Plasmodium falciparum infections are common in sub-Saharan Africa, but their effect on subsequent symptomaticity is incompletely understood.Asymptomatic P. falciparum and subsequent symptomatic malaria with frailty Cox models.In a 29-month cohort of 268 people in Western Kenya, we investigated the association between asymptomatic Compared to being uninfected, asymptomatic infections were associated with an increased 1 month likelihood of symptomatic malaria , and this association was modified by sex, with females  at higher risk for symptomaticity than males . This increased symptomatic malaria risk was observed for asymptomatic infections of all densities and in people of all ages. Long-term risk was attenuated but still present in children under age 5 .P. falciparum can be quickly followed by symptoms and may be targeted to reduce the incidence of symptomatic illness.In this high-transmission setting, asymptomatic This work was supported by the National Institute of Allergy and Infectious Diseases . Plasmodium falciparum infections, defined as the presence of parasites in the absence of symptoms, are common across sub-Saharan Africa. In 2015, a geo-spatial meta-analysis estimated a continent-wide prevalence of asymptomatic P. falciparum in children aged 2 to 10 years of 24% based on microscopy and rapid diagnostic test (RDT) results  samples for post hoc molecular parasite detection. Symptomatic P. falciparum infections were detected using passive surveillance by testing people with self-reported symptoms with a malaria RDT  and collecting a DBS  from DBS and then tested in duplicate for P. falciparum parasites using a duplex real-time PCR (qPCR) assay targeting the P. falciparum pfr364 motif and human β-tubulin gene  both replicates amplified P. falciparum and both Ct values were < 40 or (ii) one replicate amplified P. falciparum and the Ct value was < 38.DBS were processed to detect lin gene . From eaParasite densities were estimated using standard curves generated from amplifications on each plate from templates of known parasite density. To generate these templates, parasite strain 3D7 was cultivated in vitro using standard conditions and the parasite density was estimated initially by light microscopy of Giemsa-stained slides and then by hemocytometer. For the latter, after averaging estimates of parasite density from five to six chambers, the non-diluted sample was diluted with fresh whole blood to obtain a 2000 p/μL stock solution. This was then serially diluted with whole blood to obtain 1000, 200, 100, 20, 10, 2, 1, 0.2, and 0.1 p/μL samples. Each of these was then prepared as a DBS of 30 μL volume, and from these gDNA was extracted as above for clinical samples. The result was a series of gDNA samples from mocked templates of known concentrations of 3D7 parasite that were processed identically to the clinical samples.P. falciparum infection during monthly active case detection assessments, defined as P. falciparum-positive by qPCR in a person lacking symptoms. People who were P. falciparum-negative by qPCR during monthly visits were considered uninfected. Participant follow-up was imputed for the first consecutive missed monthly visit during each follow-up period by carrying forward the previous month’s value as the exposure status of the missed monthly visit  and P. falciparum-positive by both RDT and qPCR. Outcome events occurring within 14 days of receipt of AL for a symptomatic infection were excluded.The main outcome assessed was days to symptomatic malaria. We defined symptomatic Some participants were classified as symptomatically infected at a monthly visit through passive detection of symptoms; this occurred if a study team member conducting a monthly visit was approached by a participant reporting malaria-like symptoms. The study team member would then perform an RDT and record information as for a passively detected sick visit. Symptoms were not routinely elicited during interviews on monthly visits. If the person met the case definition for symptomatic malaria, they were confirmed as having a symptomatic visit on that day and removed from follow-up until 14 days post-receipt of antimalarials or the next monthly follow-up visit. If that person did not meet our case definition for symptomatic malaria, then they were removed from follow-up for that month and re-entered for follow-up in the following month.Across all participants, we estimated the hazard of subsequent symptomatic malaria when infected with asymptomatic malaria compared to being uninfected at monthly visits. The hazard of symptomatic malaria was calculated for multiple follow-up periods: (i) 1 month, (ii) 3 months, (iii) 6 months, (iv) 12 months, and (v) 29 months (entire study period). For each follow-up period exceeding 1 month, exposure status was ascertained at every monthly follow-up visit and allowed to vary each month using a method proposed by We first estimated the time to symptomatic malaria across the full 29 months using Kaplan-Meier curves and the log-rank test. We compared differences in median time to symptomatic malaria across select covariates using the Wilcoxon rank sum test with continuity correction for dichotomous variables or the Kruskal-Wallis test for polytomous variables. The Bonferroni correction was applied to all table p-values to account for repeated measures during the 29 months of follow-up.In order to account for anticipated confounders of the relationship between asymptomatic infection and symptomatic malaria, we next computed a multivariate frailty Cox proportional hazards model .(1)h1(t)The model controlled for the following confounders as determined by a directed acyclic graph : age  or sex, computing hazard ratios and 95% confidence intervals (CI) of the main exposure, and comparing a Cox proportional hazards model with an interaction term between the potential modifier and main exposure to https://github.com/duke-malaria-collaboratory/time_to_symptomatic_malaria,  infections, we excluded all monthly follow-up visits occurring within 14 days prior to a symptomatic infection, reducing the possibility that pre-symptomatic infections could be misclassified as asymptomatic. The time frame for identifying potentially pre-symptomatic infections was chosen for consistency with previous work studying time to symptomatic malaria . The anaAsymptomatic infections defined as above were further classified as meeting a series of thresholds of parasite densities: any density, >1, >10, >100, >500, and >1000 parasites/μL. These classifications were assigned in a non-mutually exclusive fashion to asymptomatic infections, and then the 1-month likelihoods of symptomatic malaria relative to uninfected people were modeled separately using the Cox proportional hazards model in P. falciparum-positive by real-time PCR (qPCR). A ‘stringent’ case definition defined a symptomatic infection as one where a participant had a self-reported fever during a sick visit and was P. falciparum-positive by both RDT and qPCR. Additional sensitivity analyses were computed to investigate the separate effects of additional covariates by incorporating into the frailty Cox proportional hazards model in We computed sensitivity analyses to account for potential misclassification of the outcome of symptomatic malaria in the main models over 1- and 29-month intervals. A ‘permissive’ case definition defined a symptomatic infection as one where a participant had at least one symptom consistent with malaria during a sick visit and was The study was approved by institutional review boards of Moi University (2017/36), Duke University (Pro00082000), and the University of North Carolina at Chapel Hill (19-1273). All participants or guardians provided written informed consent, and those over age 8 years provided additional assent.For 29 months, we followed 268 participants from three villages in Western Kenya. After excluding participants with less than 2 months of follow-up, the analysis dataset consisted of 257 participants with a median of 222 days  of follow-up and a median age of 13 years  . OverallIn a univariate frailty Cox proportional hazards model, compared to uninfected people, the 1-month crude hazard ratio of symptomatic malaria for participants with asymptomatic infections was 2.69 (95% CI: 2.12 to 3.43). This association was similar in a model adjusted for covariates   as well In a subset analysis accounting for potentially pre-symptomatic infections, compared to uninfected people, the risk of symptomatic malaria was increased in those with asymptomatic infections by more than 1.7 times  when limited to those with events more than 14 days after exposure ascertainment . In thisNext, we assessed the relationship between asymptomatic infection and subsequent symptomatic malaria over longer follow-up periods. Extending the follow-up period led to a diminution in the risk of symptomatic malaria comparing those asymptomatically infected versus uninfected over 3 months , 6 months , 12 months , or 29 months  . In the We assessed for effect modification of the main exposure-outcome relationship by sex and by age in the main and pre-symptomatic models over various periods of follow-up . For ageOwing to the consistently elevated short-term risk of symptomatic malaria in people with asymptomatic infections, we investigated the effect of parasite density in these infections on the risk of subsequent symptomatic malaria within 1 month. Compared to uninfected people, the 1-month hazard of symptomatic malaria was significantly increased by asymptomatic infections of all parasite densities, with the highest risk for those with densities > 1000 parasites/μL  . This obP. falciparum infections and the risk of symptomatic malaria. In the short term, compared to uninfected individuals, people of any age with asymptomatic infections were associated with a more than twofold increased hazard of symptomatic malaria within 1 month. This elevated likelihood of symptomatic malaria was associated with asymptomatic infections at all parasite densities. As follow-up time was expanded, the association between asymptomatic infection and the increased risk of subsequent symptomatic malaria remained significant but attenuated. Collectively, our findings that detection of an asymptomatic P. falciparum infection confers an elevated risk of future symptomatic malaria supports the routine treatment of infections even in the absence of symptoms to prevent clinical cases.Using a 29-month longitudinal cohort in a high malaria transmission region of Kenya, we investigated the association between asymptomatic Previous studies that detected asymptomatic infections using microscopy also reported an increased short-term hazard of symptomatic illness among children within 9 to 30 days after having an asymptomatic malaria infection . We builP. falciparum parasites of any density is significantly associated with an increased risk of malaria in the forthcoming month and suggest that detection modality should not influence a decision to treat.Elevated risk of symptomatic malaria within 1 month was present for asymptomatic infections of any parasite density. We did observe a dose-response of the risk of symptomatic malaria as a function of parasite density, particularly among adults, but the risk of malaria was increased relative to uninfected people even when they harbored low-density infections. Prior studies observed conflicting relationships between asymptomatic parasite density and subsequent malaria: PCR-positive infections below the limit of detection of microscopy were not associated with subsequent symptomatic malaria in Ugandan children , but werWe observed significant modification of the relationship between asymptomatic infection and symptomatic malaria risk by sex. Specifically, despite an overall lower burden of symptomatic malaria among females that is consistent with prior studies , we obseWe observed that the increased risk for symptomatic disease associated with asymptomatic infection weakened as the follow-up length extended from 3 to 29 months, illustrated in both the multi-level models and Kaplan-Meier curves. One possible explanation for this observation could be inherent to the methodology whereby the magnitude of the average hazard ratio decreases as follow-up time increases . AlternaWe used a novel approach to capture how asymptomatic malaria varied over time. Most previous work used an intention-to-treat approach for asymptomatic infections identified in cross-sectional surveys ; howeverThis study had some limitations that should be considered when weighing the findings. First, asymptomatic infections were only captured at monthly follow-up visits, potentially missing transient asymptomatic infections between visits. By allowing participant exposure to vary over time, we assumed exchangeability between the exposed and unexposed groups. This was mitigated by the observation that approximately 94% of the study population changed exposure status at least once during follow-up. Finally, we estimated parasite densities using molecular methods and only at a single time point, though densities are known to fluctuate during infections. However, this potential