further classified into mild thrombocytopenia (platelet counts from 100 to 150 × 103/µL), moderate thrombocytopenia (platelet counts from 50 to 100 × 103/µL), and severe thrombocytopenia (platelet counts less than 50 × 103/µL) [Thrombocytopenia was defined as a total platelet count <150 × 10 103/µL) .t-test for continuous variables and the chi-square test for categorical variables to compare means and proportions. ROC curve analysis was performed to calculate sensitivity, specificity, positive predictive value, and negative predictive value of platelet count in predicting malaria. In all cases, a P value less than 0.05 was considered statistically significant.The data were entered and analyzed using a Statistical Package for the Social Science (SPSS) Version 20 statistical software. We used the Ethical approval was obtained from the Research and Ethics Review Committee of College of Medicine and Health Sciences, Wollo University. Permission to conduct the study was also obtained from Ataye District Hospital. Written informed consent from adult participants and assent for children under 18 years of age were obtained before enrolment into the study. To ensure confidentiality, participants' data were linked to a code number. Any abnormal test results of participants were communicated to the concerned body in the hospital.n = 143; 33.8%) were within 15 to 24 years of age. More than half of the study participants were females (54.8%) and rural residents (53%). About 24.8% of participants were illiterate and 25.8% were housewives. Thrombocytopenia was noted in 106 (25.1%) acute febrile patients. Fifty-four (12.8%) patients had mild thrombocytopenia, 43 (10.2%) had moderate thrombocytopenia, and 9 (2.1%) had severe thrombocytopenia , and most of the study participants (ytopenia .P. vivax positive and 18 (24.66%) were P. falciparum. There was no statistically significant difference in malaria infection between male and female acute febrile patients . Malaria infection was more prevalent in rural residents (22.8%) than urban residents (11.1%), (P = 0.002).Out of the 423 acute febrile patients, 73 (17.3%) were microscopically confirmed malaria cases and 350 (82.7%) had negative blood films . Of the P < 0.001). The prevalence of thrombocytopenia among malaria patients (79.5%) was significantly higher than those of malaria negative acute febrile patients (13.7%), P < 0.001. Regarding to the severity of thrombocytopenia, about 67% malaria-infected patients had mild to moderate thrombocytopenia and 12.3% had severe thrombocytopenia  than in P. vivax (3.6%) infected study participants. Most of the malaria negative acute febrile patients (86.3%) had normal platelet count , the optimum cutoff point of platelet count to differentiate malaria infection from acute febrile patients was less than 150 × 103/µl with sensitivity of 79.5% and specificity of 86.3%  of the platelet count was 0.893 , followed by P.falciparum (25%). This was in agreement with other studies [P. falciparum [Malaria is one of the high burden diseases in developing countries. Ethiopia is one of the sub-Saharan countries highly endemic to malaria where an estimated 68% of the population lives in malarious areas , 5. In t studies , 29, 30,lciparum , 28.Plasmodium infection. The association of thrombocytopenia and malaria infection was in agreement with previous studies [P. falciparum (83.3%) and P. vivax (78.2%) infected patients (P = 0.7482) which is similar to a study done by Kassa et al. [P. falciparum than P. vivax [P. vivax infected patients [In this study, mean platelet counts were significantly reduced in malaria-infected patients than those with nonmalaria. Thrombocytopenia occurred in 79.5% of malaria-infected patients. These findings imply that thrombocytopenia may be a marker of  studies , 31–33. a et al. . In contP. vivax  and Shaipatients –16. In cpatients . A studypatients . There apatients . In contpatients .μl as an optimal cutoff value with 79.5% sensitivity, 86.3% specificity, 95.3% negative predictive value, and 54.7% positive predictive value. The area under the curve of the platelet count was 0.893 which means thrombocytopenia is a good discriminatory test for the presence or absence of malaria. These values are very close to studies done in Thailand that found a sensitivity of platelet count <150,000/μl for diagnosing malaria to be 85%, specificity 85%, negative predictive value 97%, and the positive predictive value 48% [In this study, the ROC analysis demonstrated platelet counts <150,000/alue 48%  and in Lalue 48% . Our resalue 48%  and Tangalue 48% .Malaria is still among the major public health problems in the country. The prevalence of thrombocytopenia was significantly higher among malaria patients than malaria negative acute febrile patients in Ataye Hospital. Thrombocytopenia is a good discriminatory test for the presence or absence of malaria with 79.5% sensitivity and 86.3% specificity. Therefore, this may be used in addition to the clinical and microscopic parameters to heighten the suspicion of malaria.


