Plasmodium falciparum parasite results in a wide spectrum of disease outcomes in malaria. Development of severe disease is associated with a progressively augmented imbalance in pro- and anti-inflammatory responses to high parasite loads and sequestration of parasitized erythrocytes. Although these phenomena collectively constitute common denominators for the wide variety of discrete severe malaria manifestations, the mechanistic rationales behind discrepancies in outcome are poorly understood. Exploration of the human pathophysiological response by variations in protein profiles in plasma presents an excellent opportunity to increase the understanding. This is ultimately required for better prediction, prevention and treatment of malaria, which is essential for ongoing elimination and eradication efforts.The intimate interaction between the pathophysiology of the human host and the biology of the −14) were selected for a stringent analysis approach. Here, 24 proteins showed elevated levels in malaria patients and included proteins involved in acute inflammatory response as well as cell adhesion. The remaining three proteins, also implicated in immune regulation and cellular adhesivity, displayed lower abundance in malaria patients. In addition, 37 proteins  were identified with increased levels in patients with severe compared to mild malaria. This set includes, proteins involved in tissue remodelling and erythrocyte membrane proteins. Collectively, this approach has been successfully used to identify proteins both with known and unknown association with different stages of malaria.An affinity proteomics approach was used to analyse 541 paediatric plasma samples collected from community controls and patients with mild or severe malaria in Rwanda. Protein profiles were generated with an antibody-based suspension bead array containing 255 antibodies targetting 115 human proteins. Here, 57 proteins were identified with significantly altered levels  in patients with malaria compared to controls. From these, the 27 most significant proteins  contains supplementary material, which is available to authorized users. Plasmodium falciparum continues to be one of the leading infectious causes of morbidity and mortality in children worldwide [Severe malaria caused by orldwide , 2. At forldwide –5. ImporP. falciparum malaria progresses to the severe form, this imbalance becomes even more profound, pointing to an exaggerated human immune response as one key aspect in the pathogenesis of the disease.The outcome of the disease is a result of the intimate interaction between the biology of the parasite and the pathophysiology of the human host during an on-going infection. Certain aspects of the host pathophysiology are well-known. For example, the early stages of clinical illness are known to be characterized by an imbalance in pro- and anti-inflammatory cytokines as a response to parasitized erythrocytes . IncreasP. falciparum parasitized erythrocytes to platelets, uninfected erythrocytes and endothelium of the peripheral microvasculature [Severe and fatal malaria has also been intrinsically linked to the sequestration of culature . Sequestculature , 14. In culature , 16.P. falciparum malaria pathogenesis are known. There is however still a major gap in the understanding of both general and specific mechanisms behind the appearance of uncomplicated malaria and in particular the various and discrete forms of complications presented in severely ill patients [Thus, certain factors involved in the interaction between the parasite and the host and how these collectively contribute to the patients –20. Idenhttp://www.proteinatlas.org) to identify a protein panel discriminating patients with uncomplicated and different categories of severe malaria in a cohort of 700 paediatric samples from Nigeria [High-throughput screens of host protein levels in plasma present unprecedented opportunities to identify human proteins associated with disease pathogenesis. A previous in-house study by Bachmann et al. used suspension bead arrays and more than 1000 antibodies from the Human Protein Atlas  tubes. The blood was processed immediately after sampling from the patient into separate blood constituents by gel flotation . The plasma samples were subsequently snap frozen in liquid nitrogen and stored at below − 80 °C until proteomic analysis was performed . Plasma Antibodies for this screening were selected to validate previous findings by Bachmann et al.  in a newhttp://www.proteinatlas.org). In addition, 20 antibodies from R&D Systems, Abcam and Novus Biologicals were also included. Two assay specific controls were included in order to control the background; rabbit IgG  for background binding to rabbit IgG molecules and a blocked bare bead (without coupled antibody) for background binding to the beads. Furthermore, two additional assay specific controls were used as sample loading controls; anti-human IgG  and anti-human albumin . The selected antibodies were coupled onto carboxylated beads for the bead array assay , originating from the Human Protein Atlas (HPA)  [Data analysis and visualization were performed with the open source software R (ect.org)  and variAs a part of quality control, inter- and intra-assay correlations were used to evaluate assay reproducibility using nonparametric Spearman’s correlation coefficients from the R-package ‘stats’. In order to explore sample heterogeneity, the distribution of the samples was illustrated with a nonlinear dimension reduction algorithm called t-distributed stochastic neighbour embedding (t-SNE) , 27. TheThe univariate analysis included evaluation of individual protein’s ability to separate two sample groups. Student’s t-tests were used on log-transformed data for the analysis of the differences between controls and malaria cases . Wilcoxon rank sum tests were used for the comparison between mild and severe malaria. False discovery rate (FDR) by Benjamini & Hochberg  was usedMultivariate analysis was used to identify patterns in the data and to identify a potential combination of markers with higher separation power. Classification of protein level profiles was made using the unsupervised hierarchical clustering method Self-Organizing Tree Algorithm (SOTA) . The dathttps://string-db.org). The analysis was performed using all 61 presented proteins  were calculated for all replicated samples to assess the technical variability of the assay. All median CVs were below 10% (IQR = 5), both between replicates within the same labelling plate and between all replicates in the same assay plate. Furthermore, the median CV between assay plates in the first run was 8% (IQR = 2) and the median CV between the first and the second run was 10% (IQR = 3). Spearman’s correlations were calculated  were observed for 76 antibodies corresponding to 57 proteins  were selected from this list with p-values below the arbitrary cut-off 10The selected 27 proteins with the most significant differences were further characterized by SOTA clustering to reveal trends in protein level profiles with respect to disease progression   were identified with the chosen significance level Table . The relDehydration is common among malaria patients and may present a potential experimental challenge as measuring relative protein levels may result in higher signals due to dehydration, regardless of the disease state. Therefore, clinically assessed hydration status of the patients were investigated to ensure that the increased protein levels in severe malaria cases compared to mild were not due to dehydration . The samples were re-analysed, excluding dehydrated individuals in the two patient groups, to observe potential differences  or increased in febrile convulsions compared to cerebral malaria . Interestingly, prior studies have found these three proteins (together with CA2) in microvesicles derived from parasitized erythrocytes . To the P. falciparum malaria parasite as the adherence to the vascular endothelium protects the parasite from splenic clearance. The cytoadherence properties of infected erythrocytes are also intimately linked to severe malaria, as the resulting vascular occlusion prevents proper oxygenation of surrounding tissues and organs [Cytoadherence is a central process in the