bias in density estimations should be random and non-directional, and therefore mitigated by the analysis of over 1600 density measurements in asymptomatic infections.P. falciparum infections were associated with a high likelihood of being shortly followed by symptomatic illness across all ages and parasite densities. These results suggest interventions focus on treating and reducing asymptomatic malaria in high-transmission settings.In conclusion, using a novel exposure coding method and frequent sampling of both children and adults over 29 months, we found that asymptomatic  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Plasmodium falciparum infection at the baseline, compared to uninfected individuals.This study addresses an important topic with major public health implications: whether chronic, asymptomatic parasite carriage is associated with increased or decreased risk of subsequent episodes of clinical malaria in Africa. The authors followed up individuals exposed to intense malaria transmission in western Kenya. They used a novel analytical approach to assess the association between baseline asymptomatic infections and subsequent symptomatic malaria and found that the risk of disease is higher if someone carried asymptomatic Decision letter after peer review:Plasmodium falciparum infection on the risk of subsequent symptomatic malaria in a longitudinal cohort in Kenya" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Marcelo U Ferreira as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Cristian Koepfli (Reviewer #2).Thank you for submitting your article "Impact of asymptomatic The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1. How was the cohort assembled to support the representativeness of the participants for the general community?2. Which symptoms were asked about in the self-report, and what was the algorithm used to define a case as symptomatic or asymptomatic, over what time period?3. Was any participant classified as symptomatically infected at a monthly visit? If so what status were they given at that visit?4. How many participants were symptomatic, PCR positive but RDT negative, and therefore not treated? How did their clinical course, if any, compare with those who were also RDT positive and therefore treated?5. Was there any correlation by individuals in the same household?6. Are you able to control for spatial heterogeneity in risk, that could also help tease out whether superinfection has confounded your results?7. Please reconsider your suggestion of causality between asymptomatic and symptomatic infections.8. Were the time periods that occurred after an individual was treated for a symptomatic illness different than before they had an illness? I noted that treatment was not included in the models.9. Given that some parasite genotyping data are already available for this cohort, could the authors incorporate genotyping data in their analysis to distinguish between persisting infections that became symptomatic vs. superinfection with new strains?10. The authors ascertain the exposure status at every monthly follow-up visit, thereby treating each of these visits as a new study entry. It remains unclear whether this method is applicable for infectious diseases for which the risk of subsequent infections changes over time. The key question is whether this change is moderate or not over the time period considered. The stratification by age shows substantial changes over five year periods which is not that much more than a 29-month follow up. Please discuss whether these results are robust against the deviations from moderate time dependence.Reviewer #1:The "premunition" hypothesis postulares that individuals living in malaria-endemic areas gradually develop a form of clinical immunity characterized by the chronic carriage of low parasite burdens that reduces the risk of superinfection with more virulent strains and protects from full-blown disease . Whether this hypothesis holds in African settings with contrasting levels of transmission intensity remains unknown.Here, Sumner and colleagues provide evidence that, contrary to the premunition hypothesis, pre-existing asymptomatic infections at the baseline are associated with increased (rather than decreased) short-term risk of clinical disease in a cohort of 268 Kenyans exposed to intense malaria transmission and followed up for 29 months. This finding has major public health implications as it implies that treating asymptomatic infections  may reduce subsequent malaria-related morbidity.Sumner and colleagues use multivariate frailty Cox proportional hazards models to account for the repeated observations per individual – an interesting approach that has not been previously applied (to my knowledge) to the study of infectious diseases. One possible caveat is that the model does not account/correct for some degree of acquired immunity elicited by a previous infection diagnosed during the follow-up. For example, if the study participant is uninfected at baseline, asymptomatically infected during the first follow-up visit and again uninfected during the second follow-up visit, his/her level of "clinical immunity"  may have changed from the baseline (uninfected) to the second visit . This might be discussed in the manuscript.The key biological question underlying this study is whether chronically infected but asymptomatic individuals are more likely than their uninfected counterparts to develop clinical disease because pre-existing parasites eventually multiply and parasite density crosses the  "fever threshold", causing malaria-related symptoms, or, alternatively, whether these infected hosts are more likely  to be superinfected with more virulent parasite strains over the next few weeks and therefore develop clinical disease. Surprisingly, this question remains unaddressed in the present manuscript.P. falciparum infections in this cohort (doi: 10.1093/cid/ciab357). Molecular data suggest that the second hypothesis is correct: incident infections with only novel haplotypes were significantly associated with increased odds of subsequent symptomatic malaria over 14 months of follow-up (doi: 10.1093/cid/ciab357). Integrating these separately reported results in a single publication would render it much more appealing for the broad audience of eLife readers.However, the same authors have recently reported a detailed molecular analysis of incident In conclusion, Sumner et al. convincingly show that asymptomatic parasite carriage in a high-transmission setting in Kenya is associated with increased subsequent risk of clinical malaria, but the mechanisms underlying this association remain relatively unexplored in this study.Comments for the authors:This is a clearly written manuscript that addresses a topic of major public health significance. My only concern refers to the way the interesting results reported here are explored.The authors use a relatively new approach to survival analysis to show that carriers of asymptomatic malaria infections are more likely than uninfected individuals in the same populations to develop a clinical disease over the next month, although not necessarily over longer periods of follow-up. To this end, they excluded putatively "pre-symptomatic" infections, that were arbitrarily defined as those occurring within 14 days prior to a symptomatic infection. I see no clear justification for this 14-day time window.I would favor an alternative, more strict approach: excluding infections leading to clinical symptoms only if identical parasite haplotypes persisted since the first parasite detection until the clinical episode. This would provide evidence of "pre-symptomatic" infections. Combining changes in parasitemia over time would make the case even stronger. Quantifying the proportion of subsequent symptomatic infections associated with persisting haplotypes would provide an information of major biological and epidemiological interest and would allow us to test whether the arbitrary time window of 14 days is appropriate to rule out "pre-symptomatic infections". The authors have already genotyped a large proportion of incident infections in cohort participants (doi: 10.1093/cid/ciab357) but do not consider this rich dataset in their analyses.The exposure status of each study participant  was ascertained at every monthly follow-up visit and allowed to vary each month. This is an interesting approach that has been previously used in epidemiological studies of non-communicable diseases, but not of infections. The caveat here is that each new infection (either persisting or self-cured) may reduce the subsequent risk of malaria-related disease. Therefore, someone who is uninfected (at baseline), then infected (first follow-up visit) and again uninfected (second follow-up visit) has a similar "exposure status" during the second follow-up visit as someone who remained uninfected since the baseline evaluation, but this (mis)classification ignores acquired immunity gradually developed in response to each infection experienced by cohort participants, which may reduce the subsequent risk of infection and disease.Not surprisingly, the risk of disease following asymptomatic parasite carriage increases with increasing parasite density , but I wonder whether age-related fever thresholds may be observed in this population. Given that parasite density data are available, I suggest that a further analysis of parasite density levels associated with symptoms across age groups might provide some interesting insights into the biological/immunological mechanisms underlying the main study finding.Reviewer #2:1) At least three processes could potentially result in more frequent clinical infection following asymptomatic infection. First, the infection might be presymptomatic. Each clinical infection is preceded by a short period (a few days) of asymptomatic blood-stage infection. Second, chronic asymptomatic infections might increase in density though hitherto unknown processed, and cause clinical illness. Third, asymptomatic infection might be an indicator for higher exposure. Subsequent new infections might then result in clinical disease.Depending on the scenario, different control interventions are warranted. If asymptomatic infections develop into symptomatic infections, treating these infections will reduce the number of clinical cases. If they are a marker for higher exposure, vector control will be warranted.The first option was analyzed by a subgroup analysis . The results showed a surprisingly large difference between models, indicating that a large number of 'asymptomatic' infections was in fast presymptomatic.Scenario 2 and 3 could be distinguished by parasite genotyping, as a new infections will most likely be a different clone. Thus, genotyping would add substantially to the interpretation of the data. Given that the authors already have published genotyping results from a similar study , this should be straightforward. It might also help to understand better why some previous studies have found similar results as this one, while other studies have found contrasting results.2) Seasonality was not considered in the analysis, but might be important to understand the observations. For example, the finding that "a difference in the time to symptomatic malaria in the first few months post asymptomatic infection but not long-term" could be confounded by the fact that most transmission occurs in the wet season, and thus that the probability for both asymptomatic and clinical infection is higher in the wet season.3) Lines 52-54: It would be good to mention whether these estimates are based on microscopy or PCR. It would also be good to introduce the concept of supatent infections in the introduction, and discuss the possibility that even by PCR some infections were missed.4) Lines 188-189: While I like brevity, this section should be expanded, given its importance for the study. How many participants were never infected? How often was someone infected at a single time point? What was the duration of infections? Did you observe the sequence infected-non infected-infected, pointing to possible undetected infections at certain time points (in particular if the same clone was observed)?Likewise, given that age was an important variable, please provide more details on the age of clinical patients. A figure showing age trends in asymptomatic and clinical infections would be helpful.Reviewer #3:Sumner et al. report on a prospective cohort study of 254 participants aged 1 to 85 years living in three villages in Western Kenya. Participants gave monthly blood samples for testing by polymerase chain reaction (PCR) for parasite DNA and recorded any symptoms of illness during the previous 30 days from June 2017 through November 2019. Patients who reported symptoms of illness at any time were tested for malaria by rapid diagnostic test (RDT) and had blood samples taken for analysis by PCR. The study assessed whether asymptomatic individuals carrying malaria parasites were more likely, over the following time period, to have a symptomatic episode of malaria than people not infected with malaria. Using an analysis that treated each