Severe falciparum malaria has substantially affected human evolution. Genetic association studies of patients with clinically defined severe malaria and matched population controls have helped characterise human genetic susceptibility to severe malaria, but phenotypic imprecision compromises discovered associations. In areas of high malaria transmission, the diagnosis of severe malaria in young children and, in particular, the distinction from bacterial sepsis are imprecise. We developed a probabilistic diagnostic model of severe malaria using platelet and white count data. Under this model, we re-analysed clinical and genetic data from 2220 Kenyan children with clinically defined severe malaria and 3940 population controls, adjusting for phenotype mis-labelling. Our model, validated by the distribution of sickle trait, estimated that approximately one-third of cases did not have severe malaria. We propose a data-tilting approach for case-control studies with phenotype mis-labelling and show that this reduces false discovery rates and improves statistical power in genome-wide association studies. In areas of sub-Saharan Africa where malaria is common, most people are frequently exposed to the bites of mosquitoes carrying malaria parasites, so they often have malaria parasites in their blood. Young children, who have not yet built up strong immunity against malaria, often fall ill with severe malaria, a life-threatening disease. It is unclear why some children develop severe malaria and die, while other children with high numbers of parasites in their blood do not develop any apparent symptoms.Genetic susceptibility studies are designed to uncover why such differences exist by comparing individuals with severe malaria (referred to as ‘cases’) with individuals drawn from the general population (known as ‘controls’). But severe malaria can be a challenge to diagnose. Since high numbers of malaria parasites can be found in healthy children, it is sometimes difficult to determine whether the parasites are making a child ill, or whether they are a coincidental finding. Consequently, some of the ‘cases’ recruited into these studies may actually have a different disease, such as bacterial sepsis. This ultimately affects how the studies are interpreted, and introduces error and inaccuracy into the data.Watson, Ndila et al. investigated whether measuring blood biomarkers in patients  could improve the accuracy with which malaria is diagnosed. They developed a new mathematical model that incorporates platelet and white blood cell counts. This model estimates that in a large cohort of 2,220 Kenyan children diagnosed with severe malaria, around one third of enrolled children did not actually have this disease. Further analysis suggests that patients with severe malaria are highly unlikely to have platelet counts higher than 200,000 per microlitre. This defines a cut-off that researchers can use to avoid recruiting patients who do not have severe malaria in future studies. Additionally, the ability to diagnose severe malaria more accurately can make it easier to detect and treat other diseases with similar symptoms in children with high numbers of malaria parasites in their blood.Watson, Ndila et al.’s findings support the recommendation that all children with suspected malaria be given broad spectrum antibiotics, as many misdiagnosed children will likely have bacterial sepsis. It also suggests that using complete blood counts, which are cheap to obtain and increasingly available in low-resource settings, could improve diagnostic accuracy in future clinical studies of severe malaria. This could ultimately improve the ability of these studies to find new treatments for this life-threatening disease. Plasmodium falciparum kills nearly half a million children each year, mostly in sub-Saharan Africa  as clinical or laboratory evidence of vital organ dysfunction in the presence of circulating asexual sitaemia . The WHOsitaemia . An inclsitaemia . For a gOur goal was to develop a biomarker-based model that can differentiate probabilistically between ‘true severe malaria’ and severe illness not caused primarily by malaria, but with concomitant parasitaemia. We define ‘true severe malaria’ conceptually as a febrile illness caused by malaria parasites, with organ dysfunction, that can result in death whereby mortality is attributable directly to the malaria parasites. This attributable mortality can be given a formal causal definition by using a conceptual  randomised experiment of delayed versus prompt antimalarial therapy. In a theoretical patient population with true severe malaria, delay in administration of an effective antimalarial would result in increased mortality  whereas HBB, ABO and FREM3, We developed a probabilistic diagnostic model of severe malaria based on haematological biomarkers using data from 1704 adults and children mainly from low transmission settings whose diagnosis of severe malaria is considered to be highly specific. We used this model to demonstrate low phenotypic specificity in a cohort of 2220 Kenyan children who were diagnosed clinically with severe malaria. We validated the predictions using a natural experiment, the distribution of sickle cell trait (HbAS), the genetic polymorphism with the strongest known protective effect against all forms of clinical malaria . BuildinPfHRP2 concentrations >1000 ng/mL and >1000 parasites per μL of blood  to develop a simple biomarker-based reference model of severe malaria. To fit the reference model , we used platelet and white count data from (i) severe malaria patient cohorts enrolled in low transmission areas where severe disease accompanied by a positive blood stage parasitaemia has a high positive predictive value for severe malaria . Platelet counts are not age-dependent and do not vary substantially across genetic backgrounds. The marginal distributions of platelet counts were comparable between Asian adults and children with severe malaria and African children with high plasma PfHRP2 (Appendix 2). A low platelet count (thrombocytopenia) is a universal feature of severe malaria . To illustrate this important point, in a cohort of 566 severely ill Ugandan children enrolled in the Fluid Expansion as Supportive Therapy (FEAST) trial . Children enrolled in the FEAST trial who had significant thrombocytopenia  had comparable PfHRP2 concentrations to Asian adults diagnosed with severe falciparum malaria (ulations . HoweverT) trial , a trial malaria .We can consider the hospitalised Kenyan children in this series as a mixture of two latent sub-populations, ‘severe malaria’ and ‘not severe malaria’ . To estimate the proportion of each, we use the distribution of HbAS, the human polymorphism most protective against all forms of clinical falciparum malaria. HbAS provides at least 90% protection against severe malaria . The caut-distribution fit to the severe malaria reference data) had a diagnosis of severe malaria that was 100% specific . The cases with lower likelihood values were assumed to be drawn from a mixture of the two latent populations with an unknown mixing proportion; the prevalence of HbAS in the ‘not severe malaria’ subgroup was estimated from a cohort of hospitalised children enrolled in the same hospital and who were malaria blood slide positive but were clinically diagnosed as not having severe malaria  under the reference model (a bivariate PfHRP2 >1000 ng/mL) were assumed to be drawn only from P. P was modelled itself as a mixture of bivariate t-distributions. We used an informative prior on the mixture proportion  in the Kenyan cases, a beta distribution approximating the posterior estimate from the analysis of HbAS prevalence.We then estimated P for each Kenyan case by fitting a mixture model to the reference data and to the Kenyan data jointly. The model assumed that the platelet and white count data for the Kenyan children were drawn from a mixture of P and P. The reference data  and a set of matched population controls (n = 1614), across 9.6 million biallelic variants on the autosomal chromosomes . We compHBB: HbAS; ABO: O blood group; FREM3: in close linkage with the GYPA/B/E structural variants that encode the Dantu blood group; HBB, 9% around ABO and 5% around FREM3). This resulted in larger –log10 p-values for HBB and ABO, but slightly smaller for FREM3 . For the three major genes , effect sizes were increased by 10–30% and associations all had higher significance levels on the –log10 scale (0.25–1.7). The allele frequencies of all three polymorphisms were directly associated with the probability weights, showing increased protection in individuals more likely to have severe malaria (Appendix 5). Two polymorphisms on the genes ARL14 and LOC727982, reported previously as associated with protection in severe malaria (neither of which are related to red cells), showed decreased effect sizes and –log10 p-values and are thus potentially spurious hits.We re-analysed case-control associations for 120 polymorphisms on 70 candidate malaria-protective genes which were typed directly in the 2220 Kenyan children along with 3940 population controls. In this case-control cohort, 14 polymorphisms had previously been identified as associated with protection or increased risk in severe malaria . A re-anG6PD + 202T, G6PD + 202T allele), approximately the same absolute log-odds were estimated for both sub-populations but they had opposite signs. Under an additive model in females, the rs1050828 T allele was associated with protection in the ‘severe malaria’ sub-population (odds ratio of 0.71 [95% C.I. 0.57–0.88]) but with increased risk in the ‘not severe malaria’ sub-population (odds ratio of 1.30 [95% C.I. 1.00–1.70]). The additive model including both males and females was consistent with these opposing effects but significant only at a nominal threshold , but these are still largely research procedures and have not been widely adopted or measured at scale for genetic association studies. Our results suggest that imprecision in clinical phenotyping is more substantial than thought previously. In this cohort of 2220 Kenyan children diagnosed with severe malaria from an area of moderate transmission, a probabilistic assessment suggests that around one-third may not have