biology of the d organs –52. In ld organs , cytoadhIntriguingly, this study also identified proteins with a connection to cell adhesion and migration of substantially lower abundance in plasma of malaria patients compared to healthy controls. The decrease in CCL5 levels during malaria infection has been suggested to be a result of malaria-induced thrombocytopaenia . ThromboThe host proteins identified herein as variable upon malaria infection could serve purposes beyond providing clues to the understanding of host-parasite interaction and the pathogenesis of the disease. Although many of the targetted proteins are part of the pro- and anti-inflammatory responses that are shared with other infections, many others could potentially serve as prognostic markers for malaria infection. Microscopic examination of patient blood smears is still considered the golden standard of malaria diagnostics, but the specificity and sensitivity of this approach depend heavily on highly trained personnel , 58. AntLevels of 115 carefully selected human proteins were analysed in 541 paediatric plasma samples from community controls and patients with mild and various types of severe malaria, collected in Rwanda, by affinity proteomics. The results validate the previous findings of protein candidate markers associated with malaria infection done with the same affinity approach. New potential markers were identified that could be important leads towards an increased understanding of host-parasite interaction and pathogenesis of the disease. This study shows that a set of proteins, either individually or as a part of a panel, can display a highly significant discriminatory capacity between controls and malaria cases. Furthermore, a set of promising candidate markers were identified that significantly separate mild and severe malaria cases, despite the clinical overlap between these disease states. Consistent with the current literature, the identified increased levels of a variety of proteins related to acute phase immune responses and cytoadherence, but also new proteins that could be either linked to the same or other pathophysiological phenomena, such as infection-related microvesicular loads. Further evaluation and characterization of these presented proteins could enable increased understanding of their infection-biological roles and function. By increasing the understanding of the underlying mechanisms behind the clinical manifestations, this could potentially become an important component to improve treatment and prediction of disease progression.Additional file 1. Clinical patient characteristics. Table summarizing the clinical characteristics for all the 541 included patients, divided by disease subcategory. Information about sex, age, nutrition status (based on WHO reference z-score), temperature and dehydration status are provided.Additional file 2. Information about the number of individuals classified with the different severe stratifications. Table over the combination of dual severity stratifications for the 180 patients with severe malaria. Patients may suffer from one, two or more severe stratifications (not shown).Additional file 3. Supplementary method information. A. Description of the sample labelling protocol including sample plate distribution and plate controls. B. Protocol for the antibody coupling onto the carboxylated beads and sample test for estimating coupling efficiency.Additional file 4. Proteins significantly discriminating between community controls and malaria cases. Table with information about all antibodies targetting the 57 proteins  discriminating between malaria cases and controls. The information provided is listed as follows: gene name, Uniprot ID, gene description, individual p-values and antibody ID. Antibodies which names include “HPA” are generated within the Human Protein Atlas project and “R&D” from R&D Systems.Additional file 5. Proteins with significantly altered levels between mild malaria and severe malaria cases. Table with information about all antibodies targetting the 37 proteins  with divergent levels in mild compared to severe malaria patients. The information provided is listed as follows: gene name, Uniprot ID, gene description, individual p-values and antibody ID. Names of antibodies from the Human Protein Atlas project are named “HPA” and from R&D Systems “R&D”.Additional file 6. t-SNE plots. Plot A-F shows t-distributed stochastic neighbour embedding (t-SNE) plots to visualize the patient samples coloured based on different clinical parameters for all 61 proteins showing significant p-values between any of the investigated sample groups. All data points are shaped according to the sample group: community controls (point), mild malaria (rectangle) and severe malaria (triangle). A. Colouring by sample subgroup: community controls (green), mild malaria (orange) and severe malaria (red). B. Colouring by patient sex: F = female (blue), M = male (green). C. Colouring by patient age in months, ranging from 1–12 months (green) to 61–72 months (blue). D. Colouring by WHO reference z-score for nutrition based on patient age and weight. Normal nutrition (green), moderate undernutrition (blue), severe undernutrition (red). E. Colouring by patient body temperature at sampling, ranging from 35 °C (light yellow) to 41 °C (red). F. Colouring by signs of dehydration of the patient.Additional file 7. Assay variation. Variation between assays calculated as Spearman’s Rho. A. Intra-assay variation. Each data point represents the calculated median antibody MFI for 88 replicated samples during the same assay run but in different assay plates. Spearman’s correlation was calculated to 0.999. B. Inter-assay variation. Each data point represents the calculated median antibody MFI for 325 replicated samples between two runs. Spearman’s correlation was calculated to 0.965.Additional file 8. Information about proteins discriminating between controls and malaria patients. One panel for each of the proteins presented as potential markers for separating community controls from malaria cases with a p-value < 10−14. The panel includes one boxplot with protein levels for the group of controls and the malaria cases together with the Spearman’s correlation Rho for that protein between the two experiments (Exp 1 and Exp 2) and the classification power of the protein represented on ROC curves .Additional file 9. Information about proteins with divergent levels between mild and severe malaria patients. One panel for each of the 37 proteins presented as potential markers for separating mild malaria from severe malaria cases with a p-value < 0.05. The panel includes one boxplot with protein levels for the two groups and p-values together with the Spearman’s correlation Rho for that protein between the two experiments (Exp 1 and Exp 2). The second boxplot illustrate the protein profile per sample group but only including the samples that did not show signs of dehydration.Additional file 10. Information about proteins with divergent levels between febrile convulsion compared to cerebral malaria patients. One panel for each of the five proteins with a p-value < 0.01. Each panel includes a boxplot with protein levels for the group of patients with febrile convulsions and the group with cerebral malaria. The panel does also include the Spearman’s correlation Rho for that protein between the two experiments (Exp 1 and Exp 2) and the classification power of the protein represented on ROC curves .Additional file 11. Spearman correlation’s for antibodies targetting the same protein. Table of presented antibodies targetting the same protein with Spearman’s Rho > 0.70. The table also includes the gene and gene description of the target protein of the antibodies.Additional file 12. Multi-protein signature. Multi-protein ROC curve including all eight antibodies identified by Lasso and single antibody ROC curves with corresponding antibody ID and AUC.Additional file 13. Heatmap over relative protein intensities between cases with mild and severe malaria. Exploratory hierarchical clustering of samples with mild and severe malaria for all proteins with p-values < 0.05 between these two groups. An extra sample-legend is provided for sample subgroup: mild malaria (orange) and severe malaria (red).