monthly visit as a new entry in the study, the time to symptomatic malaria or the end of the study was calculated and attributed to the status of the participant in that month (uninfected or infected but asymptomatic). Repeated measures on each participant were accounted for in the models using a random-effect measure at the level of participant.The researchers found that participants with asymptomatic infections developed symptomatic infections more quickly than those uninfected . There was a statistically significant difference in the hazard ratio comparing symptomatic malaria between asymptomatic infected and uninfected participants for periods from 1- to 6-months, but not at 12 months, after adjusting for covariates, with a decline in the hazard ratio over longer follow-up periods.These data add to the ongoing discussion about the importance and clinical relevance of asymptomatic malaria infections. There is widespread recognition that a substantial proportion of the human malaria parasite reservoir in malaria-endemic areas is found in people who do are asymptomatic, paucisymptomatic or afebrile. There is a debate, however, as to whether these infections are: a) the result of previous infections on their way to being resolved; b) chronic infections resulting from partial immunity to malaria; or c) new onset patent parasitemia appearing prior to the onset of symptoms. Additionally, the long-term outcomes of these infections, and their potential deleterious effects, have been the subject of debate. Such infections could: a) disappear without intervention; b) remain for long periods of time without causing harm; c) remain for long periods of time causing mild intermittent symptoms; or d) produce symptoms of illness that prompt healthcare seeking and treatment.The authors of this paper have taken great care in the design and analysis of the complex data gathered during this study, some aspects of which have been reported elsewhere . However, the authors' conclusion that asymptomatic infections should be treated with antimalarials because the asymptomatic infections themselves increase the risk of future symptomatic malaria is not fully supported by the evidence. The findings in this study could also result from superinfection, that is, if individuals with asymptomatic infections are more likely to be infected again, a new parasite strain could provoke symptoms of illness. If an asymptomatic infection serves as a marker of living in an area with a higher force of infection, then it would follow that such individuals are at greater risk of multiple infections. The development of symptoms associated with a new infection by a different parasite strain would, therefore, not be affected by treatment of a previous asymptomatic infection.There is already some suggestion in the report that symptomatic infections were associated with a higher force of infection. The study reported that time to symptomatic malaria was shorter for participants living in the village of Maruti. A previous paper reporting on entomologic indices in the study area showed that this village had the highest density of malaria mosquito vectors per household, and effectively the highest entomologic inoculation rate, compared to the other villages . Additionally, the previous paper reported that 41 individuals had more than 1 symptomatic infection, suggesting heterogeneity in transmission and force of infection.Additionally, it was surprising to see that age, which is generally a proxy for greater lifetime exposure to malaria and therefore a higher degree of partial immunity, did not modify the association between asymptomatic infection and subsequent symptomatic infection. This finding could also be explained by the symptomatic infections arising from reinfection with new strains of parasites more likely to cause symptoms.The strengths of the report lie in the use of a novel approach to time-varying exposure status (asymptomatic infection vs. uninfected) that avoided misclassification of person-time; careful statistical analysis of the data, including excluding post-baseline potential pre-symptomatic episodes; and relatively complete follow-up of a modest cohort of participants.The weaknesses in this paper, however, limit the paper's ability to conclude that asymptomatic infections should be treated to avoid symptomatic illness. In addition to the points mentioned above, the analysis did not control for the timing of episodes. Although not reported in this paper, the previous paper by this group suggests that the proportion of the cohort that had asymptomatic malaria infections at baseline was >50%. These baseline infections appear to be counted as asymptomatic infections although the length of time that these individuals had been infected was unknown. The authors could clarify whether these baseline asymptomatic infections were more likely to become symptomatic than asymptomatic infections that developed later, perhaps suggesting that many of them were presymptomatic.Comments for the authors:The paper is very well written and conceived, but I do not agree that the main conclusion is supported by the data.Comments on the statistical analysis:1. Line 105-107: missed monthly visits got an exposure status equal to the previous month's value – was any sensitivity analysis done?2. Line 107-109: why are people considered lost to follow-up and censored at the time of the imputed monthly visit; I would argue imputation is best not done in this situation3. Line 136-138: How do the authors account for repeated measures using a Bonferroni correction?4. Line 143-144; Equation 1: What is 5. Individual are clustered in households ; was this taken into account in the analysis? This would be very relevant for malaria. A nested frailty approach would be useful here.6. Throughout the text it would help to clarify which HR are referred to: conditional or unconditional (wrt the frailty). This can be briefly mentioned so that repetition is not needed. Essential revisions:1. How was the cohort assembled to support the representativeness of the participants for the general community?P. falciparum prevalence in 2013: Kinesamo (18.4%), Maruti (20.8%), Sitabicha (22.8%), Obala AA PloS One 2015;10(7)]. We have added some text to the methods to describe this:The cohort was assembled using radial sampling of 12 households per village for three villages within Webuye, Western Kenya. The first household in each village was randomly selected. The three villages were geographically close and chosen due to their high malaria prevalence in a previous cross-sectional study in the area  If that person did not meet our case definition for symptomatic malaria, then they were removed from follow-up for that month and re-entered for follow-up in the following month.”4. How many participants were symptomatic, PCR positive but RDT negative, and therefore not treated? How did their clinical course, if any, compare with those who were also RDT positive and therefore treated?In the primary analysis data set, we included 0 participants who were symptomatic, PCR positive, and RDT negative, because they did not meet our case definition for symptomatic malaria. Looking back at the original data set prior to any censoring criteria being applied, there were 6016 observations collected through monthly and sick visits and 183/6016 (3.0%) of them met the criteria of being symptomatic, PCR positive, and RDT negative. Subsetting the data set to only sick visits, 183/983 (18.6%) of sick visits were symptomatic, PCR positive, and RDT negative. Because this number was fairly few across a large number of participants and 29 months of observation, we have limited ability to make inferences about the natural history of malaria in RDT-negative/PCR-positive people; however, we did conduct a secondary analysis where we computed the hazard of symptomatic malaria using a secondary permissive definition for symptomatic malaria  to assess if alternative symptomatic malaria case definitions influenced results. Using the secondary permissive case definition for symptomatic malaria, we observed overall similar results to those produced using the primary case definition. We have added this to the main text:“We observed similar 1-month elevated risks of malaria in asymptomatically-infected people when using both the “permissive”  and the “stringent”  alternate case definitions for symptomatic malaria .”5. Was there any correlation by individuals in the same household?We chose to only include a random intercept at the individual and not household level due to the little impact correlation at the household level had on the relationship between asymptomatic/uninfected at monthly visits and subsequent symptomatic malaria. We assessed the possibility of using a nested frailty approach with random intercepts at the individual and household levels. To do so, we re-computed the frailty Cox proportional hazards model described in Equation 1 in the main text using a random intercept at the individual level and an additional random intercept at the household level. Results were similar for the 1-month hazard of symptomatic malaria for those asymptomatically-infected versus uninfected when a random intercept at the household level was included  versus excluded . Because including a household level random intercept had little impact on model results, we excluded it from analyses to be able to have model convergence to test effect measure modification of the relationship by age and sex.6. Are you able to control for spatial heterogeneity in risk, that could also help tease out whether superinfection has confounded your results?P. falciparum prevalence in 2013: Kinesamo (18.4%), Maruti (20.8%), Sitabicha (22.8%), Obala AA PloS One 2015;10(7)].We controlled for spatial heterogeneity in risk by including village fixed effects in the models. We do not expect spatial risk to be substantially different within and between villages due to the radial sampling of households, close proximity of villages to each other , and similar high malaria prevalence across the three villages …” We made similar changes in the Introduction, Results, and Discussion, each of which are tracked in the accompanying documents.8. Were the time periods that occurred after an individual was treated for a symptomatic illness different than before they had an illness? I noted that treatment was not included in the models.To test if prior treatment during the study period influenced results, we re-computed the frailty Cox proportional hazards model in Equation 1 with a covariate for prior treatment. To do so, we reran the frailty Cox proportional hazards model in Equation 1 with an additional covariate representing prior receipt of antimalarial treatment. This variable was coded dichotomously as having received study-prescribed antimalarials up until that monthly visit or not. For example, a person was coded as having not received study-prescribed antimalarials up until their first symptomatic infection, but afterward were coded as receiving treatment from that point forward in follow-up. Compared to primary models, antimalarial treatment had minimal effect on the hazard of symptomatic malaria when asymptomatically infected versus uninfected in the short-term  but made results largely null in the long-term .We have added to the methods section Sensitivity analyses:“For prior antimalarial treatment, we included a variable coded dichotomously as having received study-prescribed antimalarials up until that monthly visit or not; a person was coded as having not received study-prescribed antimalarials up until their first symptomatic infection, but afterward were coded as receiving treatment from that point forward in follow-up,” and the Results the general statement that “This association was similar in a model adjusted for covariates   as well as when using alternative modeling approaches, alternate outcome case definitions, and in sensitivity analyses.”9. Given that some parasite genotyping data are already available for this cohort, could the authors incorporate genotyping data in their analysis to distinguish between persisting infections that became symptomatic vs. superinfection with new strains?Clin Infect Dis 2021;ciab357], and we supplemented these 14 months of phase 1 with an additional 15 months from phase 2 for this analysis.Unfortunately, parasite genotype data are unavailable for more than half of the months of observation that we analyze here. Our recent analysis of parasite genotypes used data from the first phase of this cohort  suggested an association between the presence of new haplotypes in incident infections and an increased likelihood of symptomatic malaria; however, this relationship was overall null for persistent infections. We have referenced some of these results into the discussion:Results from that paper [Sumner KM “The increased short-term hazard could reflect misclassification of a “pre-symptomatic” infection that progressed to symptoms as an asymptomatic exposure . […] The increased hazard of symptomatic malaria could also have been due to the presence of new genotypes in infections (i.e. superinfection), although we previously reported