had severe malaria , under an additive model  could be used as a simple exclusion criterion in studies of severe malaria. Based on this analysis, we recommend that future studies in severe malaria collect and record complete blood count data. Further studies of platelet and white blood cell counts from a diverse cohort of children with severe falciparum malaria, confirmed using high-specificity diagnostic techniques such as visualisation of the microcirculation, and measurement of plasma P. falciparum along with prostration (Blantyre Coma Score of 3 or 4), cerebral malaria (Blantyre Coma Score of <3), respiratory distress  and severe anaemia (haemoglobin <5 g/dL). Controls were infants aged 3–12 months who were born within the same area as the cases and who were recruited to a cohort study investigating genetic susceptibility to a wide range of childhood diseases. Cases and controls were genotyped for the rs334 SNP and for The Kenyan case-control cohort has been described in detail previously . Severe eviously .PfHRP2 were jointly measured for 566 children . In order to select only those with a very high probability of having severe malaria as the primary cause of illness, we selected the 121 children who had measured PfHRP2 >1000 ng/mL and parasitaemia >1000 per μL.FEAST was a multicentre randomised controlled trial comparing fluid boluses for severely ill children (n = 3161) that was not specific to severe malaria . PlateleThe AQ and the AAV studies were two randomised clinical trials in Vietnamese adults diagnosed clinically with severe falciparum malaria recruited to a specialist ward of the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam, between 1991 and 2003 . AQ VietPfHRP2 concentrations were available in 172 patients from Bangladesh. 55 patients from this series were younger than 15 years of age.We included data from multiple observational studies in severe falciparum malaria conducted by the Mahidol Oxford Tropical Medicine Research Unit in Thailand and Bangladesh between 1980 and 2019. These pooled data have been described previously . PlateleIn the Kenyan severe malaria cohort (n = 2220), data on platelet counts were missing in 18%, white blood counts were missing in 0.2% and parasite density was missing in 1.6%. In-hospital outcome (died/survived) was missing for 13 patients. rs334 genotype was missing for 7; missForest (targeted genotyping data was not included for imputation). Appendix 7 shows the missing data pattern in the studies in Vietnamese adults and in the Kenyan severe malaria cases. Ten datasets were imputed for each dataset independently and were used for the subsequent analyses. Analyses using directly typed genetic polymorphisms or the within-hospital outcome as the dependent variables used only the data where these outcomes were recorded, assuming that they were missing at random.We did multiple imputation using random forests for all available clinical variables using the R package Thrombocytopenia accompanied by a normal white blood count and a normal neutrophil count are typical features of severe malaria , but thePfHRP2 measurements indicating a large latent parasite biomass  or in children or adults with high plasma  biomass .log10 scale), with mean white counts reaching a plateau around 5 years of age. We used this to correct all white count data in children less than 5 years of age, both in the reference data and the Kenyan cohort.In the first years of life, white blood cell counts are often much higher than in adults because of lymphocytosis. We used data from 858 children from the FEAST trial, in whom white counts were measured, to estimate the relationship between age and mean white count in severe illness (median age was 24 months). The estimated relationship is shown in Appendix 8  . The useFor platelet counts , age is not a confounder and published data support the hypothesis that thrombocytopenia is highly specific for ‘true’ severe malaria in children as well as adults suspected of having severe malaria . The French national guidelines specifically mention thrombocytopenia  for the diagnosis of severe malaria in children who have travelled to a malaria endemic area. In a French paediatric severe malaria series in travellers, almost half had severe thrombocytopenia  . In Dakan = 438) .log10 scale, platelet counts and white counts show a good fit to the normal approximation but with some outliers so a t-distribution was used (robust to outliers). For all modelling of the joint distribution of platelet counts and white blood cell counts, we chose bivariate t-distributions with 7 degrees of freedom as the default model. The final reference model used was a bivariate t-distribution fit to the joint distribution of platelet counts and white counts both on the logarithmic scale. On the log10 scale, the mean values (standard deviations) were approximately 1.76 (0.11) and 0.92 (0.055) for platelets and white counts, respectively. The covariance was approximately 0.0035. These values varied very slightly across the 10 imputed datasets. Log-likelihood values for each severe malaria case in the Kenyan cohort were calculated for each imputed dataset independently. The median log-likelihoods per case were then used in downstream analyses.We visually checked approximate normality for each marginal distribution using quantile-quantile plots (Appendix 9). On the The diagnostic model of severe malaria using platelet counts and white blood cell counts cannot be applied to all patients. We summarise here the known and possible limitations. When using this model to estimate the association between a genetic polymorphism and the risk of severe malaria, if the genetic polymorphism of interest affects the complete blood count independently, there will be selection bias (see the directed acyclic graph in Appendix 10). One example is HbSS. Children with HbSS have chronic inflammation with white blood cells counts about 2–3 times higher than normal and slightly lower platelet counts . All 11 HBA1-HBA2 genes  or it could be concomitant (which may result from extensive parasitised erythrocyte sequestration in the gut), that is, a result of severe malaria. The former should be identified as ‘not severe malaria’ (as bacteraemia is the main cause of illness), but the latter should be identified as ‘severe malaria’ and might be mis-classified as ‘not severe malaria’ under our model. However, in a series of 845 Vietnamese adults (high diagnostic specificity), only one of eight patients who had concomitant-invasive bacterial infections and a white count measured had leukocytosis . For a set of diagnostic biomarkers We assume that the Kenyan cases are a latent mixture of two sub-populations: f1 by using the distribution of HbAS  without making parametric assumptions about P0: Out of the 2213 Kenyan cases with rs334 genotyped, we assume that cases in the top 40th percentile of the likelihood distribution under P0 is unknown and denoted For the other cases, the proportion drawn from Finally, additional information is incorporated by using data from a cohort of individuals with severe disease from the same hospital who had positive malaria blood slides but whose diagnosis was not severe malaria re HbAS) .Under these assumptions, we can fit a Bayesian binomial mixture model to these data with three parameters: P1  with the same interpretation as inverse probability weights. The weighted glm is equivalent to computing the maximum likelihood estimate where the log-likelihood is weighted by wi. In our case-control analyses, all the controls are given weight 1. f0. Appendix 12 shows the results of a simulation study demonstrating how the effect estimates and standard error estimates vary as a function of the proportion of mis-classified cases (as given by the probability weights).For each plink2 to prune the SNPs (options: –maf 0.01 –indep-pairwise 50 2 0.2) down to a set of 462,120 SNPs in approximate linkage equilibrium. These SNPs were then used to calculated the first five principal components (Appendix 13), which we subsequently used to control for population structure in the genome-wide association study. We used the Michigan imputation server with the 1000 Genomes Phase 3 (version 5) as the reference panel to impute 28.6 million polymorphisms across the 22 autosomal chromosomes. This is a web-based service that runs imputation pipelines . Encrypted results are returned with a one-time password. Of the remaining 3682 individuals (1681 cases and 1615 controls), we had clinical data available for 1297 cases. We only used the subset of individuals with clinical data available in order for a fair comparison between the weighted and non-weighted genome-wide association studies. We ran subsequent genome-wide association studies on all biallelic sites with a minor allele frequency glm with a binomial link for all tests of association . The supplementary appendix gives the R code for weighted logistic regression. The point estimates from the weighted model estimated by glm are correct but it is necessary to transform the standard errors in order to take into account the reduction in effective sample size (see code).Anonymised whole-genome data from the Illumina Omni 2.5M platform for 1944 severe malaria cases and 1738 population controls were downloaded from the European Genome-Phenome Archive .We fit a categorical  logistic regression model to the case-control status as a function of the directly typed polymorphisms .Code, along with a minimal clinical dataset for reproducibility of the diagnostic phenotyping model, is available via a GitHub repository: https://dataverse.harvard.edu/dataverse/kwtrp).A curated minimal clinical dataset is currently available alongside the code on the GitHub repository. This will also be made available at publication via the KEMRI-Wellcome Harvard Dataverse . Requests for access to appropriately anonymised clinical data from the AQ and AAV Vietnam study and the Asian paediatric cohort can be made via the Mahidol Oxford Tropical Medicine Research Unit data access committee by emailing the corresponding author JAW (jwatowatson@gmail.com) or Rita Chanviriyavuth (rita@tropmedres.ac).The FEAST trial datasets are available from the principal investigator on reasonable request  feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Acceptance summary:The fundamental premise of genome wide association studies for severe malaria is to take a population with confirmed severe malaria and compare with a control group who do not have severe malaria. This paper presents a novel and valuable method for improving power for severe malaria genetic association studies. The method would also be useful for studies of other disease where there is a clinical definition that sometimes includes people who do not truly have the disease.Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Dominique Soldati-Favre as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Michael White (Reviewer #2).Thank you for submitting your article "Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision" for consideration by 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) The paper would benefit from a clear definition early on of what is meant by "true severe malaria" – is it severe malaria symptoms that would go away if the malaria parasites are removed or severe malaria symptoms that would persist if all non-malaria illness was removed.2) Page 3. "To rule out confounding by geography and age, we demonstrate the discriminatory value of platelet counts alone." It wasn't clear why this ruled out confounding by geography and age until it was discussed several sentences later that "Total white blood cell counts are age dependent and vary across genetic backgrounds."3) For the data tilting method, how does one interpret the estimated odds ratio?Is it the effect of the genotype on true severe malaria?4) A simulation study would be useful in understanding the statistical properties of the proposed method.5) A table summarizing the cohorts with summary statistics such as geographic location, age, symptom severity, and other relevant epidemiological information would be very useful.6) A more explicit demonstration that what we observe about severe malaria in Asian adults applies to Asian children, applies to African children.7) Figure 1B. For the grey line fitted to the FEAST data, does this also include the PfHRP2 = 1 data. As this was non-detectable, is this a valid thing to do?8) Figure 3. Can you check the panel labels? What's the horizontal dashed line?9) Were they significant associations between parasite density and the probability of severe malaria.10) Please provide some additional information on the comparison between the training and testing data used for the model.Reviewer #1 (Recommendations for the authors):The paper would benefit from a clear definition early on of what is meant by "true severe malaria" – is it severe malaria symptoms that would go away if the malaria parasites are removed or severe malaria symptoms that would persist if all non-malaria illness was removed.Page 3. "To rule out confounding by geography and age, we demonstrate the discriminatory value of platelet counts alone." It wasn't clear to me why this ruled out confounding by geography and age until it was discussed several sentences later that "Total white blood cell counts are age dependent and vary across genetic backgrounds."For the data tilting method, how does one interpret the estimated odds ratio?Is it the effect of the genotype on true severe malaria?eLife paper but simulation studies would be useful in understanding the statistical properties of the proposed method.This may not be needed for an Reviewer #2 (Recommendations for the authors):Please provide some additional information on the comparison between the training and testing data used for the model. Essential Revisions:1) The paper would benefit from a clear definition early on of what is meant by "true severe malaria" – is it severe malaria symptoms that would go away if the malaria parasites are removed or severe malaria symptoms that would persist if all non-malaria illness was removed.We agree that this is important and central to the exercise, and was left too vague in the initial submission.We define “true severe malaria” conceptually as (i) a febrile illness caused by malaria parasites, (ii) with an elevated risk of death, (iii) and in which mortality is directly attributable to the malaria parasites.PfHRP2 concentration, consistent with the hypothesis that the subgroup of patients with high PfHRP2 has higher specificity for “true severe malaria” .The two conditions which we are trying to discriminate between are severe illness caused by malaria and severe illness with coincidental malaria. A more formal definition can be given using a thought experiment: an idealized  randomized trial whereby antimalarial treatment is delayed vs given promptly. In a population of “true severe malaria” patients, delay in administration of an effective antimalarial would result directly in increased mortality, whereas this would not be the case in “not severe malaria”. In clinically diagnosed severe malaria delay in starting curative treatment is associated with an increased mortality , and pre-referral treatment in suspected severe malaria has been shown to reduce mortality and morbidity . The life-saving advantage of artesunate over quinine in the large RCTs AQUAMAT and SEAQUAMAT can also be interpreted as supporting this in that artesunate kills circulating ring stage parasites whereas quinine does not, resulting in a delay in the onset of therapeutic benefit, thus mimicking a “delay” in treatment. There was evidence in the AQUAMAT trial of an increased treatment effect as a function of the admission plasma We have added the following paragraph to the penultimate paragraph in the Introduction (lines 93-104):Our goal was to develop a biomarker-based model that can differentiate probabilistically between `true severe malaria' and severe illness not caused primarily by malaria, but with concomitant parasitaemia. We define `true severe malaria' conceptually as a febrile illness caused by malaria parasites, with organ dysfunction, that can result in death whereby mortality is attributable directly to the malaria parasites. This attributable mortality can be given a formal causal definition by using a conceptual  randomised experiment of delayed versus prompt anti-malarial therapy. In a theoretical patient population with true severe malaria, delay in administration of an effective antimalarial would result in increased mortality, whereas in a population with severe illness not caused by malaria  there would not be a corresponding increase in mortality.2) Page 3. "To rule out confounding by geography and age, we demonstrate the discriminatory value of platelet counts alone." It wasn't clear why this ruled out confounding by geography and age until it was discussed several sentences later that "Total white blood cell counts are age dependent and vary across genetic backgrounds."This paragraph was unclear and we have rewritten it. We have removed the “rule out” as it is not possible in this context to rule out confounding. The re-written paragraph now reads as (lines 120-137):-16 for a spline term on the log10 platelet count in a generalised additive logistic regression model predicting PfHRP2 > 1,000 ng/mL, Appendix 1). Children enrolled in the FEAST trial who had significant thrombocytopenia  had comparable PfHRP2 concentrations to Asian adults diagnosed with severe falciparum malaria .Direct comparisons of white blood cell counts across these two data sets are confounded by geography and age. Total white blood cell counts are known to be age-dependent and vary across genetic backgrounds, in particular lower neutrophil counts are associated with mutations in the ACKR1 gene that results in the Duffy negative phenotype prevalent in African populations . However, after adjustment for age (see Methods), the marginal distributions of total white counts were comparable between Asian adults and children with severe malaria and African children with high plasma PfHRP2 (Appendix 2). Platelet counts are not age dependent and do not vary substantially across genetic backgrounds. The marginal distributions of platelet counts were comparable between Asian adults and children with severe malaria and African children with high plasma PfHRP2 (Appendix 1). A low platelet count (thrombocytopenia) is a universal feature of severe malaria (see evidence collated in Methods). To illustrate this important point, in a cohort of 566 severely ill Ugandan children enrolled in the FEAST trial , low platelet counts were highly predictive of blood stage parasitaemia and elevated PfHRP2 (p=103) For the data tilting method, how does one interpret the estimated odds ratio?Is it the effect of the genotype on true severe malaria?Yes, exactly. This is analogous to the interpretation of regression models when using inverse probability weighting . We have added the following sentence to the Methods (lines 545-547):The log odds ratio computed from the weighted logistic regression can be interpreted as the causal effect of the polymorphism on `true severe malaria' relative to the controls, where `true severe malaria’ is defined by the sampling distribution f0.4) A simulation study would be useful in understanding the statistical properties of the proposed method.We have added a simple simulation study to the github repository which is reported in Appendix 12. The simulation assumes that cases are composed of two latent classes , for which we have calibrated class probabilities . We then varied the proportion of the true cases from 50% to 100%. Figure 1 in Appendix 12 shows the distribution of the case weights for the 50% contamination and 0% contamination scenarios (panels A and B), and shows how the effect estimates and standard errors vary as a function of the proportion of true cases (panels C and D). When we use the information in the case probability weights (weighted log-likelihood) the mean effect estimates on the log odds scale  are close to the true simulated effect for 50% contamination and recover exactly the true effect when the proportion of true cases > 80%. This increase in precision in effect estimation comes at the cost of an increase in the standard errors (due to the reduced effective sample size). Figure 2 in Appendix 12 shows the resulting effect on statistical power. It is important to note that the advantage of the re-weighted