Plasmodium species, current focus is mainly directed towards Plasmodium falciparum, and to a lesser extent P. vivax. There is a substantial lack of data on both global and local transmission patterns of the neglected malaria parasites P. malariae and P. ovale spp. We used a species-specific real-time PCR assay targeting the Plasmodium 18s rRNA gene to evaluate temporal trends in the prevalence of all human malaria parasites over a 22-year period in a rural village in Tanzania.We tested 2897 blood samples collected in five cross-sectional surveys conducted between 1994 and 2016. Infections with P. falciparum, P. malariae, and P. ovale spp. were detected throughout the study period, while P. vivax was not detected. Between 1994 and 2010, we found a more than 90% reduction in the odds of infection with all detected species. The odds of P. falciparum infection was further reduced in 2016, while the odds of P. malariae and P. ovale spp. infection increased 2- and 6-fold, respectively, compared to 2010. In 2016, non-falciparum species occurred more often as mono-infections. The results demonstrate the persistent transmission of P. ovale spp., and to a lesser extent P. malariae despite a continued decline in P. falciparum transmission. This illustrates that the transmission patterns of the non-falciparum species do not necessarily follow those of P. falciparum, stressing the need for attention towards non-falciparum malaria in Africa. Malaria elimination will require a better understanding of the epidemiology of P. malariae and P. ovale spp. and improved tools for monitoring the transmission of all Plasmodium species, with a particular focus towards identifying asymptomatic carriers of infection and designing appropriate interventions to enhance malaria control.A reduction in the global burden of malaria over the past two decades has encouraged efforts for regional malaria elimination. Despite the need to target all  Plasmodium falciparum and P. vivax. However, eliminating malaria requires the elimination of all human malaria parasites and limited interest has been directed towards estimating the disease burden attributable to the neglected malaria parasites P. ovale spp. and P. malariae. The authors used molecular methods to analyse 2897 blood samples collected in five cross-sectional surveys over a period of 22 years, and described the transmission patterns of all human malaria parasites in a Tanzanian village. They demonstrate a persistent transmission of P. malariae and P. ovale spp. despite a substantial reduction in transmission of P. falciparum, highlighting the need for more attention towards non-falciparum malaria. The authors discuss the implications of these findings in the context of current efforts for regional malaria elimination.The reduction in the global burden of malaria has encouraged efforts for elimination. Attempts to control and monitor transmission have mainly focused on the predominant malaria parasites  Plasmodium falciparum and P. vivax malaria [Since the turn of the millennium, there has been a substantial reduction in the global burden of malaria including a reduction in the clinical incidence of both  malaria –3. This  malaria ,4. SeverP. falciparum and to a lesser extent also of P. vivax. However, achieving malaria elimination requires the elimination of all malaria parasites infecting humans  [P. malariae and P. ovale spp. are reported to be widely distributed throughout tropical Africa and other malaria endemic regions of the world, their epidemiology remains far less studied than that of P. falciparum and P. vivax and both global and local temporal trends in transmission intensity are largely unknown [The focus of malaria control programmes has historically mainly been directed towards limiting transmission of st Asia) ,5,6. Whi unknown –10.P. malariae and P. ovale spp. have the potential to cause significant morbidity. Infection with P. malariae is an established cause of nephrotic syndrome, which can lead to progressive renal failure, particularly in adolescents or young adults [P. ovale spp. has in recent years been recognised as a potential cause of severe malaria [Although generally considered benign, g adults ,12 and hg adults . Further malaria –16.P. falciparum [Plasmodium species using microscopy requires both highly skilled microscopists and good quality microscopes. It is particularly difficult in asymptomatic low density infections, or mixed species infections with P. falciparum, in which both P. malariae and P. ovale spp. frequently occur [P. malariae and P. ovale spp. [P. malariae and P. ovale spp. is largely underestimated.In malaria endemic areas of tropical Africa, the majority of clinical malaria attacks are attributed to lciparum . This isly occur ,18,19. Iale spp. –23. GiveP. malariae and P. ovale spp. is greater than was previously reported [P. malariae to be more common than P. ovale spp. and have estimated the prevalence to range from 1 to 35% and 1 to 25%, respectively, depending on transmission setting [P. falciparum, there have been few studies, and none using PCR, that investigate how the prevalence of P. malariae and P. ovale spp. change over time as the prevalence of P. falciparum decreases [Over the past decade, cross-sectional studies using PCR for parasite detection have generated evidence that the prevalence of both reported ,7. These setting –29. Althecreases .P. falciparum and non-falciparum infection by analysis of samples collected in five cross-sectional surveys in a Tanzanian village over a period of 22 years. We assessed the temporal trends in prevalence of all human Plasmodium spp. in an area experiencing a substantial reduction in the prevalence and transmission of P. falciparum.In this study, we used PCR to evaluate changes in the prevalence of P. falciparum have been described in previous publications [The Nyamisati Malaria Research Project was established in 1985 in Nyamisati, a rural fishing village located 150 km south of Dar es Salaam in the Rufiji river delta area in Kibiti District, Tanzania. Malaria transmission in the area is perennial with seasonal fluctuations. Within the project, the same research team conducted repeated cross-sectional surveys between 1986 and 2016 . The surications ,33. The The project was approved by the Nyamisati village board and ethical approval was granted by the Ethical Review board of the National Institute for Medical Research in Tanzania, the Regional Ethical Committee at Karolinska Institutet (Dnr. 00–084), and the Regional Ethical Review Board in Stockholm, Sweden (Dnr. 2012/1151–32). In addition, ethical approval for the 2016 survey was granted by the Institutional Review Board at Muhimbili University of Health and Allied Sciences, a delegated activity of the Medical Research Coordinating Committee (MRCC), Tanzania. Oral informed consent was obtained from all study participants and/or their guardians and was documented in a