that such newly-apparent genotypes were associated with symptoms only in previously-uninfected people .”10. The authors ascertain the exposure status at every monthly follow-up visit, thereby treating each of these visits as a new study entry. It remains unclear whether this method is applicable for infectious diseases for which the risk of subsequent infections changes over time. The key question is whether this change is moderate or not over the time period considered. The stratification by age shows substantial changes over five year periods which is not that much more than a 29-month follow up. Please discuss whether these results are robust against the deviations from moderate time dependence.To account for the gradual acquisition of immunity in cohort participants and subsequently time dependence, we have re-computed the models including a variable for the number of prior asymptomatic infections a person experienced in the study up until each monthly visit. To assess how the number of prior asymptomatic infections a person had during the study period could have influenced results, we re-computed the frailty Cox proportional hazards model in Equation 1 with a variable added for the number of prior asymptomatic infections each person had in the study up until each monthly follow-up visit. The covariate for number of prior infections was included as a continuous number in the model. We observed that the number of prior asymptomatic infections had little impact on the hazard of symptomatic malaria comparing those asymptomatically infected to uninfected in both the short-term  and long-term  compared to the primary models” Overall, we did not observe a large difference in the short-term or long-term results when accounting for the number of prior infections a person experienced, suggesting that the results were robust to deviations from time dependence.We have added to the methods section Sensitivity analyses:“For the number of prior infections, we included in the model as a covariate the number of prior infections as a continuous number,” and to the Results the general statement that “This association was similar in a model adjusted for covariates   as well as when using alternative modeling approaches, alternate outcome case definitions, and in sensitivity analyses.”Reviewer #1:[…] Comments for the authors:This is a clearly written manuscript that addresses a topic of major public health significance. My only concern refers to the way the interesting results reported here are explored.The authors use a relatively new approach to survival analysis to show that carriers of asymptomatic malaria infections are more likely than uninfected individuals in the same populations to develop a clinical disease over the next month, although not necessarily over longer periods of follow-up. To this end, they excluded putatively "pre-symptomatic" infections, that were arbitrarily defined as those occurring within 14 days prior to a symptomatic infection. I see no clear justification for this 14-day time window.I would favor an alternative, more strict approach: excluding infections leading to clinical symptoms only if identical parasite haplotypes persisted since the first parasite detection until the clinical episode. This would provide evidence of "pre-symptomatic" infections. Combining changes in parasitemia over time would make the case even stronger. Quantifying the proportion of subsequent symptomatic infections associated with persisting haplotypes would provide an information of major biological and epidemiological interest and would allow us to test whether the arbitrary time window of 14 days is appropriate to rule out "pre-symptomatic infections". The authors have already genotyped a large proportion of incident infections in cohort participants (doi: 10.1093/cid/ciab357) but do not consider this rich dataset in their analyses.We have updated the manuscript text to reflect why the 14 day (2 week) time window was chosen for the pre-symptomatic subset analysis:“The time frame for identifying potentially pre-symptomatic infections was chosen for consistency with previous work studying time to symptomatic malaria .”Unfortunately parasite genotype data are only available for less than half of the time period of this cohort. Additionally, incorporation of these complex deep-sequenced genotype data would vastly expand the scope and impact of this report, which is focused on the clinically-actionable aspects of the natural history of asymptomatic infections.The exposure status of each study participant  was ascertained at every monthly follow-up visit and allowed to vary each month. This is an interesting approach that has been previously used in epidemiological studies of non-communicable diseases, but not of infections. The caveat here is that each new infection (either persisting or self-cured) may reduce the subsequent risk of malaria-related disease. Therefore, someone who is uninfected (at baseline), then infected (first follow-up visit) and again uninfected (second follow-up visit) has a similar "exposure status" during the second follow-up visit as someone who remained uninfected since the baseline evaluation, but this (mis)classification ignores acquired immunity gradually developed in response to each infection experienced by cohort participants, which may reduce the subsequent risk of infection and disease.Addressed in Essential revisions #10 above.Not surprisingly, the risk of disease following asymptomatic parasite carriage increases with increasing parasite density , but I wonder whether age-related fever thresholds may be observed in this population. Given that parasite density data are available, I suggest that a further analysis of parasite density levels associated with symptoms across age groups might provide some interesting insights into the biological/immunological mechanisms underlying the main study finding.As suggested, we did an additional analysis assessing the 1-month hazard of symptomatic malaria comparing people with asymptomatic infections with parasite densities above a series of thresholds to people who were uninfected, stratified by people’s age groups . Among adults >15 years, we still saw a positive association between increasing parasite density in asymptomatic infections and a higher 1-month hazard of symptomatic malaria ; however, parasite density had less of an effect among children. We have added this analysis to the main text:“As an additional analysis, we repeated this process for each parasite density threshold stratified by participant age . This observed increase in the hazard of symptomatic malaria with increasing parasite density was most pronounced among adults >15 years ; however, children’s likelihood of symptomatic infection did not appear to be influenced by parasite density.”Reviewer #2:1) Seasonality was not considered in the analysis, but might be important to understand the observations. For example, the finding that "a difference in the time to symptomatic malaria in the first few months post asymptomatic infection but not long-term" could be confounded by the fact that most transmission occurs in the wet season, and thus that the probability for both asymptomatic and clinical infection is higher in the wet season.To investigate the effect of seasonality on our results, we re-computed the models including seasonality as a covariate. To investigate how seasonality could have affected results, we re-computed the frailty Cox proportional hazards model in Equation 1 while including a variable for seasonality. We classified monthly visits that occurred any time from May to October as the high transmission season and from November to April as the low transmission season, based on the region’s rainy seasons. With seasonality in the model, a high hazard of symptomatic malaria was observed among those that were asymptomatically infected compared to uninfected at monthly visits ; these results were similar to the main analysis presented in the manuscript using Equation 1, suggesting that the increased hazard of symptomatic malaria following asymptomatic infection was not solely attributable to seasonality.We have added to the methods section Sensitivity analyses:“For seasonality, we classified monthly visits that occurred any time from May to October as the high transmission season and from November to April as the low transmission season, based on the region’s rainy seasons.,” and to the Results the general statement that “This association was similar in a model adjusted for covariates   as well as when using alternative modeling approaches, alternate outcome case definitions, and in sensitivity analyses.”2) Lines 52-54: It would be good to mention whether these estimates are based on microscopy or PCR. It would also be good to introduce the concept of supatent infections in the introduction, and discuss the possibility that even by PCR some infections were missed.We have now added the specific malaria diagnostics used for the estimates:P. falciparum in children aged 2-10 years old of 24% based on microscopy and rapid diagnostic test results (RDT) .”“In 2015, a geo-spatial meta-analysis estimated a continent-wide prevalence of asymptomatic 3) Lines 188-189: While I like brevity, this section should be expanded, given its importance for the study. How many participants were never infected? How often was someone infected at a single time point? What was the duration of infections? Did you observe the sequence infected-non infected-infected, pointing to possible undetected infections at certain time points (in particular if the same clone was observed)?We have added some details to the first paragraph of results describing participant follow-up: “… person-months of asymptomatic malaria exposure; the median total months of asymptomatic exposure for a participant was 9 . Exposure status frequently changed for participants and remained constant for only 16 (6.2%) people across follow-up; 4 people were asymptomatically infected for the entirety of follow-up and only 12 people were never infected .”Likewise, given that age was an important variable, please provide more details on the age of clinical patients. A figure showing age trends in asymptomatic and clinical infections would be helpful.We have added more detail about the age of the participants to the main text and have added Figure 3—figure supplement 2 illustrating the age distribution: “… and a median age of 13 years  .”Reviewer #3:Comments for the authors:The paper is very well written and conceived, but I do not agree that the main conclusion is supported by the data.Comments on the statistical analysis:1. Line 105-107: missed monthly visits got an exposure status equal to the previous month's value – was any sensitivity analysis done?Lancet Infect Dis 2018;18(5)]. Imputing missed monthly visits added 715 observations to the primary analysis data set, with imputed monthly visits making up approximately 13% of the observations in the data set (715/5379).Our primary models impute missed monthly visits to have an exposure status equal to the previous month’s value. We chose this approach based on a previous paper that had employed this approach to study asymptomatic malaria over time  were similar to the results presented in the manuscript where imputation was performed ; notably, imputation produced estimates closer to the null of 1, suggesting that bias from imputation was towards the null.We have added to the Exposure and outcome ascertainment section “A sensitivity analysis was conducted for imputation using a dataset without imputation for missed monthly visits,” and to the Results “This association was similar in a model adjusted for covariates   as well as when using alternative modeling approaches, alternate outcome case definitions, and in sensitivity analyses.”2. Line 107-109: why are people considered lost to follow-up and censored at the time of the imputed monthly visit; I would argue imputation is best not done in this situation.Addressed above.3. Line 136-138: How do the authors account for repeated measures using a Bonferroni correction?p-values for Table 1 by multiplying each p-value by 29, which was the maximum amount of follow-up visits (and repeated measures) each person could have in the study.We applied the Bonferroni correction to all the table 4. Line 143-144; Equation 1: What is We have clarified the definitions for these terms in the main text:“We allowed the main exposure to vary each month based on the monthly follow-up visit infection status ; was this taken into account in the analysis? This would be very relevant for malaria. A nested frailty approach would be useful here.Addressed in Essential revisions #5 above.6. Throughout the text it would help to clarify which HR are referred to: conditional or unconditional (wrt the frailty). This can be briefly mentioned so that repetition is not needed.Throughout the main text and supplement, we have updated the HR abbreviation to indicate whether the unconditional, crude HR is being reported (cHR) or the conditional, adjusted HR is being reported (aHR). Models that produced an aHR always included a random intercept at the individual level.