Malaria in pregnancy can result in placental infection with fetal implications. This study aimed at assessing placental malaria (PM) prevalence and its associated factors in a cohort of pregnant women with peripheral malaria and their offspring.The data were collected in the framework of a clinical trial on treatments for malaria in pregnant women . Placental malaria (PM) was diagnosed by histopathological detection of parasites and/or malaria pigment on placenta biopsies taken at delivery. Factors associated with PM were assessed using logistic regression.Out of 745 biopsies examined, PM was diagnosed in 86.8 % of women. Acute, chronic and past PM were retrieved in 11 (1.5 %), 170 (22.8 %), and 466 (62.6 %) women, respectively. A modifying effect was observed in the association of gravidity or anemia at the study start with pooled PM . In women under 30, gravidity ≤ 2 was associated with an increased prevalence of pooled PM but in women aged 30 years or more, gravidity was no more associated with pooled PM . Anemia was associated with pooled PM in women under 30  but not in women aged 30 years or more . Similarly, the association of gravidity with past-chronic PM depended also on age. A higher prevalence of active PM was observed in women under 30 presenting with symptomatic malaria , while there was no significant increase in the prevalence of active PM (presence of parasites only) in women with symptomatic malaria when aged 30 years or more . In women with chronic PM, the prevalence of low birth weight or prematurity was the highest (31.2 %) as compared with past PM or no PM.P. falciparum peripheral infection in Nanoro, especially in younger women This underlines the importance of preventive measures in this specific group.Despite the rapid diagnosis and efficacious treatment of peripheral infection, the prevalence of placental malaria remained high in women with  Plasmodium falciparum  is the parasite responsible for a large majority of cases of malaria in the general population in Africa [P.falciparum erythrocyte membrane protein1 (PfEMP1) expressed by the parasite and coded by the var gene family. There are different types of this protein binding to various receptors on the endothelium of the blood vessels [P. falciparum[5]. However, the results are unclear as its activity seemed to be mediated through chondroitin sulfate [In 2019, 12 million pregnant women were infected by malaria worldwide. According to World Health Organization, more than one-third 35 %) of these infections occurred in the West-African region [5 % of thn Africa . Infecte vessels . Hyaluro sulfate , low bir sulfate –9 which  sulfate , 11.Pregnant women acquire protective immunity against PM as their ages increase. That is why younger pregnant women are more prone to PM than their older counterparts , 13. AlsWe hypothesized that the immunity related to age may influence the relationship between gravidity and other maternal characteristics and PM. While factors associated with placental malaria have been studied widely, there is little information on these potential interactions , 17–22. The current study aims to assess the prevalence of PM in Burkina Faso and to assess if factors associated with PM are depending on age.P. falciparum parasitemia whatever the presence of symptoms. However, women with symptoms and/or signs  of severe malaria were not included. Detailed methodology and study results were published elsewhere [The present study used data collected in the framework of a multicenter, randomized, open-label trial of treatments for malaria in pregnant women entitled: “safe and efficacious artemisinin-based combination treatments for African pregnant women with malaria (PREGACT)” which is registered under the number NCT00852423. The latter evaluated the efficacy and safety of four artemisinin-based combination treatments (ACT) in pregnant women with lsewhere , 26.P. falciparum peripheral infection, who were willing to give informed consent, were enrolled and treated with one of the four ACTs at random and followed up until delivery. All participants were provided a long-lasting insecticidal bed net upon inclusion.Briefly, second or thirdtrimester pregnant women with microscopically confirmed At inclusion in the parent study, obstetrical, medical, demographic, and anthropometric data were recorded. The use of malaria prevention methods before the inclusion in the study was documented. Peripheral malaria infection was confirmed and parasites density and species were determined by microscopic examination of thick and thin blood smear stained with Giemsa . HemogloThe cure of the initial episode was ascertained on the basis of a negative blood smear obtained at the end of the three days treatment course. Peripheral malaria parasitemia occurring after the this episodeuntil delivery was recorded.Delivery date and mode, gestational age, and newborn characteristics were collected. Also, a biopsy of the placenta was collected.2. Preterm birth was defined as a birth occurring before 37 weeks of gestation and low birth weight was defined as birth weight below 2500 g. The season at delivery was either rainy (July to December) or dry (January to June) [Biopsies pieces were collected from the maternal side of the placenta, as soon as possible after delivery and kept in a neutral buffered 10 % formalin. Subsequent procedures comprised embedment in paraffin wax, slicing in 4 mm thick sections, and staining with hematoxylin– eosin. Reading and classification of PM patterns were done according to the method described by Ismail. Acute PM infection was considered in presence of parasites and absence of malaria pigment. Chronic PM infection was considered in presence of both malaria parasites and malaria pigment. A past PM was considered in absence of malaria parasites but the presence of malaria pigment. No PM infection was considered when there were no malaria parasites nor malaria pigment . An exteto June) .The gestational age at delivery was calculated from the estimation done by ultrasonography at inclusion. The association of placental