research database. The use of oral consent was approved by the respective ethical review boards and was selected due to a low degree of literacy in the village.Plasmodium infection  in the ABI Taqman 7500 or QuantStudio™ 5 Real-Time PCR system , following a previously described protocol [Plasmodium species used in combination with a conserved reverse primer. The P. ovale- and P. malariae-probes , and the P. vivax- and P. falciparum-probes (synthetized by Applied Biosystems) were each labelled with a distinct fluorophore, and, depending on the master mix, either ROX or Mustang Purple was used as the reference dye [P. falciparum-specific forward primer, 0.125 μl (10 μmol/L) of each of the other species-specific forward primers and 0.5 μl (10 μmol/L) of the reverse primer, 0.2 μl (10 μmol/L) of each species-specific probe, passive reference dye ROX or Mustang Purple and DNA/RNA-free water. The samples were run using a cut-off of 45 cycles to define positive samples, starting with 95 °C for 20 s, followed by the thermal cycles of 95 °C for 1 s and of 60 °C for 20 s. Standards, negative and species-specific positive controls were included on each plate. The assay was optimised to detect all species simultaneously, with a limit of detection of approximately 0.5 parasites per μl blood. The PCR method does not distinguish between the two sympatric species of P. ovale, i.e. P. ovale curtisi and P. ovale wallikeri, but we established that it could detect both of them using serial dilutions of positive controls .Venous blood was collected in EDTA, separated, and stored frozen as plasma and packed cells. DNA was extracted from packed cells using Qiagen blood mini kit  (1994–1999), a BioRobot M48 Robotic Workstation (Qiagen) (2010), or a magnetic bead separation method using a Hamilton Chemagic Star Robot  (2016). Real-time PCR was used to qualitatively detect protocol . The masence dye . The reahttps://www.R-project.org) and Stata 14 . For the purpose of the analyses, a mixed species infection was defined as an infection with P. falciparum and P. malariae and/or P. ovale spp. A non-falciparum infection was defined as an infection with either P. malariae or P. ovale spp. or both. Fever at the time of survey was defined as an axillary body temperature of above 37.5 °C and/or a history of fever or “hot body” within 24 hours. Generalized estimating equation (GEE) regression models were used to estimate population-averaged effects while accounting for the statistical dependency of repeated observations from individuals participating in multiple surveys [Plasmodium spp. independently over time while adjusting for covariates, i.e. age, sex, and fever at the time of survey. A multinomial logistic regression model was used to jointly evaluate the relative risk ratio of P. falciparum mono-infections, mixed-species infections, and non-falciparum infections over time while adjusting for the above specified covariates. In all analyses, age was treated as a categorical variable with five categories . P-values <0.05 were considered significant.Data were analysed using R version 3.4.3  for P. malariae, and 136 (4.7%) for P. ovale spp.  and 0.07 , respectively, i.e. corresponding to a 93% reduction in the odds of infection from 1994 to 2010 .The observed year-wise species-specific prevalence is presented in  to 2010 . CompareP. malariae remained relatively stable during the 1990’s, with the model-estimated prevalence varying from 11.3% to 16.2%. This was followed by a reduction in the prevalence to 1.1% in 2010 corresponding to a significant 92% reduction in the odds of P. malariae infection from 1999 to 2010    . However= 0.047) .Plasmodium ovale spp. were overall least frequently detected with the prevalence of infection declining gradually during the 1990’s, from 10.0% in 1994 to 4.4% in 1999 . Similar to P. falciparum and P. malariae, the prevalence of P. ovale spp. was further reduced to 0.6% in 2010  corresponding to an estimated overall 94% reduction in the odds of infection between 1994 and 2010   compared to 2010  . However to 2010 , making P. falciparum infection in 2010, but was not as apparent for the other species.For all species, the observed prevalence was overall highest among 5 to 16 year old children . A shiftPlasmodium falciparum mono-infections represented the majority of infections and accounted for overall 73.1% (95% CI 70.7–75.4%) of infections during the study period  and 5.3% (95% CI 4.2–6.6%) of infections, respectively. In P. falciparum mixed species infections, the combination with P. malariae was most common, followed by P. ovale spp., and lastly by infections with all species  of being infected with either a P. falciparum mono-infection, mixed infection, or a non-falciparum infection declined significantly from 1994 to 2010  or a P. falciparum mixed infection  compared to a P. malariae and/or P. ovale spp. infection. There was no significant difference in the odds of presenting with fever at the time of survey between those infected with P. malariae and/or P. ovale spp. and those who were PCR negative .The number of symptomatic infections occurring at the time of the cross-sectional survey varied over the years and was greater for fections . The oddPlasmodium spp. in five cross-sectional surveys over two decades in a Tanzanian village experiencing a substantial reduction in the prevalence of P. falciparum infection. We used real-time PCR to obtain a high sensitivity and specificity in detection of both mixed-species and non-falciparum infections. Plasmodium malariae and P. ovale spp., but no P. vivax, infections were detected throughout the study as both mixed and mono-infections. Although the prevalence of all species declined over time, the decline in P. ovale spp. prevalence was smaller leading to a relative increase in the number of infections being due to P. ovale spp. Furthermore, there was a shift of P. malariae and P. ovale spp. infections from occurring almost exclusively as mixed species infections with P. falciparum to occur more commonly as mono-infections. This illustrates that the transmission patterns of non-falciparum species do not necessarily follow those of P. falciparum. These findings emphasise the need to carefully monitor the prevalence and transmission trends of non-falciparum species of Plasmodium to improve our understanding of their epidemiology and to guide specific interventions aimed at achieving malaria control and elimination.In the present study we assessed the prevalence of P. falciparum between 1985 and 2010 [P. falciparum and 94% for P. malariae, and P. ovale spp., between 1994 and 2010. We then observed a further 46% reduction in the odds of P. falciparum infection until 2016. In contrast, the odds of P. malariae and P. ovale spp. infection increased by 2-fold and 6-fold, respectively, from 2010 to 2016. The observed increase in the relative contribution of non-falciparum infections to the overall