Plasmodium and Haemoproteus. As a nonlethal disease, avian malaria can affect the lifespan and reproductive rate of birds. If there is a differential effect depending on bird species, then this disease might have a significant effect on avian biodiversity. The current study aimed to determine the incidence of Plasmodium in hummingbirds in humid premontane forest areas.Avian malaria is a tropical disease caused by protozoans of the genera Blood samples (n=60) were collected from hummingbirds from two areas (Santuario de Aves Milpe and Hacienda Puyucunapi) of Pichincha Province, Ecuador. Prevalence and parasitemia were determined by microscopic examination of blood smears stained with Giemsa reagent. Both study sites are part of a 1000 m elevational gradient; hence, elevation was used as a predictor variable for prevalence and parasitemia levels in a Mann–Whitney U-test. This test was also used to test for a sex bias.This study reports on a total of 12 bird species that inhabit both study sites. At Milpe, the lower elevation site, a prevalence of 100% was recorded, whereas at Puyucunapi, the prevalence was 96%. The combined prevalence was 97%. Elevation and sex did not influence prevalence nor parasitemia in hummingbirds.This study does not suggest a significant elevation or sex bias on prevalence and parasitemia in hummingbirds. Plasmodium and Haemoproteus are genera of hemosporidians, blood-borne protozoan parasites, and the etiological agents of malaria in birds [Plasmodium is a parasite transmitted by mosquitoes while Haemoproteus is transmitted by biting midges and louse flies [Plasmodium and Haemoproteus are paraphyletic, have a common ancestor, and share many biological features; therefore, they can be easily confused [Parasitism is a species interaction that is pervasive worldwide, with over 31,000 protozoan parasites already described and more than three-quarters yet to be reported. The research that has been conducted to date on protozoan species is usually tied to their medical and economic significance. Hence, species parasitizing mammals have been more widely studied than those parasitizing birds and reptiles . Avian min birds . At presin birds . Plasmodse flies . Plasmodconfused . For exaconfused .Haemoproteus is more diverse than Plasmodium except in South America, where Plasmodium is more prevalent and widespread [Plasmodium and Haemoproteus is explained in Plasmodium utilizes blood-sucking mosquitoes (Culicidae), while Haemoproteus utilizes biting midges (Ceratopogonidae) and louse flies (Hippoboscidae) [Haemoproteus meronts are only found in the internal organs of the vertebrate host, while Plasmodium parasites can be found in red blood cells as merozoites, meronts, and gametocytes [Leucocytozoon, the third genus of avian hemosporidian parasites; however, this genus is transmitted by blackflies (Simuliidae) and does not cause malaria but causes pathologies in birds [Leucocytozoon are not generally found in wild birds, as they are known to primarily affect poultry such as ducks and turkeys [Avian malaria has the potential to exert strong selective pressure on birds since it is frequently virulent . Some ofdespread . The prooscidae) ,10. Anotin birds . Moreove turkeys .Plasmodium and Haemoproteus. However, to date, hummingbirds have not been well studied with regard to avian malaria [Hummingbirds are birds of the family Trochilidae, which is endemic to the American continents and can be parasitized by both  malaria ,14. Ther malaria . Trochil malaria -18, alloThe aim of this study was to determine the degree of infection of hummingbirds by avian malaria in humid premontane. We chose two sites with a 1000 m elevational difference to test whether prevalence and parasitemia were different along the elevational gradient since the infection affects the reproductive rate of bird species . Given tThis study was approved by Mindo Cloudforest Foundation as it follows international guidelines, such as the Guidelines of the Use of Wild Birds in Research by the Ornithological Council. Blood samples were collected as per standard sample collection methods without any harm or stress to the hummingbirds.The samples were collected during October 2018-February 2020. Blood sampling was performed at two different reserves managed by the Mindo Cloudforest Foundation in Pichincha Province: The Milpe Bird Sanctuary located in San Miguel de Los Bancos  and Hacienda Puyucunapi located near Nanegalito . The study sites have a 1000 m elevational gradient. They have a similarly humid climate with an annual average temperature of approximately 16°C, an annual average relative humidity of 80%, and an average annual cumulative rainfall of approximately 2525 mm across both areas . MoreoveFor this study, all hummingbirds (family Trochilidae) were captured using mist nets. Birds were marked or their distinguishing characteristics were recorded such that recaptures were not resampled. First, each bird was weighed (g) and standard measurements, including exposed culmen, tarsometatarsus, tail, and wing length , were taSamples were stained with Giemsa reagent diluted 1:5 in phosphate-buffered saline at the laboratory at Yachay Tech University ,29. EachA Wilk–Shapiro test was performed to test for normality of the parasitemia data. Since normality was not supported, a non-parametric Mann–Whitney U-test was used to compare the independent samples from Milpe and Puyucunapi. This test is the non-parametric equivalent of the Student’s t-test. Both tests can be considered analogous since their main objective is to confirm or deny the existence of statistically significant differences between the two groups to be studied . In addiA total of 60 birds from 12 species of hummingbirds were captured at the two study locations. Of these, 47 were captured at Puyucunapi and 13 at Milpe. Therefore, the sample sizes used for statistical analysis were 60 (n=60), 47 for Puyucunapi  and 13 fHeliodoxa rubinoides species. In addition, the highest level of parasitemia was 9% which was found in Heliodoxa imperatrix  . Given tHaemoproteus infections are higher in hummingbirds than in passerine birds [There are few studies concerning the avian hemosporidians responsible for malaria in Latin America, Ecuador, included, with some reports in the Galapagos Islands -39. Therne birds ,10,40,41ne birds ,42.Haemoproteus infections in hummingbirds include Bradshaw and collaborators, who studied the presence and prevalence of Haemoproteus archilochus in two species of California hummingbirds, Archilochus alexandri and Calypte anna. Blood samples were mainly collected from three locations of Central California. A total of 261 specimens were sampled in 1.5 years. Their results indicate a relatively low H. archilochus prevalence with 4.76% in C. anna and 37.84% in A. alexandri [et al. [Haemoproteus spp.Some of the existing studies concerning  [et al.  in 2019.Haemoproteus and Plasmodium genera, was reported in 2014 by Harrigan et al. [et al. [Haemoproteus, Plasmodium, and Leucocytozoon at higher elevations and lower temperatures, hence supporting the results of the statistical analysis concerning elevation performed in the current study [et al. [Haemoproteus lineages from 50 hummingbirds from 11 species. Twenty-four individuals were also infected with Leucocytozoon spp., but none of the individuals were coinfected with Plasmodium. Moens et al. [Haemoproteus diversity and specialization were low in hummingbird species of the Ecuadorian Andes. Finally, the authors suggested that although Haemoproteus parasites are generalists, their prevalence was higher in hummingbirds than in birds that do not belong to the Trochilidae family. In addition, some studies show that hummingbirds are more susceptible to several pathologies, including avian malaria, because of their high metabolic requirements [The first report of avian hemosporidians in hummingbirds in Ecuador, from both the n et al. ; samples [et al.  found a nt study . Another [et al.  in Podocs et al.  showed tirements ,45. HencH. imperatrix with a parasitemia rate of 9% while the least parasitized species was Ocreatus underwoodii, with a parasitemia rate of 1%. The prevalence of Plasmodium in the two studied areas, Puyucunapi and Milpe, was high, at 96% and 100%, respectively, as expected for areas with a humid forest and the presence of bodies of water [This study reports on a total of 12 hummingbird species, two of which were from the Milpe area, which represents the lower elevation of the two examined sites. The most parasitized species in this region was of water -24. Thesof water .” In othof water ,42.et al. [et al. [Plasmodium and Haemoproteus in Central and South America was 25%, with the lowest prevalence reported in Colombia. The authors also found that Plasmodium prevalence increased at lower altitudes while Haemoproteus prevalence increased at higher elevations. This finding could support the slightly higher prevalence of Plasmodium spp. (100%) at the lower studied site, Milpe, compared to that of Puyucunapi (96%) in the current study. Finally, Cuevas et al. [Pulgarín et al.  sampled  [et al.  collectes et al.  performePlasmodium spp. parasites. However, they were not found in all samples. In general, the parasite stages found during the microscopic examination in this work were merozoites