malaria with maternal characteristics was assessed using logistic regression. Only factors associated with PM with p-value < 0.05 in the univariate analysis were kept for the multivariate models. The modifying effect of age was assessed by introducing interactions in logistic regression. Interactions of age with the following maternal characteristics were considered: gravidity, anemia, symptomatic malaria at study start, recurrent malaria during follow-up, and season at delivery. When an interaction was statistically significant, the odds ratios of the association of these variables with placental malaria and their 95 % confidence intervals were estimated by age category. Outcome variables were either pooled PM, active PM, or past-chronic PM. Distribution of low birth weight (LBW) and prematurity by placental malaria status was also outlined.The statistical significance level was set at 0.05. All analyses were performed usingSTATA® statistical software version 16 .Only one woman was pregnant for the first time and this did not allow us to create a separate group of primigravidae.The PREGACT study was approved by the ethics committee of the University of Antwerp in Belgium and the National Ethics Committee of Burkina Faso. Written or witnessed thumb-printed informed consent was obtained from all participants before inclusion and any study procedure was undertaken. All the procedures of the study were carried out according to the guidelines of the ethics committees of Burkina Faso and Belgium that provided approvals.From June 2010 to April 2013, 870 pregnant women in their second or third trimester were recruited into the PREGACT trial at Nanoro and Nazoanga sites. Among the 847 women who delivered, 779 had a placental histology assessment. After excluding 13 twins and 21 stillbirths or malformations, the remaining cohort included 745 participants  women were under 30 years, 355 (47.7 %) had less than 3 previous pregnancies, 308 41.4 %) had symptomatic malaria, and 447 (74.2 %) had anemia  women. Parasites were seen in 181 24.3 %) of the placentas and malaria pigment in 636 (85.4 %). Acute, chronic, and past placental malaria was diagnosed in 11 (1.5 %), 170 (22.8 %) and 466 (62.6 %) women, respectively. . Anemia at enrollment was also associated with pooled PM in women under 30 years of age  but not in women of 30 years or more   of infected placentas compared to our study were reported in the same area in another multicentric study. This difference could be explained by the inclusion of both women with and without peripheral infection in the latter .Malaria parasites were found in 24.3 % (active infection) of the placentas in our study, while malaria pigment was present in 85.4 %. Malaria pigment could be a marker of peripheral parasitemia at the initial stage of the pregnancy, active infection reflecting more near-term intense peripheral infection , 32. It In our study, 13.2 % of the placentas were uninfected. Such discordance between peripheral and placental malaria was already reported in Nigeria. Authors attributed this to peripheral parasitemia of low density occurring at the beginning of the pregnancy , probablMaternal age , 37, 38,The association of gravidity, anemia at study start, and symptomatic malaria at study start with PM was modified by maternal age in our study.Placental malaria affects primigravidae or secundigravidae more than multigravidae , 18, 40.In our study, a higher prevalence of pooled PM was observed in anemic women aged less than 30 years. Infected red blood cells bind to the vascular walls in the bone marrow. This results in a lower production of red blood cells contributing to anemia , 44. In Undernutrition is one of the main causes of anemia through iron insufficiency in low and middle-income countries , 47 likePregnant women could benefit from iron and folic acid supplements without being exposed to an increased risk of malaria compared to those receiving folic acid only . HoweverSymptomatic malaria was associated with active PM in women aged less than 30 years of age in our study. Acquired immunity against malaria is weak in younger women and may be compared to that of women residing in regions. As a result, they may experience more clinical episodes , 56.Fever is the most common symptom in individuals infected by malaria. The presence of fever implies intense parasitemia above the pyrogenic threshold overpassing the tolerance capacity –59. ThisThe risk factors of placental malaria are not limited to the above-mentioned. They include environmental and socio-economic factors as far as the use of preventive measures against malaria. Indeed, placental malaria prevalence was higher in women delivering in the dry season compared to those delivering in the rainy season in a study conducted in Benin, Burkina Faso, and The Gambia . In Came, 56, 60 The present analysis had some limitations. The study was not designed primarily to assess factors associated with PM. Thus, we did not assess some factors like educational and socio-economic levels. This information was not captured in the database of the parent study.In the present study, we aimed at exploring the extent to which age could be associated with placental malaria. Thus, we chose 30 years as the cut-off, going beyond the usual cut-off of fewer than 25 years in most of the studies investigating the relationship between placental malaria and age . This coHowever, our study has several strengths. The participants were recruited at peripheral health centers, the first level of contact with the health system and this reduces the chances of a selection bias. The prospective design was also an advantage. Analysis exploring interactions of age with other maternal factors are more relevant to understanding how factors are associated with PM.P. falciparum infection in Nanoro, especially in younger women . This underlines the importance of preventive measures in this specific group.Despite the rapid diagnosis and efficacious treatment of peripheral infections, the prevalence of placental malaria remained high in women with peripheral