likelihood approach relies heavily on the calibration and precision of the case probability weights. If the diagnostic model is biased or only weakly informative (eg the majority of the weights are not close to 0 or 1) then likelihood re-weighting will not add much and could reduce power.5) A table summarizing the cohorts with summary statistics such as geographic location, age, symptom severity, and other relevant epidemiological information would be very useful.We have added Table 1 which summarizes the 4 data sets used in the analysis.6) A more explicit demonstration that what we observe about severe malaria in Asian adults applies to Asian children, applies to African children.PfHRP2. The same is true for the white counts after age adjustment. Although there are clinical differences between adults and children with severe malaria, the fundamental pathological processes appear to be the same. This is supported by the fact that the life-saving treatment advantage of artesunate over quinine is the same when comparing children with high plasma PfHRP2  versus adults .The number of Asian children with severe malaria studied in our analysis is relatively small by comparison with the number of Asian adults. There is no evidence that the marginal distributions of platelet counts are different between the Asian adults and children or the Asian adults and the African children with high PfHRP2 in African children  strongly supports low platelet counts as a universal feature of severe malariaWe argue that the proposed reference model for severe malaria is justified for two following reasons. First, we make an age-adjustment to the white counts ; second, the relationship between platelet counts and The model allows for varying mean platelet counts and white counts across the datasets: in the Kenyan children the sampling distribution P is modelled as a mixture of two components, one equal to the fit using Asian adults/children and the other equal to the fit using the 121 children in FEAST .7) Figure 1B. For the grey line fitted to the FEAST data, does this also include the PfHRP2 = 1 data. As this was non-detectable, is this a valid thing to do?PfHRP2 concentrations which were set to 1 ng/mL. If we assume that all these patients did indeed have a PfHRP2 concentration less than the lower limit of the ELISA assay  then we believe that this is valid with some limitations on the interpretation of the regression fit. The analysis is using a log10(x+λ) transformation (a Box-Cox transformation). Choosing λ=1  is widely used, for example in pharmacometric analyses where drug concentrations are often below the lower limit of detection for a particular assay. This can introduce bias in parameter estimation for pharmacokinetic models (see for example https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/) but we can’t see any issue in this particular setting as we are only demonstrating the correlation between PfHRP2 and platelet counts in severe illness rather than attempting to infer a population mean PfHRP2 concentration for a given platelet count.The grey line (changed to brown in the revised paper so that it is more visible) does include the non-detectable HRP2/3 deletions are common. This could dilute the association between platelet counts and PfHRP2 plasma concentrations. HRP2/3 deletions were rare in Uganda at the time of the FEAST trial confirmed by the fact that very few patients had measurable parasitaemia >1000 uL with undetectable plasma PfHRP2.One issue could be for patient populations where 8) Figure 3. Can you check the panel labels? What's the horizontal dashed line?We have corrected the legend of Figure 3 (panels C and D). The horizontal dashed line in panel D was showing the mean mortality in the cohort. We have added the analogous lines to panels C and to the new panel E (parasite density – as suggested in next point). We have included explanations in the legend.9) Were they significant associations between parasite density and the probability of severe malaria.p=10-25 for a linear model fit to log parasite densities). Patients with a probability of severe malaria approximately equal to 1 under our model have a mean parasite density of ~70,000 per uL, whereas those with a probability approximately equal to 0 have a mean parasite density of ~13,000 per uL (roughly a fivefold difference). We have added a plot of model probabilities versus parasite densities to Figure 3 (panel E in the revised manuscript). These additional results are now described on lines 175-177 and 184-186:Thank you. This is a very important question that we had addressed but then forgot to include in the paper! There is a significant relationship between the model probabilities and the admission parasite densities  and admission peripheral blood parasite density . [..] The admission parasite densities in patients with a probability of severe malaria close to 1 were approximately five-fold higher than in patients with a probability of severe malaria close to zero.The individual probabilities were also predictive of in-hospital mortality (p=1010) Please provide some additional information on the comparison between the training and testing data used for the model.See Table 1 and replies to comment 6.


Annually 125 million pregnancies are at risk of malaria infection. However, the impact of exposure to malaria in pregnancy on neurodevelopment in children is not well understood. We hypothesized that malaria in pregnancy and associated maternal immune activation result in neurodevelopmental delay in exposed offspring.n [%] positive: 240 [57.3]), placental malaria (n [%] positive: 112 [29.6]), and maternal immune activation on neurocognitive development in children. Linear mixed-effects analysis showed that children exposed to antenatal malaria between 33 and 37 weeks gestation had delayed language development across the 2-year follow-up, as measured by MCAB-CDI . Maternal immune activation, characterized by increased maternal sTNFRII concentration, between 33 and 37 weeks was associated with lower MCAB-CDI language score . Main limitations of this study include a relatively short length of follow-up and a potential for residual confounding that is characteristic of observational studies.Between April 2014 and April 2015, we followed 421 Malawian mother–baby dyads  who were previously enrolled  in a randomized controlled malaria prevention trial with 5 or 6 scheduled assessments of antenatal malaria infection by PCR. Children were evaluated at 12, 18, and/or 24 months of age with cognitive tests previously validated in Malawi: the Malawi Developmental Assessment Tool (MDAT) and the MacArthur–Bates Communicative Development Inventories (MCAB-CDI). We assessed the impact of antenatal malaria  to an increased risk for neurocognitive deficits and neuropsychiatric disease in exposed children. Excessive maternal immune activation, irrespective of pathogen, is thought to mediate this effect.Millions of pregnant women are at risk for malaria infection each year. To our knowledge, the impact of malaria during pregnancy on child neurodevelopment has not been systematically studied in a clinical setting.We conducted an observational cohort follow-up study nested within a larger randomized controlled trial with detailed records of malaria in pregnancy to examine the impact of malaria in pregnancy on neurocognitive development in exposed children.To our knowledge, our data provide the first indication in a clinical cohort that malaria in pregnancy may be a previously unrecognized risk factor for neurodevelopmental delay.Furthermore, the association of systemic inflammation with reduced neurocognitive scores highlights a potential mechanistic pathway through which malaria in pregnancy could be affecting fetal neurodevelopment.There are millions of children in malaria-endemic regions who are not currently meeting their developmental potential. Malaria in pregnancy may be a modifiable risk factor for neurodevelopmental delay in children exposed in utero.Our findings suggest that scaling up efforts to prevent malaria infection could be an effective strategy to protect mother–baby dyads from poor developmental outcomes.Larger trials powered to address potential residual confounding, with a longer follow-up period and more diverse neurocognitive and neuropsychiatric tests, are required to confirm and extend these findings. Early developmental delays are prevalent in low- and middle-income countries (LMICs), where an estimated 1 in 3 preschool-age children do not reach cognitive and socio-emotional milestones . IdentifPlasmodium falciparum malaria infection in pregnancy is driven by the accumulation of parasitized erythrocytes binding to chondroitin sulfate A in the placental intervillous space, where they lead to the recruitment, retention, and activation of mononuclear cells [P. falciparum malaria in pregnancy could interfere with normal neurodevelopment in children.A growing body of evidence links maternal infection during pregnancy to neurocognitive deficits and neuropsychiatric disease in exposed offspring ,4. Sincear cells . Malariaar cells –9, involar cells –13. CollPreclinical studies of murine malaria in pregnancy revealed an association between in utero exposure to malaria and developmental deficits in memory and affective-like behavior in offspring that persisted to adulthood  –16. FurtP. falciparum parasites were detected in all sample types using a real-time PCR assay targeting the P. falciparum lactate dehydrogenase gene that detects down to a density of 2 parasites/microliter [This study enrolled mother–baby dyads from women enrolled in a previous 3-site, 2-arm randomized superiority trial of prevention of malaria in pregnancy in Malawi . HIV-negcroliter . Here, wcroliter . Congenicroliter .At each antenatal visit, a maternal plasma sample was collected and stored at −80°C. Inflammatory plasma analyte data for this cohort were derived as described . BrieflyThe parent trial was registered with the Pan African Clinical Trials Registry (PACTR201103000280319) and ISRCTN Registry (ISRCTN69800930). Ethical approval for the current study was obtained from the Malawian College of Medicine Research and Ethics Committee (COMREC reference number: P.08/13/1477), the University