and meronts. Microgametocytes and macrogametocytes were not observed. As mentioned before (see Introduction), Haemoproteus meronts are only found in the internal organs of the vertebrate host, while Plasmodium parasites can be found in red blood cells in both sexual and asexual forms. Therefore, only gametocytes are usually observed in erythrocytes infected by Haemoproteus lineages [Haemoproteus parasites were not observed under the microscope in the parasitological diagnosis in this study despite it is usually more common than Plasmodium in hummingbirds [Haemoproteus gametocytes were not observed [In the current study, meronts were observed when examining blood smears to identify lineages ,10. For ingbirds ,10,40,41observed ,10.Plasmodium can also provoke pronounced decreases in red blood cell number, brain bleeding, and edema. The spleen and liver are also affected by this pathogen, leading to enlargement and even necrosis on some occasions. Nonetheless, birds that live in areas where malaria is endemic are usually not mortally affected, as is the case in both studied humid forest locations of Pichincha Province [H. imperatrix, an endemic species on the western slopes of the West Andes in Ecuador and Colombia, had a particularly high level of parasitemia in this study. Does this high level increase its risk of extirpation? Conversely, is a species with low parasitemia, such as O. underwoodii, any safer?Avian malaria goes from asymptomatic to lethal in domestic, wild, and captive birds ,47. TherProvince ,49. In aProvince . TherefoProvince ,52. H. iFinally, avian malaria was detected and diagnosed by microscopic examination of Giemsa-stained blood smears due to the advantages associated with this technique, such as its simplicity and low cost .Plasmodium being concentrated in South America. Hence, it is important to know the different effects of infections of these parasites on bird health and biodiversity, especially in hummingbirds, which are extremely diverse in Ecuador. The statistical analysis showed that there is not enough evidence to claim that the elevation parameter is directly related to avian malaria incidence in the current study. Either way, the outcome is consistent with the results of other studies performed in Ecuador and in Latin America. In addition, this study suggests that sex does not affect parasitemia as expected from the literature despite uniparental care of the chicks. Of the 12 bird species analyzed in this study, H. imperatrix is the species with the most elevated potential risk of extirpation due to its high degree of parasitemia. Therefore, understanding how avian malaria affects hummingbirds and what species are endangered by the disease is essential for the protection and conservation of Trochilidae.Avian malaria parasites have a worldwide distribution, with LMS: Conceptualization, formal analysis of the results, and writing the manuscript. LMS, MPT, and CSA: Collected samples. MPT: Contributed to the conceptualizations, identified the bird species, and revised the manuscript. CSA: Experimental assays, analysis of the results, and writing the manuscript. IRA and CSA: Performed statistical analyses. All the authors read and approved the final manuscript.


Research Topic also highlights an important key-ingredient of successful research: the extensive collaborations and multidisciplinary/transdisciplinary consortiums at the root of each activity.The recent endorsement of RTS,S/AS01 for broad use in children residing in regions with moderate to high malaria transmission is a key milestone in the fight against malaria . HoweverRamjith et al., 2022 developed mathematical models, presented power analysis considerations, and made an online tool to allow data analysis and sample size estimation when conducting trials for transmission-blocking interventions. The authors describe what data are needed for either an assessment of transmission-blocking activity or transmission-reducing activity and where power can be increased while considering the many confounders involved. The models seek to maximize the informativeness of future transmission-blocking intervention trials, and allow pre- and post-intervention comparisons.The complexity of the parasite lifecycle; gaps in our understanding on the interactions of the parasite and host; and the amazing capacity of malaria-infected red blood cell for immune subversion and immunosuppression  are highNunes-Cabaço et al., 2022 traced the history of the clinical assessment of whole-sporozoite malaria vaccines from its earliest concept in 1967. Several milestones were discussed, including the achievements in PfSPZ (Pf sporozoite) vaccine production and controlled human malaria infection (CHMI) studies. To date, PfSPZ vaccines seem highly protective in malaria-naïve adults but somewhat less active in African adults. First results from studies in infants and small children have been disappointing.KC et al., 2022). Several trials also show that antibody levels against sporozoites were not predicting protection per se, and that prior malaria exposure significantly resulted in lower antibody responses, even in females with higher antibody levels than their male counterparts.Sex has recently gathered attention as a variable that can influence immune response, vaccine efficacy and safety. Clinical trials of PfSPZ-based vaccines in the US, Germany, Kenya, Tanzania, Mali, Burkina Faso, and Equatorial Guinea showed that participants older than 11 years of age had sex-associated differences in vaccine-induced antibody response but no sex-related differences in protection   . PfRipr5 has been identified as a promising blood-stage vaccine candidate and is proceeding into clinical testing. The GMP-compliant recombinant protein was produced using the insect cells-baculovirus expression vector system and tested in pre-clinical model. Three human-acceptable adjuvant formulations tested head-to-head: Alhydrogel®, GLA-SE or CAF®01 showed comparable levels of anti-PfRipr5 antibodies. The highest functional activity by growth inhibition assay (GIA) was obtained in PfRipr5 with CAF®01.At the preclinical stage is another vaccine antigen, a fragment of Bougouma et al., 2022 reported the results of a phase Ib trial of the BK-SE36 vaccine candidate based on the serine repeat antigen-5 in 12- to 60-month-old children living in a malaria endemic area in Burkina Faso. The safety and immunogenicity of BK-SE36 were demonstrated in this age group for the first time. In general, the vaccine was safe and similarly immunogenic when given subcutaneously and intramuscularly; and as expected, subcutaneous vaccination led to more adverse events than the intramuscular route. The increase in IgG titers after vaccination was more pronounced in 12–24 months than in 25–60 month-old children, and a delayed third dose significantly boosted the immune response.Dassah et al., 2022). The study showed the importance of naturally acquired immunity; the influence of age and parasite threshold at which fever is triggered; and the relatively high pre-existing anti-merozoite antibodies in Burkinabe children.Looking for clues in a follow-up study after a Phase 2b multi-center clinical trial of the GMZ2 vaccine , in-deptde Jong et al., 2022 assessed antibody responses in two CHMI trials  to disentangle stage-specific signals and identify responses specific to sexual stage parasites vs asexual stage antibody response. The study provide insight into the humoral responses to two transmission-blocking vaccine candidates (Pfs48/45 and Pfs230) and identified new antigens that may be developed as markers for gametocyte exposure.CHMI is increasingly becoming an important tool for the clinical evaluation of candidate drugs and vaccines as well as a model to dissect the heterogeneity in immune response to malaria . The stuSalkeld et al., 2022 used CHMI in attempts to mimic the field observation of blood-stage malaria immunity acquired throughout several clinical episodes. After three homologous blood-stage CHMI, majority of the subjects did not show measurable functional anti-parasite immunity based on reduced parasite growth/multiplication rate but repeat infections did show boosting of antibody responses to MSP1 and AMA1. The work demonstrated the safety of repeated CHMI with no major differences in clinical symptoms or laboratory markers of infection across primary to tertiary challenges.P. falciparum are making progress, the highs and lows in P. vivax had come in trickles . The species is considered a key obstacle in malaria elimination (in vitro cultivation method that have largely restricted research efforts to develop interventions. Roobsoong et al., 2022 present the challenges of using P. vivax-CHMI, particularly the stringent and safe preparation of the parasites to be used, the logistics and limitations of sporozoite- and blood-stage CHMI of P. vivax.Last but not the least, while clinical trials against trickles , 7. P. vmination  because We hope that by highlighting progress, challenges and limitations in malaria vaccine clinical trials, this Research Topic will be useful in creating a shared vision that a malaria-free world needs concerted and evolving action.NP, AT, BM, and TT are the four editors of the Research Topic, wrote this editorial and approved the final version.