prevalence of infection is in line with reports from Burkina Faso where an increase in the prevalence of P. malariae infection was observed by microscopy as transmission of P. falciparum decreased [P. malariae and P. ovale spp. between 1990 and 2010 when the prevalence of P. falciparum decreased [P. malariae and P. ovale spp. in Dielmo has later been confirmed using PCR [Plasmodium species.Previous studies of the Nyamisati cohort have examined the changing transmission intensity of and 2010 ,33. Hereecreased . Howeverecreased . Althougecreased  used onlsing PCR . These dP. falciparum in Nyamisati between 1985 and 2010 has been attributed to the presence of a research and healthcare team who provided prompt access to diagnosis and treatment, more effective antimalarial treatment (i.e. ACTs), and vector control measures (ITNs were distributed after the surveys in 1993 and 1999) [P. falciparum prevalence observed after 2010. However, it does not appear to have affected the prevalence of P. malariae and P. ovale spp. to the same extent. In 2016, P. ovale spp. superseded P. malariae as the second most commonly detected species and its prevalence returned to levels similar to those in 1999, i.e. prior to any large-scale intervention with bed nets at the study site [The reduction in the prevalence of nd 1999) ,33. LLINudy site .Plasmodium species appear to share the same primary malaria vectors [An. gambiae complex , all of which are highly anthropophilic and predominantly indoor-biting at night [Plasmodium species differently, but whether P. malariae and P. ovale spp. are more or less efficiently transmitted by the secondary vectors compared to P. falciparum is currently unknown.In Tanzania, all  vectors . Entomolat night ,42. Accuat night ,43,44. SP. ovale spp. infections [P. ovale spp., could theoretically contribute to a lower relative reduction in transmission of P. ovale spp. compared to the other species. With the available data, it is not possible to determine whether this could explain the observed transmission patterns in Nyamisati. The first-line antimalarial treatment used at the study site did not differ depending on Plasmodium species but changed during the study period from SP to ACT when ACT became readily available in the village in 2009 [P. falciparum, ACTs are highly efficacious against asexual stages of both P. malariae and P. ovale spp. and the change of first-line anti-malarial is unlikely to have contributed to the smaller relative reduction in non-falciparum infections [According to current WHO guidelines, primaquine treatment is recommended to prevent relapses of fections . However in 2009 . As for fections ,47.P. malariae and P. ovale spp. are reported to occur as mixed species infections with P. falciparum [P. malariae and 57% of P. ovale spp. infections occurred as mono-infections. Furthermore, our data indicate that individuals harbouring non-falciparum infections are less likely to be symptomatic and thereby may be less likely to seek medical treatment. The observed shift has important implications for malaria control and monitoring of transmission intensity. It increases the importance of accurately identifying each species independently and highlights the need to detect and actively target asymptomatic carriers of infection in order to provide interventions that can reduce the transmission of non-falciparum malaria.In sub-Saharan Africa, a majority of infections with lciparum ,48–50. AThe present study is somewhat limited by the repeated cross-sectional design as well as the relatively long time-intervals between the surveys. However, a substantial number of individuals participated in multiple surveys, providing a longitudinal aspect of the study design. An even closer follow-up on the individual level may have provided a more detailed understanding of the epidemiology of non-falciparum infections. To account for annual variation in the start of the peak transmission season, all surveys were conducted during the beginning of the long rainy season  . During P. ovale  [Another limitation of the study is that the PCR-method used does not distinguish between the two recently described sympatric species of llikeri) ,34. AlthPlasmodium infection relies largely on the use of microscopy and/or RDTs that lack sensitivity for the detection P. malariae and P. ovale spp. [P. malariae infections may occur as sub-microscopic infections [P. falciparum histidine rich protein (HRP-2) are sufficient in most areas of sub-Saharan Africa [P. falciparum HRP-2-only test, which by design cannot detect non-falciparum infections, has recently been recognised as a problem for diagnosis and surveillance in Senegal where P. malariae and P. ovale spp. have also been reported to occur more frequently as mono-infections [Because molecular methods are still expensive and often difficult to implement in large scale for routine surveillance, detection of ale spp. ,52,53. Dfections . In addifections ,54. The n Africa ,54,55. Tfections .P. malaria and P. ovale spp. that occurred while the prevalence of P. falciparum declined may support previously raised concerns that strategies designed for reducing transmission of P. falciparum may be less effective in reducing transmission of the non-falciparum species of Plasmodium [P. malariae and P. ovale spp., this is likely due to their species-specific ability to cause persistent asymptomatic infections in combination with a low effectiveness of current diagnostic and surveillance tools which contribute to their resilience to interventions [P. falciparum but also for P. malariae and P. ovale spp. where asymptomatic carriage appears to be even more common [Our findings highlight some of the key challenges that will need to be addressed if malaria elimination is to be achieved. The observed increase in the prevalence of asmodium ,57,58. Fe common ,38,59. Te common ,60.P. ovale spp., and to a lesser extent of P. malariae, infections despite a substantial and continuous reduction in the prevalence of P. falciparum over a period of 22-years. This demonstrates that the transmission patterns of non-falciparum species do not necessarily follow those of P. falciparum, stressing the need for attention towards P. malariae and P. ovale spp. transmission in Africa. Furthermore, the prevalence patterns observed by PCR highlight the need for field-applicable tools to detect non-falciparum infections. Malaria elimination will require a better understanding of the specific epidemiological features of P. malariae and P. ovale spp. as well as improved tools for efficient monitoring of all Plasmodium species, with a particular focus towards identifying asymptomatic carriers of infection and designing appropriate intervention strategies to reach the goals of elimination.In summary, we observed the maintenance of S1 Table(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S1 Checklist(DOC)Click here for additional data file.


Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress.Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria.ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 , LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait , blood group O , and –α3·7-thalassaemia . We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4  and FREM3 . The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region  that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria , as was homozygosity .Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4  and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health.Both Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative. Plasmodium falciparum malaria has had a pre-eminent role in child mortality within tropical regions for the past 5000 years. This mosquito-transmitted infection spends most of its lifecycle in human beings within red blood cells, in which it multiplies approximately ten times every 2 days until controlled by either immunity or treatment. Chronic asymptomatic and repeated uncomplicated malaria episodes cause high levels of childhood anaemia and undernutrition in malaria-endemic areas, whereas severe malaria—including severe malarial anaemia, cerebral malaria, and respiratory distress—is associated with high acute mortality.Evidence before this studyATP2B4”), , and “Dantu”. We did not restrict our search by language. We supplemented our search with a review of reference lists within papers identified by our search and those from our personal records. Our search retrieved six papers containing data for malaria and ATP2B4 , two relevant papers relating to malaria and FREM3 (one case-control study and one molecular genetic study), and one laboratory-based functional study relating to malaria and the rare blood group antigen Dantu. Although previous studies have highlighted associations between polymorphisms in ATP2B4 and FREM3 and malaria risk, they have lacked detail about the precise clinical effects of these polymorphisms. Moreover, previous studies have not confirmed that the association between FREM3 and severe malaria is accounted for by close chromosomal linkage to the rare blood group antigen Dantu.We searched PubMed between Jan 1, 1960, and May 30, 2018, with the terms ,  of severe Implications of all the available evidenceATP2B4 polymorphisms affect the membrane of red blood cells, which is the main target of malaria infection in human beings, yet the haematological outcomes of these polymorphisms remain unknown. In the case of the Plasmodium vivax form of human malaria, discovery of a strong protective association between negativity for the red cell blood group Duffy antigen has led directly to design of a promising vaccine. Discovering the mechanisms by which ATP2B4 and Dantu protect against severe P falciparum malaria offers similar potential for drug and vaccine development in the future.Both the Dantu and +-thalassaemia. However, protection against malaria might also be afforded by other polymorphisms.Malaria has had a major effect on the human genome through selection of polymorphisms associated with improved survival.Here, we describe the effect of a wide range of key genetic candidates—most of which relate to the structure and function of red blood cells—on risk for severe childhood malaria in the population of Kilifi in Kenya. The aim of our study was to verify the importance of specific candidates that could provide insights into the pathophysiology of severe malaria and that might be plausibly used to underpin the development of new approaches to prevention and treatment of this debilitating disease.Our study was set in Kilifi County on the coast of Kenya.We included as cases children (aged <14 years) who presented to hospital with clinical features of severe malariaWe included as controls infants (aged 3–12 months) who were born within the same study area as cases and who were recruits to a cohort study investigating genetic susceptibility to a range of childhood diseases.Individual written informed consent was provided by the parents of all study participants. Ethics approval for the study was granted by the Kenya Medical Research Institute and the National Ethical Review Committee in Nairobi, Kenya (SCC1192) and the Oxford Tropical Ethical Review Committee in Oxford, UK (020-06).+-thalassaemia  by PCR, as described previously,We investigated the association between severe malaria and 129 single nucleotide polymorphisms (SNPs) plus one 3·7 kb deletion in 70 gene regions that had been identified as candidates through previous studiesP falciparum malaria both overall and in terms of specific phenotypes, expressed as odds ratios (ORs) for their frequency in cases compared with healthy uninfected controls. Secondary outcomes included associations between polymorphisms and inpatient mortality, and between polymorphisms and P falciparum parasite densities among severe malaria cases, as judged from peripheral blood smears.The primary outcome was the association between specific genetic polymorphisms and risk of severe R.We ascertained the sample size for this study pragmatically, as the number of children presenting to Kilifi County Hospital during the study period who were eligible for inclusion as cases. We included roughly two controls for every case to maximise power. We did all analyses using BCAS3 [rs184142841], GRIP1 [rs192909543], GUSBP5 [rs148111931], LTBP2 [rs74063230], OXNAD1 , and RHOG [rs138826089]) and one SNP was removed because more than 10% of genotypes were missing (PLEKHG1 [rs144224092]), making genotype calls unreliable  risk factor for malaria, both at a genetic level and at a sociocultural level; therefore, we used gender as a covariate in the autosomal polymorphism analyses. We did not look specifically at the effect of individual ethnic groups in Kilifi because of space and power considerations. In our primary analysis of severe malaria phenotypes, we allowed individual cases to be included more than once if they manifested more than one phenotype of severe malaria. In secondary analyses, we classified individuals uniquely based on relative mortality, using the hierarchy of cerebral malaria, severe malarial anaemia, respiratory distress, and other forms of severe malaria. For X-chromosome polymorphisms, we did analyses both overall and for each gender separately, based on our previous observations with the X-chromosome gene G6PD, in which we noted opposing effects in males and females that were undetectable in combined analyses.We calculated odds ratios (ORs) for associations of polymorphisms with risk for severe malaria and its major phenotypes, and for disease outcomes in terms of mortality, by comparing allele and genotype frequencies among cases and controls, using a fixed-effects logistic-regression model. We adjusted analyses for the confounding effects of genetic background (using self-reported ethnic origin) and the rs334 polymorphism in SNPassoc package in R. We then used the lower bound of the 95% CI of the resulting p-value distribution (p≤0·005) as our significance level for all further analyses.We tested for associations between polymorphisms and risk for severe malaria using a range of different genetic models of