Health Network Research Ethics Board (REB number: 13-6741-AE), and the University of Liverpool (IREC number: RETH000693). Written informed consent for participation of infants was obtained from caregivers.n = 524; Between April 2014 and April 2015, children born in both treatment arms of the parent trial were subsequently enrolled in the PAMaNeD cohort study . Enrollment in the PAMaNeD cohort study began after women had completed their involvement in the parent trial . To mitigate selection bias, every attempt was made to trace, contact, and re-consent all eligible mother–baby pairs n = 524; . Mother–Children were seen at 12, 18, and 24 months of age. At each clinic visit, a clinical history and physical exam were conducted, and any illnesses since the last visit were recorded and corroborated using the child’s health passport. Bed net use was recorded at each visit, and the majority of children  were reported to have slept beneath a bed net the previous night. If the child was ill at the time of assessment, the visit was rescheduled for when they were well. Mothers were encouraged to bring infants with any signs or symptoms of illness to the study clinic between scheduled visits.At 12, 18, and 24 months of age, the child’s home environment was assessed using the Family Care Indicator (FCI) questionnaire. The FCI assesses the ability of the household to meet the physical, mental, and social needs of the child and has been adapted and validated for use in Malawi . On the At 12, 18, and 24 months, the MDAT was used to assess age-specific neurocognitive development . The MDAAt 18 and 24 months, the MCAB-CDI was used to assess language development . The MCAAt 18 and 24 months, children were assessed using the A-not-B test  and delaThis study is reported according to STROBE guidelines .The primary outcomes presented here are total MCAB-CDI and total MDAT scores through repeated measures at 12, 18, and 24 months. A subanalysis was performed on the subdomains of the MDAT . Malaria infection was analyzed by 2 exposure definitions: (1) placental malaria, defined as positive placental histology  or positive placental PCR at delivery, and (2) antenatal malaria, defined as PCR-confirmed malaria infection during pregnancy at any scheduled or unscheduled visit including enrollment and delivery . The latter was also stratified by specific gestational age windows . There were 91 (21.6%) women who met the definition for both antenatal malaria and placental malaria; however, the 2 exposure groups are not directly compared and do not overlap within a single analysis. A detailed breakdown of the characteristics of malaria infections in this cohort  is provided in Statistical analysis was performed using R version 3.5.1 . The prespecified statistical analysis is described in the study protocol . In addiTo examine the impact of maternal malaria infection and inflammation on longitudinal neurodevelopment, we built LME models using the lme4 package in R . LME modp-Values were adjusted for multiple comparisons using the Holm–Bonferroni method , compared to children born to mothers who were PCR negative for malaria in this window, even after correcting for multiple comparisons  stratified by maternal malaria status are presented in parisons . Stratifparisons .p < 0.001) (p = 0.001)    and lowe.06, < 0.%CI, −8.5= 0.003) .Here we assessed longitudinal neurodevelopment up to 24 months of age, in a cohort of 421 Malawian children born to mothers with well-characterized antenatal and placental malaria. After controlling for confounding factors, the strongest association in our data linked PCR-positive malaria late in pregnancy (33–37 weeks gestation) with impaired language development up to 2 years of age. Furthermore, analysis of inflammatory mediators supports the hypothesis that this association is driven by maternal immune activation, as increased maternal plasma concentration of sTNFRII between 33 and 37 weeks gestation was associated with reduced language score in exposed children. These findings provide evidence that malaria in pregnancy may be an underrecognized risk factor for developmental delay in malaria-endemic regions.The profile of neurodevelopmental delay associated with malaria in pregnancy and maternal immune activation  in our cohort is consistent with previous findings for other maternal infections in women living in LMICs –34. Mechp < 0.001), in agreement with previously published comparisons [Here, antenatal-malaria-associated and sTNFRII-associated decreases in MCAB-CDI language development scores represented the largest, and most clinically relevant, effect size. Maternal sTNFRII and antenatal malaria between 33 and 37 weeks gestation were both associated with significantly lower scores in language development in exposed children. There were some differences in MDAT scores by maternal malaria status, but these did not remain significant after correction for multiple comparisons and lacked clinical relevance given the modest effect sizes (<1 item difference on a 138-item assessment tool). Conversely, the effect sizes for language development using the MCAB-CDI are significant for under-2 child development ,39. Fromparisons . HoweverThe impact of the timing of maternal infection on neurodevelopment remains largely unknown. One preclinical study in a murine model of maternal immune activation revealed distinct profiles of neurological sequelae depending on the gestational timing of insult . Our datEven in the context of this relatively healthy cohort, malaria during pregnancy was associated with neurodevelopmental deficits in language after controlling for birth weight, gestational age at delivery, and sociodemographic factors that impact child development. Malaria in pregnancy is associated with adverse birth outcomes, including LBW due to small for gestational age (SGA) and/or PTB . LBW andp-values were adjusted for the number of comparisons to mitigate the effect of multiple comparisons on the type I error rate. As an observational study where the exposure variable cannot be allocated at random , the study was prone to bias. This bias was mitigated by measurement and consideration of as many potential confounders as possible ; however, some residual confounding may remain, and larger trials powered to address residual confounding are necessary to confirm and extend these findings. Residual confounders that are associated with neurodevelopment in LMICs but that we were unable to measure could include other maternal or child infections , chifections , and antfections . Here, wfections . Given tIn Malawi, an estimated 40% of children have low early childhood development scores , similarS1 Data(XLSX)Click here for additional data file.S1 Protocol(PDF)Click here for additional data file.S1 STROBE Checklist(DOC)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Plasmodium vivax in Botswana through active case detection. A real-time PCR was used during a similar study in 10 districts to assess changes in the P. vivax prevalence. We assessed 1,614 children (2–13 years of age) for hemoglobin  and Plasmodium parasites. The median age of all participants was 5.0 years . The median Hb (g/dL) level was 12.1, but 18.3% of the participants had anemia (Hb < 11.0 g/dL); these participants were clustered in the younger than 5 years age group in all districts (P < 0.001). The risk of anemia decreased with age 5 years or older . The prevalence rates of Plasmodium parasites were as follows: P. vivax, 12.7%; P. falciparum, 12.7%; P. malariae, 0.74%; and P. ovale , 0.68%. Mixed infection rates were as follows: P. falciparum and P. vivax, 2.35%; P. falciparum and P. ovale curtisi, 0.56%; P. vivax and P. malariae, 0.06%; and P. falciparum and P. malariae, 0.68%. The infections were largely asymptomatic (99.6%). Using logistic regression, the risk of infection with P. vivax was highest in Kweneng East , followed by South East  and Ngami . Compared to the risk of infection for children younger than 5 years, the risk of infection decreased for children 5 years or older in regions with high rates of P. vivax and P. falciparum infections. P. vivax and P. falciparum have expanded within the asymptomatic population in Botswana; therefore, careful attention is required for their elimination.In 2016, we reported the presence of  However, unlike the two sympatric species of P. ovale  that have hypnozoites stages similarly to P. vivax, it is unknown if P. malariae have hypnozoites even though they have long latency periods and can sustain infections through relapses or recrudescences.12P. malariae is known to have an enhanced capability to sustained infection in humans.13 Several reports have shown that asymptomatic infections with all Plasmodium species comprise a significant portion of the burden of disease.15 Therefore, it is reasonable to surmise that a more effective approach to malaria elimination and eradication in Africa should consider a strategy that targets all Plasmodium species in parallel in asymptomatic and symptomatic infections based on accurate active case detection using highly sensitive molecular tools.16 It is essential for the scientific community to work closely with National Malaria Control Programs (NMCPs) to achieve this goal. By obtaining data regarding all Plasmodium species in Africa, the impetus for guidance regarding the elimination and eradication strategies will allow NMCPs to retool their resources appropriately.It has been well-established that as the rates of malaria attributable to Plasmodium species that can be missed with passive data collection, which is unable to detect submicroscopic and asymptomatic infections and how they contribute to transmission.18 The Botswana NMP is retooling to forge a collaboration to create elimination strategies and improve disease surveillance, monitoring, and evaluation.19 The collaboration will improve the human resources and technical capacity through joint activities with universities and research institutions. We report the data obtained using molecular tools through our close collaboration with the NMP of Botswana to detect active cases of the four Plasmodium species that are infectious to humans. We affirm the presence of P. vivax and nonfalciparum parasites in Botswana and the changed burden