Malaria is an endemic disease in sub-Saharan Africa. In clinical practice, the main concern is the overdiagnosis of malaria leading to inappropriate drug prescription without laboratory confirmation.  This study aimed to evaluate clinical examination reliability compared with translational laboratory methods of malaria diagnosis.  The study was conducted in Goundi Hospital among hospitalized patients over a seven-month period. Patients were interviewed, and malaria tests done included the Giemsa-stained thick and thin blood smears. Diagnostic accuracy was analysed by calculating sensitivity, specificity, and predictive values. μL. The threshold pyrogen of the parasitic density was around 10.000 parasites/μL for patients between 0 and 11 months of age, between 1 and 4 years of age, and between 5 and 14 years of age. This threshold was lower for patients over 15 years of age. The study reported some issues in the findings: 60.88% (607/997) cases of fever without positivity of the blood thick smear and 40.13% (284/674) cases of positivity of the thick drop without fever. The positive predictive value of malaria was between 80 and 85% for patients under 5 years of age. This value is lower for patients between 5 and 14 years of age and patients over 15 years of age.  Among 1,874 participants, 674 (35.96%) patients had positive Giemsa-stained thick blood films. The rate of positivity is higher for patients under 5 years of age. The parasite densities were between 160 and 84.000 parasites/ A presumptive diagnosis of malaria should be confirmed by the laboratory in all suspected cases in all possible scenarios. Every parasitemia should be followed by the calculation of parasitic density. However, for the children under 5 years of age in areas of high transmission, the presumptive diagnosis of malaria in certain circumstances could be considered. In 2019, there were 229 million cases of malaria globally and 405,000 deaths despite massive efforts for malaria control . In accoThe Integrated Management of Childhood Illnesses (IMCI) approach advocates caregivers to combine these symptoms and signs to come up with a relevant approximation regarding the diagnosis of malaria . UnfortuA tough impediment to evidence-based management of malaria is the availability of laboratory confirmation in deprived healthcare settings. However, the launch of malaria RDTs comes up with a solution to this challenge. RDTs are more reliable, easy-to-use, and cheaper diagnostic tests. RDTs have a good sensitivity, require minimal training, and keep their accuracy even after substantial storage under tropical conditions. The performance of RDTs is comparable to that of expert microscopy according to relevant studies , 11.The health system in Chad is a pyramid system with three  levels oThe role of the central level is to design and guide health policies. It is responsible for mobilizing and coordinating national and international resources, supervising, evaluating, and controlling the implementation of national and intermediate level programs. It is made up of referral hospitals and training centers.The intermediate level is responsible for coordinating the implementation of the national health policy and provides technical support at the peripheral level. It is made up of regional hospitals and training centers.The peripheral level is responsible for the execution of the activities of the Complementary Package of Activities  and the Minimum Package of Activities  and constitutes the operational level of the national health policy.A meaningful study  performeIn an attempt to provide a contribution to this debate in our context, this study conducted in Chad aims to rationalize the diagnosis for a good management of malaria for patients at Goundi Hospital. For this reason, the study determines the prevalence of malaria in patients hospitalized at the hospital, then establishes a correlation between the level of parasitemia and the clinical symptoms of the malaria crisis, and confirms the cases of presumptive malaria by parasitological examination.This study was conducted over a duration of seven months from June 1, 2011, to December 31, 2011, in Goundi Hospital. There is a high transmission of malaria between September and December, hence more malaria cases that would concurrently lead to high misdiagnosis.The Goundi district hospital consists of a district hospital  with a cOur study was carried out at the Goundi Hospital. Goundi Hospital is a district hospital, located in the south of the country, in the Mandoul Oriental Region, 657 km from the Chadian capital (N'Djamena). The statutory policies that govern it assign three objectives: to provide curative care, to provide preventive care, and to promote the training of health workers.Research participants were hospitalized patients of all ages and genders from all four departments of Goundi Hospital including the intensive care unit, the post-intensive care unit, the infectious disease unit, and the gyneco-obstetric unit.Hospitalized patients who had not received any antimalarial treatment in the two weeks prior to hospital admission, and who had consented to participate in this study, were included. Only the first admission of a patient was included in the study.We have excluded patients who were not hospitalized during the period of the study. Patients who had received antimalarial treatment from another healthcare facility or by automedication during the two weeks prior to their hospitalization, during the study period, were excluded. We have excluded patients who had not consented to participate in the study. Second and subsequent admissions of the same patient were also excluded.The study was conducted in accordance with the Declaration of Helsinki (1964). Hospital management and all clinical department heads in hospitals were briefed about the study protocol, data collection tools, and details of planned blood investigations. The study was conducted after authoritative ethical approval from a local institutional research body—hospital committee, including senior management and clinical departmental heads. The research participants were informed about the purpose of the study, along with the planned laboratory tests. Informed oral consent was taken after a briefing about the purpose and protocol of the study. Privacy and confidentiality regarding information were assured to patients and or family. Only the primary medical team, involved in the patient's direct care, was given access to patients' blood results for the continuation of medical care. Once patients had consented to the data collection, the laboratory investigation, and the disclosure of data to the primary treating team, they were allowed to participate in the study. In the case of children, parents were briefed as above. The parent's consent was obtained, and information was collected from parents and/or the children's families. In the case of seriously ill or incapacitated patients, consent was taken and data were retrieved from their next of kin.Patients and/or their next of kin were updated about planned laboratory tests. Basic information was collected through well-designed data collection sheets through direct interviews with the patients or their next of kin. The data collection sheet included information regarding age, gender, fever, referral, health center, and its distance. Laboratory results included thick blood smear/drop and parasite density.We used a thermometer to measure the temperature: a rectal temperature threshold of 38.0°C, which was used as a cutoff point for fever , 14 in cμl volume of blood for thick film and 2 μl for the thin film. Once the thin smear is fixed with methanol, the thin and thick blood smears were stained with Giemsa.Two blood slides were used for each sample that arrived at the laboratory. Each of the slides had a 6 The 10% Giemsa stain was used to stain for 15 minutes on one of the two slides for the first slide reading, and the results were sent to physicians for patients' management. The second slide stained with 3% Giemsa for 60 minutes was given to two independent malaria microscopists. A positive smear was associated with each new cluster of working Giemsa stains, for quality control.The Giemsa-stained smear was first screened at a low magnification (10X × 40X objective lens) to detect suitable fields with even distribution of white blood cells (WBCs) (10–20 WBC/field) , 18. ComPlasmodium falciparum parasites were counted per 200 or 500 leukocytes; this was done to estimate the parasite density per microliter of blood.Smears were afterward examined using X100 oil immersion. At least 100 high power fields were examined before a thick smear was confirmed negative. Plasmodium parasites was counted against 200 WBC on the thick film. Parasite densities  were then calculated as follows: (number of parasites counted/WBC counted) × WBC count/μL of patient [Positive slides were subjected to the parasite density calculation. Parasite densities were reported as a ratio of parasites to WBC in thick films; this gave us the number of parasites per microliter of blood. The number of  patient .This study's primary interest is the diagnostic accuracy of malaria tests with positive thick and thin smear results and parasite density for malaria. A secondary interest includes the significance of testing parasite density.The independent variables include demographic factors such as age group and gender. The clinical profile includes the reporting of fever symptoms and the distance of referral health centers from the study site.a) are defined as the number of febrile patients with a positive thick drop. True negatives (TN/d) are the number of afebrile patients with a negative thick drop. False positives (FP/c) are febrile patients who have a negative thick drop, and false negatives (FN/b) are patients who are afebrile with a positive thick drop. Sensitivity was calculated as TP/(TP + FN). Specificity was calculated as TN/(TN + FP). The positive predictive value (PPV) was calculated as TP/(TP + FP) and the negative predictive value (NPV) as TN/(FN + TN). McNemar's test was used for further analysis to compare the sensitivities and specificities for evaluating diagnostic tests and presumptive malaria.Data were manually entered into the Microsoft Excel 10 system. Exhaustive data quality control was carried out by the reviewers to ensure the data's correctness and completeness before analysis. The results are expressed in terms of number and percentage. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio were calculated for both thick smears with Giemsa stain and checked for their association with independent sociodemographic and clinical variables. True positives  of parasite density to estimate the scattering of the parasite densities for each age group [Q1, Q3, and Q3) are the parasite densities that divide the ordered parasite densities observed in our sample into four equal groups.We calculated the quartiles (ge group . The quaQ1) is defined as the middle number between the smallest number (minimum) and the median of the data set. It is also known as the lower or 25th empirical quartile; that is, 25% of the data are below this point. The second quartile (Q2) is the median of a data set; thus, 50% of the data lie below this point. The third quartile (Q3) is the middle value between the median and the highest value (maximum) of the data set. It is known as the upper or 75th empirical quartile; that is, 75% of the data lie below this point.The first quartile  . The mosA total of 1618 (86.34%)  patientsThe combination of fever and positive thick drop was predominant in children as follows: between 0 and 11 months of age and between 1 and 4 years of age, with, respectively, 85.10% (120/141)  and 80.3p value of the McNemar test was <0.000001, we rejected the null hypothesis that the difference in results is not significant. There was a significant difference between the positivity rate and the negativity rate between the two tests. Hence, there is a significant difference between having a peripheral blood smear-positive and presumptive malaria diagnosis. The McNemar test calculated 116.37 with a p value of <0.000001.The McNemar test was used to analyze two variables: the thick peripheral blood smear and the presumptive diagnosis based on fever. Since the µL. The remaining 439 (65.13%)   cases wi(65.13%)  patients(1). Position Parameters (Median) and Dispersion Parameters (Quartiles). The position of the median was within a threshold of significant parasitemia  (000P/μL)  for the There were about 1/3 of cases present with very low parasitemia at 0–11 months . The traThe parasitic dispersion for the age group between 1 and 4  showed o3. It was the remaining one third who had parasitemia that had entered the clinical threshold for severe malaria. Simultaneously, three fourths of patients over 15 years of age , while the remaining 256 (13.66%) patients came from other towns. This is consistent with the latest statistics from the hospital, which has reported the number of out-of-district hospitalized patients fluctuating between 11 and 13% for the last decade. Patient's trust and healthcare access to Goundi Hospital for inpatient care were justified possibly because of the quality of health service delivery with trained and experienced nursing and medical staff; the availability of inpatient and emergency services and diagnostic services; and subsidized services for the patients.This study reported that 53.20% of the study participants (997 of 1874 patients) had fever. Based on this result, and just by performing a thick drop without even the parasite densities count, the presumptive diagnosis of malaria taking fever as the main argument would be a serious malpractice without any laboratory test for confirmation. According to the study of Bisoffi Z , not allThis study reported 35.96% (674) of patients with a positive thick blood smear. Our study result was lower than that found by Tuasha N. et al. in 2019  in EthioOur results argue in favour of the principle that the presumptive diagnosis of malaria in areas with high malaria transmission can only be applied to children between 0 and 4 years of age and during the rainy season . For ado3, which made an analysis/interpretation complex. The literature [The parasite density was too fluctuating in our study. The parasite density varied from 160 to 84,000 parasites/mmterature  sets a pterature  in 2006 The presumptive malaria diagnosis will be of immense value only if confirmed by laboratory examination. The postulate of fever as a diagnosis of malaria is far from the truth. The positive predictive value of fever as an indicator of malaria is 80 to 85% for children under 5 years old. After 5 years, it falls to lower levels. For the other age groups, a whole clinical set is needed and, if possible, a biological examination corroborates the diagnosis. This would prevent overprescription of antimalarials and reduce the rising resistance to drugs created by indiscriminate and unjustified use of antimalarial drugs. Considering the cost of rapid diagnostic tests, the test that appears to be the most cost-effective from an economic standpoint is a microscopic diagnostic test. An effort must be made by the healthcare workers to redefine this examination properly. Failure to quantify parasite density makes interpretation of the test difficult. The interpreted result without quantifying the parasite density exposes a risk of overtreatment. We noticed in this study a large number of patients who had a basal parasitemia (65.13%). Weak parasitemia may be accompanied by low gametocyte load that fuels transmission; thus, it is critical to treat infection regardless of parasitemia. The behavior encountered in practice among caregivers is a positive microscopic malaria test equals the prescription of an antimalarial. This habit of prescribing does not correlate with medicine-based evidence practice.