inheritance  and selected those that were most significant for each polymorphism. However, we analysed the SNP rs8176719 under a recessive model only, because this model was the only one that allowed us to test for an association between severe malaria and blood group O. Doing more than one statistical test can lead to an increased chance of false-positives. We, therefore, used an appropriate significance cutoff (p<0·005), which accounted for the simulated distribution of potential p values, by permuting (randomly reassigning) the case or control status 1000 times using the glm function in the stats package in R, with fixed effects for gender, ethnic group, and the genetic marker or set of markers  statistic when analysed on the transformed scale. We post-adjusted McFadden's pseudo-R2) statistic to the underlying disease liability scale, which we assumed to be normally distributed, using the method described by Lee and colleagues.genetics package in R.We assessed the proportion of the total variance in the overall risk of developing severe malaria at least once before the age of 14 years within Kilifi County that could be accounted for both by individual polymorphisms and overall. We analysed data on the raw , logit-transformed and probit-transformed scales under generalised linear models using the  markers . We calcThe funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. CMN, MM, KAR, and TNW had access to raw data. The corresponding author had full access to all data in the study and had final responsibility for the decision to submit for publication.Between June 11, 1995, and June 12, 2008, 2244 children presented to the high-dependency ward of Kilifi County Hospital with features of severe falciparum malaria. Between Aug 1, 2006, and Sept 30, 2010, 3949 infants born in the local community were recruited as controls. The clinical, demographic, and laboratory characteristics of severe malaria cases and community controls are summarised in Overall, 263 (12%) of 2244 children with severe malaria died in hospital. Mortality was highest in the subgroup with clinical features of cerebral malaria (196 of 1233 [16%]) and lowest in those who manifested other features of severe malaria (21 of 436 [5%]). 644 (29%) cases had two or more common phenotypes of severe malaria .Figure 1ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA 1 and HBA2), HBB, IL10, LPHN2 , LOC727982, RPS6KL1, CAND1, and GNAS for autosomal-related , with similar effect sizes for all three major severe malaria phenotypes , rs8176746 in ABO , and a 3·7 kb deletion in HBA .As anticipated, the strongest association with risk of severe malaria was with rs334 in enotypes . Strong ATP2B4  and rs186873296 located in an intergenic region between FREM3 and GYPE . rs186873296 between FREM3 and GYPE was associated with similar levels of protection against all three major phenotypes of severe malaria and protected against inpatient mortality  and HBA loci, which result in sickle-cell trait or sickle-cell disease and in –α3·7-thalassaemia, respectively. This analysis showed evidence of a negative interaction between sickle-cell trait and –α3·7-thalassaemia through which the protective effects of each polymorphism inherited independently seemed to be lost when both were inherited together , among homozygotes for the derived allele (GG) at rs1541255 of ATP2B4 compared with homozygotes for the ancestral allele , and among children with blood group O compared with non-blood group O cases (p=0·02). Significant associations were also noted between polymorphisms and haematological indices  compared with those homozygous for the ancestral allele  or haematological indices—was also investigated. Three significant associations were noted between candidate polymorphisms and malaria parasite densities . Parasit indices . Haemogllele AA; .Table 4PHBB, FREM3, ABO, HBA (HBA1 and HBA2), ATP2B4, LOC727982, ARL14, IL10, RPS6KL1, LPHN2 (ADGRL2), INPP4B, and EMR1 (HBB (rs334) accounted alone for 2·9% of the total variance, FREM3 (rs186873296) for 0·6%, and the remaining ten genes had a combined total of 1·7%  pump.ATP2B4 have been shown to affect platelet and endothelial function.P falciparum merozoites.P falciparum merozoite surface protein EBA-175,P falciparum parasites can also invade through pathways that involve interactions between other glycophorin molecules and a range of alternative merozoite ligands.Our study confirms the relevance of associations between severe malaria and several genes that have been described previously. ATP2B4 was first identified in a genome-wide association case-control study of severe malaria undertaken in Ghana, and replicated in subsequent severe malaria case-control studies.ATP2B4 was common in our study population, with an allele frequency of 33% among controls, consistent with selection through a survival advantage against malaria. Association signals detected within ATP2B4 in case-control studies of severe malaria undertaken to date might reflect their linkage disequilibrium with a functional mutation in the promoter region of ATP2B4 that results in reduced expression of red-blood-cell PMCA4 and, as a result, in reduced red-blood-cell Ca2+ extrusion.2+ has in the physiology of P falciparum red-blood-cell invasion,2+ is also important in both clumping of P falciparum-infected red blood cells and in their sequestration to the vascular endothelium, both of which could lead to severe and complicated malaria through the occlusion of blood vessels in essential tissues, including the brain.ATP2B4 might be relevant to protection against severe malaria that could potentially be exploited for development of therapeutic agents. Further studies are being done to confirm the precise mutation within ATP2B4 that is associated with malaria protection and describing its effects both on tissue-specific PMCA4 structure and function and on malaria-specific pathophysiological processes.A significant association signal of FREM3. The rs186873296 association tags a haplotype for the neighbouring region comprising GYPA, GYPB, and GYPEGYPA and GYPB, which encodes a blood antigen known as Dantu.FREM3 polymorphism correlated closely with the polymorphism that is specific to Dantu.INPP4B within the same gene region, seemed to also account for its close chromosomal proximity and strong linkage disequilibrium with Dantu. This finding supports the conclusion that the statistical association between severe malaria risk and SNPs in both FREM3—a gene of unknown biological relevance—and INPP4B are not in themselves causal with respect to malaria susceptibility but rather their associations might be accounted for by their close linkage disequilibrium with Dantu, which could most plausibly provide a malaria-protective mechanism on the basis of biological theory. Nevertheless, by contrast with sickle-cell trait, ATP2B4, and blood group O, we saw no discernible effect of rs186873296 on parasite densities in severe malaria cases within our study.A second association, previously identified in a genome-wide association study of severe malaria that included a subset of data and samples in our study,P falciparum parasites. On the other hand, the mechanism by which Dantu protects against severe