of P. falciparum in the country since the 2016 report.There are geospatial limits to the transmission dynamics of 2 The sites were Okavango, Ngami, Chobe, Tutume, Francistown, Palapye, Serowe, Kweneng West, Kweneng East, and South East. We used a multistage sampling process to select the schools, clinics/health posts, and participants. The Ministry of Basic Education primary school registers and MOHW clinic/health post registries within each district were used to select the schools and clinics involved in the study enrollment.2 Briefly, during the first stage, districts with known malaria transmission profiles based on the recommendations of the NMP were selected. During the second stage, towns within the district with variable malaria incidence rates were also selected to ensure heterogeneity within the districts. During the third stage, schools and clinics within each town/village were selected using a two-stage clustering approach based on the population density and adequate cross-sectional representation of the communities to avoid any bias. During the final stage, participants were assigned numbers and enrolled after obtaining informed parental consent and consent from the heads of schools and clinics/health posts. The total number of samples derived for each district/town was in direct proportion to the estimated population density. We enrolled 1,645 children 2 to 13 years of age between December 2015 and February 2017.The study sites were selected with the support of the NMP of the Ministry of Health and Wellness (MOHW) and Ministry of Education of Botswana, as reported previously.The study was approved by the MOHW Ethical Committee of Botswana and the Institutional Review Board of the University of Botswana (permit no. UBR/RES/IRB/BIO/062). All parents/guardians provided informed consent on behalf of all participants. When necessary, assent was also obtained from the child before a sample was collected.2The sample size was calculated as previously described.Community mobilization was performed at Kgotla meetings (community meetings with elders of the community), clinics/health posts, and parent–teacher association meetings before enrollment. Children 5 to 9 years of age were enrolled from primary schools. Children 2 to 4 years of age and 10 to 13 years of age were enrolled from the child welfare clinics. Participants were enrolled only if they had no self-reported clinical symptoms.Written informed consent for participation in the study was obtained in Setswana or English from parents or guardians for each prospective participant before enrollment. Emphasis was placed on the fact that the participants were free to participate or decline participation without any effect on their medical care.Venous blood samples (1.0–1.5 mL) were collected into EDTA tubes. Hemoglobin concentrations (g/dL) were checked immediately using a Hemocue 201 device , and the results were provided to the participants’ caregivers. Participants found to have moderate or severe anemia were referred for further investigation and treatment. Fever was defined as a tympanic temperature ≥ 37.8°C at the time of sample collection; asymptomatic participants were those without fever (tympanic temperature < 37.8°C) and without a history of fever during the preceding 72 hours. Sample collections were timed to include the onset and peak of the malaria transmission season.The samples were transported in cooler boxes within 3 hours of collection to the district hospital. Blood was separated by centrifugation at 5,000 rpm for 5 minutes into plasma and cell pellets. These were stored at −80°C until they were analyzed.Demographic variables that were recorded at the time of blood sample collection were age, sex, ethnicity, height, weight, tympanic temperature, place of residence, travel history, and malaria diagnosis during the previous year. Participants who were underweight were referred for further management. Participants who were febrile were also referred to the outpatient department for further management.Genomic DNA was extracted from the pelleted cells and purified using the Hamilton Star Microlab WorkStation  robotic system. The instructions accompanying the Machery and Nagel (MN) Nucleospin 96 blood kit were followed to achieve the extraction of high-quality DNA. This method uses silica membrane technology for binding DNA after lysis to facilitate purification. The starting blood sample was 200 μL of the packed and thawed erythrocytes, and final DNA elution volume was 120 μL sterile PCR-grade water. Then, 5 μL of the extracted DNA was used for nested PCR and 2.5 μL was used for quantitative PCR (qPCR).Plasmodium species were detected by modification of the double-nested PCR procedure targeting conserved species-specific regions of the18S small subunit of ribosomal RNA (18S ssRNA) as previously reported.21 For qPCR, the genus-specific primers and probes were those that have been previously described.21 The species-specific primers and probes for P. falciparum, P. vivax, P. ovale, and P. malariae were also published previously.23 Samples were screened during the qPCR for positivity and affirmed for species using nested PCR. All nested detection assays were single-plex and performed in a high-throughput 96-well plate , and the CFX96 Real-Time PCR detection system  was used for all qPCR assays. The kits used for nested PCR were the Qiagen PCR core kit ; the KAPA PROBE FAST qPCR Master Mix (2X)  or the abTES Malaria 5 qPCR II Kit  were also used for PCR. Species-specific primers and probes were ordered from Eurogentec . Standard controls of Plasmodium species 3D7 synchronized cultured parasites were obtained by cell sorting flow cytometry as described previously24 . Details of the amplification reactions and cycling parameters for qPCR and nested PCR have been published previously.25All Plasmodium infection, anemia, and/or age), continuous covariates grouped into categories were compared using binary and multinomial logistic regression. Odds ratios (ORs) were used for logistic regression analyses, and 95% confidence intervals (CIs) were used for point estimates. Anemia was defined as hemoglobin < 11.0 g/dL. Statistical significance for all comparisons was set at P < 0.05. Adjustment was not performed for multiple comparisons during this exploratory study.Data were entered in an Excel  data sheet. SPSS version 26  was used for analysis. Descriptive statistics and appropriate measures of central tendency were provided for relevant demographic covariates. To describe differences between study sub-populations . Participants from Tutume  were the youngest, followed by those from Kweneng East  and Serowe . Participants from Ngami  and Francistown  were older than the other participants (P = 0.004). The overall median hemoglobin concentration was 12.1 g/dL; however, anemia was present in the < 20th percentile age group in all districts (P < 0.001) (P < 0.001). Anemia was significantly related to the district of residence (P < 0.001) , followed by Okavango (P = 0.09) and Francistown (P = 0.06) (th percentile and 25th percentile hemoglobin concentrations (g/dL), respectively, were 10.2 and 10.7 for Francistown, 10.1 and 11.1 for Chobe, 10.6 and 11.3 for South East, 10.3 and 11.3 for Ngami, 10.5 and 11.4 for Kweneng East, and 10.8 and 11.3 for Serowe. Asymptomatic participants comprised 99.6% of the study population; 0.4% of the symptomatic participants had P. falciparum and were clustered mainly in Chobe. There was no difference in the sexes of participants who had Plasmodium infections and those who did not.A total of 1,645 children from 10 districts  were enr< 0.001) . Of the < 0.001) . Tutume  = 0.06) .). The 1Plasmodium parasites were available for 1,614 participants  and P. vivax (12.7%) were similar, although the prevalence differed between districts (Plasmodium infections were Kweneng East (11.96%), South East (5.82%), Ngami (2.6%), Tutume (2.5%), and Palapye (2.5%); Kweneng West (0.80) and Okavango (0.86%) had the least number of Plasmodium infections. All P. malariae and P. ovale (curtisi) infections were present as coinfections with P. falciparum or P. vivax and clustered in Kweneng East, South East, Tutume, and Palapye. P. vivax infections were strongly clustered in Kweneng East (5.6%), South East (2.5%), Ngami (1.3%), and Tutume (0.80%). According to a logistic regression analysis, the three districts with the highest risk of infection with P. vivax were Kweneng East , South East , and Ngami . There was also a relatively small cluster at increased risk for infection in Kweneng West  and Palapye . The risk of infection with P. vivax decreased with age in Kweneng East , South East , and Ngami . In contrast, all districts were significantly at risk for infection with P. falciparum (P < 0.001); however, participants 5 years or older were at decreased risk for infection in all regions except Chobe and Francistown. Interestingly, participants 5 years or older from Okavango were at increased risk for infection .Data regarding icipants . All fouistricts . The disP. falciparum and P. vivax increased significantly during 2016 to 2017, with P. vivax accounting for a significant proportion of the asymptomatic Plasmodium parasite population in Botswana. Interestingly, this observation was affirmed by the clinical outbreak that led to the conclusion by the WHO, during their assessment, that the malaria elimination agenda of Botswana was off course.6 Kweneng East and South East continue to be hotspots for asymptomatic P. vivax infections,2 which, unfortunately, appear to have spread together with P. falciparum into all districts. The presence of significant asymptomatic infections in the population has important implications for strategies and efforts to eliminate malaria. It has been established that ≥ 75% of Plasmodium infections are asymptomatic26; however, the strategic approach to interrupt Plasmodium transmission largely targets symptomatic infections because data from malaria control programs are accrued from passive rather than active case detection.18 Asymptomatic infections can be symptomatic during the short term or can remain for long periods28 before becoming symptomatic.29 The caveat is that the majority of asymptomatic infections are also submicroscopic.31 