ATP2B4 as a severe malaria resistance gene. Recently, 8 potential causal regulatory variants have been shown to be associated with severe malaria.Genome-wide association studies have identified ATP2B4 gene containing the remaining SNPs was sequenced. Logistic regression analysis was used to assess the association between the SNPs and mild malaria.Genotyping of rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452 was performed in 154 unrelated individuals . rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays, whereas the fragment of the The results showed that mild malaria was associated with rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452. The homozygous genotypes for the major alleles were associated with an increased risk of mild malaria. Furthermore, the haplotype containing the major alleles and that containing the minor alleles were the most frequent haplotypes. Individuals with the major haplotypes had a significantly higher risk of mild malaria compared to the carriers of the minor allele haplotype.ATP2B4 polymorphisms that have been associated with severe malaria are also associated with mild malaria.The online version contains supplementary material available at 10.1186/s12936-023-04503-8. Plasmodium falciparum. Host genetic factors have been shown to explain between 20 and 25% of the variations in P. falciparum malaria phenotypes [Plasmodium falciparum can cause asymptomatic infections, mild malaria, or severe malaria, including severe anaemia and cerebral malaria. Genome-wide genetic linkage analyses and genome-wide association studies have been carried out to map genes involved in the control of blood infection levels, mild malaria or severe malaria [Malaria remains one of the most common infectious diseases. According to the World Health Organization (WHO), the estimated number of cases and deaths in 2020 were 241 million and 627,000, respectively [ malaria .ATP2B4 gene. Other GWAS and candidate gene studies conducted in Burkina Faso, Cameroon, Gambia, Kenya, Mali, Malawi, or Tanzania confirmed the association of the ATP2B4 gene with severe malaria [ATP2B4 gene encodes for PMCA4, which is the main calcium pump in erythrocytes. Also, it has been hypothesized that genetic variation within ATP2B4 disrupts the homeostasis of intraerythrocytic calcium concentration and thus, affects the development and structure of intraerythrocytic stages of the parasite [ATP2B4 genetic variation is associated with parasitaemia and mild malaria attack, which is caused by parasitaemia above a clinical threshold [ATP2B4 single nucleotide polymorphisms (SNP) with parasitaemia or mild malaria.A large genome-wide association study (GWAS) conducted by Timmann et al.  in Ghana malaria , 15, 16.parasite . Thus, ihreshold . There wATP2B4 [Most of the genetic association studies reported an association of severe malaria with the tag SNPs rs10900585 or rs4951377, which are in strong linkage disequilibrium with each other. The SNPs rs10751450, rs10751451, and rs10751452 that are in linkage disequilibrium with these tag SNPs were found to influence the expression of ATP2B4 , suggestATP2B4 . FurtherATP2B4 .The study aim was to assess the association of the tag SNP rs10900585 and the recently identified regulatory SNPs with mild malaria (MM) in a Senegalese population. Here evidence of an association with mild malaria both at the SNP and haplotype levels is reported.Mild malaria patient samples (n = 75) were taken at the Principal Hospital of Dakar and the regional hospital of Tambacounda in Senegal on the day of hospital admission , whereasThe control individuals were blood donors who did not have any malaria infection (as determined by microscopy) or any other febrile illness, selected at the same period of enrolment. Selected healthy individuals were medically followed by the National Transfusion Center or Hospital Principal more than two years with biological analyses every three months. Only samples from aparasitaemic donors were included in this control group. It should be stressed that the control individuals cannot be considered resistant individuals, since they may be unexposed and uninfected at the time of sampling. The allele and genotype frequencies within the control population rather reflected those within the general population.P. falciparum infection was determined by an immunoassay enabling the detection of pfHRP2 . According to WHO recommendations, for all subjects, P. falciparum parasitaemia was measured by examination of Giemsa-stained blood smears using a magnification × 1000 and by establishing the parasite count per 1000 leukocytes. To obtain reliable results, each slide was examined by two biologists and the mean of the two results was calculated when the difference between them was low. If there was a big difference between the two counts, a third reading was done to reduce the possibility of discordance, and the mean was calculated. The detailed procedure has been described previously [P. falciparum parasitaemia; the median of parasitaemia was 6516 parasitized red blood cells/μl . MM patients did not show any evidence of impaired consciousness or seizures before and at the time of enrolment. They were surveyed for the two weeks following their enrolment, and there was no case of impaired consciousness or seizures. Blood samples were obtained on the day of hospital admission. The institutional research ethics committee of the University Cheikh Anta Diop approved the study.All the clinical cases were defined according to WHO criteria . For theeviously . MM patiATP2B4 gene containing the polymorphisms was amplified by PCR with 5 μL of whole genomic DNA, 25 μL of Master Mix GoTaq G2 Hot Start  according to the manufacturer’s instructions and 3 μL of a mixture of primers sense F: 5′TCAGGCCTAGCTATCAGTTCAG 3′ and antisense R: 5′ CGAGTAGCCGTCCGAAGTC 3′ of 10 μM each. The amplification was carried out in Mastercycler  following 35 cycles with a Tm of 60 °C. After amplification, the PCR product was checked on 1.5% agarose gel. The amplicon was then further purified with QIAquick PCR Purification Kit  following the manufacturer’s instructions. Sequencing was performed by GATC  from 5 μL of PCR product (20–80 ng / μL) and 5μL of F primer at 5 μM. The chromatograms were read with Chromas 2.6.5 software .Genomic DNA was extracted and further amplified as described . rs10900rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays  respectively. Each reaction well was added with 1.84 μl of H2O, 2.1 μl of 2X Taqman master mix, 0.06 μl of Taqman probes and 1 μl of DNA (10–15 ng/μl). Amplification was performed with polymerase activation at 95 °C for 10 min, followed by 40 cycles of denaturation  and annealing/extension . After amplification, allelic identification was performed by the integrated software of the Quantstudio 6 Flex System .SPSS  was used to perform data analyses. All the tests were two-tailed. Chi-squared test was used to compare control and patient groups for gender and ethnic groups. Mann–Whitney test was used to compare the age of the controls with that of patients. Logistic regression method that allowed us to take into account potential confounding factors was used to perform genetic association analyses. The Nominal P values, the Odds ratios (OR) and their 95% confidence interval (CI) were calculated. Moreover, the FDR method was used to correct for multiple tests . GeneticATP2B4 promoter [For all the SNPs including the tag SNP rs10900585) and 8 potential candidate variants , the observed genotype frequencies in the control group conformed to the Hardy–Weinberg equilibrium . Additional file 0900585 apromoter .Table 1AThe association of the variants with MM was assessed using a logistic regression model. The subjects carrying the homozygous genotype for major alleles were compared with those carrying either the heterozygous genotype or the homozygous genotype for minor alleles, as shown in Table This analysis focused on the potential functional variants. First, a haplotype analysis was conducted under the dominant model, which combined rs11240734, rs1541252, rs1541253, rs1541254 and rs1541255. In all, 3 haplotypes were observed with various frequencies ranging from 0.025 to 0.570 in the control group  (r-squared) map for the ATP2B4 variants in the studied population. r-squared values ranged from 0.83 to 1. r-squared values were equal to 1 for the haplotype block containing rs11240734, rs1541252, rs1541253. Table S1. Characteristics of study subjects. Table S2. SNP minor allele frequency in the study population and in other African populations. The position is the position on chromosome 1 according to human hg38 coordinates. Table S3. Genetic association results under the genetic dominant model. Haplotype contains the studied SNPs but rs10900585, which is not functional. Table S4. Genetic association results under the genetic additive model. Haplotype contains the studied SNPs but rs10900585.