Therefore, only highly sensitive molecular tools can effectively assess their actual extent.33 It is necessary for malaria elimination programs to change their approach from passive to active case detection with molecular tools,35 which have the added benefit of being able to detect all Plasmodium parasites.36The results of our survey demonstrate that the prevalence of asymptomatic 38 as have been observed for P. vivax and P. falciparum, thereby affirming that they do contribute to transmission. It has also been observed that some submicroscopic infections may never progress to symptomatic infections and subtly contribute to transmission.18 There are variations in transmission patterns that are geospatially defined in a country, and these variations need to be understood. According to our report in 2016,2 Kweneng East, South East, and Tutume were the major hotspots for P. vivax infection; however, a new locus of infection for P. vivax has emerged in Ngami in the north. Investigations of the Duffy antigen phenotype has been initiated to understand the observed trend.An argument against the detection of asymptomatic infections in NMCPs is based on whether they contribute substantially to transmission. There are transmission hotspots for asymptomatic infections,P. vivax in the country, including the north, is worrisome because it has significant implications for the elimination agenda because hypnozoites can sustain transmission by serving as infection reservoirs.39 This also applies to P. ovale.13 The data regarding Duffy negativity in the population are currently unavailable; however, there is the likelihood that some of the P. vivax infections will be Duffy-negative, which will sustain the spread. Therefore, the presence of P. vivax and P. ovale makes it imperative to implement clear plans regarding the use of primaquine in Botswana. Primaquine has a spectrum of antimalarial activities that leads to the radical cure of hypnozoite stages and sterilization of gametocytes in P. falciparum.40 We previously reported that the G6PD deficiency in Botswana based on the hemizygous male frequency was 2.30% , and that the overall frequency of G6PD-deficient genotype A (hemizygote and homozygote genotypes only) was 1.26% ; these rates should be considered when deciding to implement the use of primaquine in the country.41P. vivax has been labeled as benign, although there is ample evidence to the contrary because of its association with severe malaria.42 Perhaps the lack of hyperparasitemia observed with P. vivax infections because of the preference for reticulocytes may be a contributing factor.43 Recent reports of the presence of P. vivax in the bone marrow present the hematopoietic system as a probable hiding place, in addition to the liver, thereby limiting vascular detection by methods other than PCR in nonendemic areas.44 What we have observed in Botswana can happen in other African countries that have reported the presence of P. vivax within the population; therefore, serious attention to this matter is required. An important observation is the level of anemia, which was severer for those younger than 5 years. This observation was related to the district and age, but not the Plasmodium infection status; therefore, these anemia cases are more likely to be related to the nutritional status. Nevertheless, we cannot exclude the contribution of existing coinfections. Because anemia can influence infections, and vice versa, particular attention by the NMP is required.45It is evident that transmission in Okavango has decreased for children younger than 5 years and increased for children 5 years or older. However, it is not clear what the exact reasons are for this observed pattern of infection in this region. Perhaps the persistent efforts by the NMP to mitigate transmission in the district by indoor residual spraying may be a contributory factor. Loci of infections have clearly shifted to the south and southeastern districts, and new strategies are required. The spread of asymptomatic P. vivax is spreading along with P. falciparum in the asymptomatic population in Botswana. Local factors that affect transmission dynamics need to be carefully investigated in Botswana and other African countries. To achieve the elimination of malaria, the NMP in Botswana needs to integrate molecular tools in its strategic planning.In conclusion, we have shown that


Plasmodium vivax infection is a major barrier to its control and elimination. Factors such as adequate dosing, adherence, drug quality, and pharmacogenetics can impact the effectiveness of radical cure of P. vivax and need to be adequately evaluated. CYP2D6 pathway mediates the activation of primaquine (primaquine) into an active metabolite(s) in hepatocytes, and impaired activity has been linked to a higher risk of relapse.The relapsing nature of P. vivax malaria presented repeated relapses after being initially treated with chloroquine (25 mg/kg) and primaquine (3.5 mg/kg in 14 days) at a non-endemic travel clinic. Recurring episodes were subsequently treated with a higher dose of primaquine (7 mg/kg in 14 days), which prevented further relapses in two patients. However, one patient still presented two episodes after a higher primaquine dose and was prescribed 300 mg of chloroquine weekly to prevent further episodes. Impaired CYP2D6 function was observed in all of them.Three patients diagnosed with Lack of response to primaquine was associated with impaired CYP2D6 activity in three patients presenting multiple relapses followed in a non-endemic setting. Higher primaquine dosage was safe and effectively prevented relapses in two patients and should be further investigated as an option in Latin America. It is crucial to investigate the factors associated with unsuccessful radical cures and alternative therapeutic options. Plasmodium vivax is the most geographically widespread species causing human malaria, with approximately 40% of the world’s population at risk of infection ), eight single-nucleotide polymorphisms (SNPs)  and escribed , 23. CYPescribed , 25 and , 3183G >Ethical approval was obtained from the INI/Fiocruz ethical review board (number 0020.0.009.000–07), and all participants provided informed written consent.P. vivax malaria recurrences are reported. All patients remained in the non-transmission area throughout the follow-up. Due to the lack of tools for differentiating relapses from recrudescence, criteria of classifying recurrences as either recrudescence or relapses were applied as following: recrudescence if happening less than 28 days post-treatment and relapses if occurring after this period. There was no risk of reinfection in the cases.Herein, three cases of multiple P. vivax infection . G6PD activity was tested normal. He was treated with chloroquine and primaquine . On 16th Apr 2016 , he presented another malaria episode diagnosed as P. vivax . He was then treated with chloroquine and higher-dose primaquine . CYP2D6 genotype was performed and classified as intermediate metabolizer , 78,5 kg of bw, resided in São Gabriel da Cachoeira (Amazon state) for two years (until 18th Dec 2015), where he had a diagnosis of vivax malaria on 1st Nov 2015 being treated with chloroquine and primaquine for seven days  and was treated with chloroquine and primaquine . G6PD activity was tested normal. On 5th Apr 2016, she presented to INI/Fiocruz with a vivax relapse . She received chloroquine and primaquine , and she remained without further episodes (updated 20th Jun 2017). CYP2D6 phenotype was classified as a poor metabolizer  until 14th Nov 2015, where she was diagnosed and treated for vivax malaria on 1st Oct 2015  for two months until 4th Aug 2016, where he received treatment for vivax malaria on 1st Jul 2016  recrudescence due to resistance to the blood schizonticidal drug – usually chloroquine; (ii) relapse from activated hypnozoites – which is a particularity of P. vivax and Plasmodium ovale amongst human malaria; or (iii) reinfection in areas where active transmission exist [ biology . The orion exist . Relapseon exist , suggeston exist . The facon exist . Althougon exist , 19.P. vivax as there are for P. falciparum. Standardized molecular methods allow differentiation between recrudescence and reinfection [P. vivax endemic region after the initial episodes, thereby reducing the possibility that confounding variables were responsible for the observed relapse infection. Recrudescence due to erythrocytic parasites was not probable since the parasitaemia decreased in the blood, and therapeutic failure in the presence of the drug was not reported. The minimum interval between episodes was 52 days , which supports the classification of these recurrences as relapses since recrudescence due to erythrocytic stage parasites usually occur within 28 days after treatment with chloroquine [There are no molecular methods to reliably distinguish amongst the causes of recurrence for nfection . All thePatients were oriented about the importance of treatment and reporting adverse events during the follow-up period, and returning to the clinic in case of symptoms. None of them returned to an endemic area and presented new symptoms after the therapeutic malaria period. The three subjects were tested negative for G6PDd, and the woman was not pregnant or breastfeeding. The results reported here corroborate partially with the study of Fernando et al. , indicatThis study has some limitations. First, individual CYP2D6 phenotype was inferred from genotyping data, according to activity scores of CYP2D6 diplotypes, and there is evidence for a considerable range of variation in CYP2D6 function within genotype-inferred phenotype categories . Second,P. vivax malaria [P. vivax malaria that may lead to more effective management policies.This case series, along with previous studies, points out that CYP2D6 is a possible important determinant of the efficacy of primaquine against relapse. A relevant issue for clinical management and, consequently, control and elimination is achieving a better radical cure and classifying and treating recurring episodes. Tafenoquine (TQ) has been licensed for malaria anti-relapse therapy and chemoprophylaxis by the U.S. Food and Drug Administration . The sig malaria . Evidenc malaria , 37. Con


Recognition of the symptoms and seeking prompt treatment in a health facility is a major means of reducing morbidity and prevention of mortality from severe malaria in under-fives.To document the effect of health-seeking behaviour of caregivers and severe malaria outcome in underfives seen in a tertiary health institution in Nigeria.A descriptive cross-sectional study carried out from July 2012 – June 2013. Data were obtained using a researcher-administered questionnaire.Caregivers and children (6 – 59 months) who presented with features of severe malaria according to World Health Organization criteria.p = 0.03). Caregivers whose children presented with severe anaemia were significantly more likely to have appropriate health-seeking behaviour (p =0.00). The mortality rate of severe malaria was 15 per 1000; of which 94% were children whose caregivers did not have appropriate health-seeking behaviour. Age younger than 2 years (p = 0.02), cerebral malaria (p = 0.01) and jaundice (p = 0.03) significantly predicted mortality in the children irrespective of the caregivers' health-seeking behaviour status.Of the 120 caregivers mean [SD] age (31.4 [7.0] years) /child pairs (24 [14.7] months), 35 (29%) caregivers had appropriate health-seeking behaviour. The commonest place visited for initial healthcare before presentation was the patent medicine vendors by 87 (73%) caregivers. Seventy-seven per cent of caregivers who did not have appropriate health-seeking behaviour were from the lower family social class (Less than a third of the caregivers had appropriate health-seeking behaviour for their under-fives with severe malaria, and the majority of these were from the lower family social class. Cerebral malaria and jaundice significantly predicted mortality in children with severe malaria irrespective of caregivers' health-seeking behaviour status.The study was self-sponsored by the authors Severe malaria contributes significantly to paediatric emergency room admissions in sub-Saharan Africa.Malaria disease usually starts as a simple acute febrile illness and if left untreated, progresses to the severe (or complicated) disease usually within 72 hours with predicted high mortality.8To reduce the malaria burden, the World Health Organization (WHO) recommends home treatment of uncomplicated malaria with the recommended antimalarial drugs within 24 hours of the onset of symptoms or seeking for prompt treatment in a health facility within 24 hours of onset severe malaria symptoms.et alet alHowever, some factors such as poverty, distance to health facilities, cost of transportation, and increased waiting time in hospitals had been documented as being responsible for seeking for health care elsewhere than the health facility.et alThis cost was not within reach of most families in Nigeria for the treatment of uncomplicated malaria. Nwaneri This study was carried out at the Children's Emergency Room (CHER) of University of Benin Teaching Hospital (UBTH), Benin City, South-south Region of Nigeria. UBTH is a 750 bedded tertiary health facility that serves the people of Edo State and neighbouring states of Delta in the south-south; Ondo (south-west), Kogi  and some parts of Anambra States in the southeast region. Majority of these States are within the tropical rain forest where malaria transmission is holoendemic and stable throughout the year, especially in under-fives.This was a cross-sectional descriptive study and the study was carried out from June 2012 to July 2013. A sample size 110 was determined based on 95.0% confidence interval and statistical power of 80.0% using the formula described by Araoye (2007).The children presented with one or more features of severe malaria, according to the World Health Organization (WHO) criteria.22et alThe dependent variables in this study were appropriate HSB which was defined for this study as the presentation to a health facility within 24 hours of the onset of features of severe malaria, and inappropriate HSB is when a child with features of severe malaria presented after 24 hours of onset symptoms.et al.3The independent variables were the ages of the children, their gender, family social class, household size and ages and level of education of caregivers. The family social class was determined using the method described by Olusanya At recruitment, a semi-structured interviewer administered questionnaire was used to obtain relevant data from each child's caregiver after obtaining written informed consent. The questionnaire was validated by an extensive literature review and was pre-tested on ten caregivers who were excluded from the final analysis. Each caregiver/child pair was assigned an identification number which was used for the questionnaire and laboratory samples. The questionnaire sought information on the child's and caregivers' demographic characteristics, information on causes and symptoms of severe malaria and what was done for the child at the onset of illness. Each child was examined clinically, and all features of severe malaria were documented.The ethical certificate for this study was obtained from the Research and Ethics Committee of UBTH Benin City Protocol Number ADM/E22/A/vol.VII/741. Written informed consent was obtained from each caregiver.th per cent confidence level. Frequency tables and charts were constructed as appropriate. The significance of associations was tested using chi-square and Fisher's exact test as appropriate. Logistic regression model showing socio-demographic and severe malaria features of study participants predicting mortality irrespective of the caregivers HSB status of the caregivers was carried out. The level of significance of each test was set at p < 0.05.The data obtained in this study were recorded in a Microsoft Excel 2007 sheet and the analysis was done using the statistical package for scientific solutions (SPSS) version 16.0 . Further analysis was done using GraphPad InStat software  where applicable. Quantitative variables  were summarised using means and standard deviations where appropriate at the 95Of the 120 children recruited in the study; their mean [SD] age was 24.0 [14.7] months and that of their caregivers was 31.4 [7.0] years. There were 71 (59%) male children and 49 (41%) females. Socio-demographic characteristics of the caregivers/ children are shown in Concerning causes of malaria, 95% of caregivers recognised mosquitoes as the cause of malaria while the remaining 5% attributed malaria to the dirty environment, bad water and witchcraft. All the children were said to have presented with high fever; 70 (58%) had multiple convulsions, 67 (56%) and 55 (46%) had coke coloured urine. Mean [SD] duration of illness before presentation was 4.2 [3.5] days and the mean [SD] temperature of the children at presentation was 38.0 °C [1.2] °C. The mean [SD] packed cell volume at presentation was 22.7% [9.6] %; and the Mean [SD] malaria parasite count of the children was 3069.0 [2218.0] parasite per microlitre. Hyper-parasitaemia was not observed in any of the children.Caregivers who had appropriate health-seeking behaviour (HSB) were 35 (29%) while 85 (71%) had inappropriate HSB. The commonest place for initial seeking for health care by the caregivers was the patent medicine vendor by 87 (73%) caregivers, neighbours/ traditional doctors 17 (14%) and health facilities namely private facilities/ health centres 16 (13%).2 = 7.34, df = 2, p = 0.03).2 = 5.06, df = 2, p = 0.17) and ages  of the caregivers. It was also not significantly depend on ages of the children  and the household size .Appropriate HSB did not significantly depend on the educational status (χp = 0.00). HSB of the caregivers did not significantly affect the other features of severe malaria presentation of the children.2 = 5.71, OR = 8.5, p = 0.02). These children were 8 and half times more likely to die from severe malaria,Mortality rate observed in this study was 150 per 1000; of which 94% were children whose caregivers did not have appropriate HSB (χp = 0.02); likewise jaundice by 1.2 times . Age of the children was the only socio-demographic feature that significantly predicted mortality in the children. The younger the child, the four times likelihood of death from severe malaria .Majority of the caregivers in this study did not demonstrate appropriate health-seeking behaviour for their under-fives with severe malaria. The initial health intervention for their sick children was sought mainly at the PMVs who are not equipped to provide the required care for these children.13et al1For example, studies have shown that the prescription pattern of antimalarial drugs, especially for paediatric age groups by the PMVs is poor and most times inaccurate.Lower family social class was observed to affect the appropriateness of HSB in this study significantly. Caregivers, perhaps, would need to consider what they would pay for transportation and hospital charges before embarking on hospital visit for health care services.et alPlasmodium species in these children.26Accessibility, cost, transportation, increased waiting time in hospitals could be influencing the decision to visit PMVs as the first health care provider than to go to the health facilities.Severe malaria features that had been documented to be significant contributors to mortality include severe anaemia, cerebral malaria, hypoglycemia, and acute kidney injury.et alOf note is that severe anaemia which usually presents as paleness of the conjunctiva, oral mucosa, hands and feet are also easily identified/ recognised by the caregivers and its morbidities and mortality can be prevented by blood transfusion.This was a hospital-based study hence its findings may have under-estimated the effect of HSB on malaria morbidity and mortality. For example, the children who did not present in hospital were not included in this study and these children would have died following the malaria illness at home. A longitudinal communitybased prospective study is, therefore, suggested to bridge the above limitations.This study has demonstrated that HSB is an important determinant of outcome of severe malaria in under-fives. Efforts to improve access and affordability of care in health facilities may improve HSB of caregivers of under-fives.