malaria might not be mediated by reduced parasite invasion at all, but instead relate to the pathophysiology of malaria more broadly. Further work will be needed to elucidate the mechanisms definitively.On the one hand, although the Dantu polymorphism does not seem to offer protection by reducing red-blood-cell parasite invasion, the absence of any apparent effect on parasite densities might simply show that patients have severe malaria, and does not exclude the possibility that the malaria-protective effect of Dantu might be restricted to red-blood-cell invasion via a glycophorin-specific pathway by a subset of GYPA, GYPB, and GYPE loci lie in an area of the genome that has characteristics of ancient balancing selection.Comparative genetic analysis of chimpanzees and human beings has shown that the FREM3 and haematological indices among severe malaria cases are noteworthy. The most likely reason for the high haemoglobin concentrations in cases with both these genotypes is that such children are protected from all forms of clinical malaria that result cumulatively in higher levels of anaemia in children without these protective polymorphisms. Although this protection is well recognised for sickle-cell trait,FREM3. Moreover, the lower mean red-blood-cell volume and higher red-blood-cell count that we observed in sickle-cell trait cases is consistent with the findings from a previous study conducted in the same population.The associations between sickle-cell trait and homozygosity for rs186873296 in CD40LG were associated with a significantly increased risk of severe malaria, but by contrast with findings of a case-control study of severe childhood malaria in Tanzania,CD40LG and a specific phenotype of severe malaria in our current study presumably reflects the greater power of our study relative to earlier studies, because small studies are prone to false-positive findings as a result of statistical chance. Likewise, although significant associations were seen between severe malaria and polymorphisms in seven additional genes , without further data their potential for translation remains elusive.How the remaining polymorphisms described both here and in previous studies can be exploited for therapeutic advantage, in terms of their associations with the overall risk of severe malaria, remains unclear. For example, in agreement with previous studies,HBB contributes only 2·9% to the total variance in risk for severe malaria despite its large effect size because protection is only afforded to a small proportion (about 15%) of the population.Despite strong associations between severe malaria and several candidate polymorphisms, our analyses suggest that together they only accounted for a small proportion (5·2%) of the total variance in risk for contracting severe malaria in Kilifi County overall, only a quarter of the overall heritability attributed in an earlier study.HBB (6·3%) and other polymorphisms compared with the proportions we reported in our study. However, the estimates in that previous study were not adjusted for the ascertainment bias that will have resulted from the study's case-control design. It is also not clear whether the earlier estimates were generated on the observed or underlying liability scale, resulting in bias from the overall prevalence. These failures to account for prevalence and study design in previous studies highlight the need to apply the adjustments we made to compare heritability estimates across populations validly.In a previous study,3·7-thalassaemia, and large proportions of the population are affected by other polymorphisms, many of which have unknown haematological implications. Moreover, because such polymorphisms are so common, many children inherit more than one, with outcomes that—in most cases—are even less well understood. It will be important to better understand the mechanisms by which these red-blood-cell conditions protect against severe malaria, along with their broader haematological outcomes. Future research should determine how malaria-protective mechanisms might be emulated to uncover potential new approaches to the prevention and treatment of severe malaria.In conclusion, in accordance with findings of previous studies, we report that the strongest protective genetic associations against severe malaria all relate consistently to polymorphisms that affect the structure or function of red blood cells. As a result, some polymorphisms have been selected to very high levels. For example, almost two-thirds of the population in our study area were affected by –α


Background: Central to the successful elimination ofPlasmodium falciparum malaria, are tests with superior capability of diagnosing low-density parasitaemias. Empirical evidence on the performance of the commonly available diagnostics (light microscopy (LM), rapid diagnostic tests (RDT) and polymerase chain reaction (PCR)) is needed to better inform case management and surveillance activities within primary health care settings where elimination offalciparum malaria is targeted. The objective of this study was to estimate the sensitivity (Se) and specificity (Sp) and predictive values of LM, RDT and PCR tests forP. falciparum infection in children, while evaluating the effect of specific covariates on the accuracy of the tests.Methods: The study enrolled 1,563 children presenting with fever (axillary temperature ≥ 37.50C) to the Ngerenya dispensary, Kilifi County between March and December 2014. A Bayesian latent class model (BLCM) was fitted to the participants’ diagnostic data obtained from blood samples that were screened for the presence ofP. falciparum using the three tests.Results: The PCR assay registered a higher Se  than LM  but similar to RDT . However, the assay showed a similar Sp  to both RDT  and LM . Regarding predictive values, the tests yielded statistically similar estimates of positive and negative predictive values (PPV and NPV). A serial interpretation of the results of RDT and LM raised the PPVs and NPVs to >98%.Conclusions: LM and RDT afford high Se and Sp in symptomatic care-seeking children in this lowP. falciparum prevalence setting. A serial combination of the tests assures high PPV and NPV estimates. These elements, coupled with the wide deployment and affordability of the tests, lend the tests useful for guiding clinical care and surveillance activities forP. falciparum within elimination settings. However, studies report a declining trend ofP. falciparum prevalence particularly along the Kenyan coastal region4.Malaria persists as a leading cause of morbidity and mortality globally5. Light microscopic (LM) examination of thin or thick blood smears is held as the standard method for malaria diagnosis5. The test is inexpensive, generally exhibits high sensitivity (Se) and specificity (Sp) and permits parasite quantification which is a vital attribute in evaluating disease severity and guiding appropriate therapy6. Nevertheless, the test is fraught with some challenges: it requires good lab equipment and well trained microscopists that are often lacking in poor settings and it may display poor Se especially in cases of low parasitaemia given its detection limit of approximately 50 – 100 parasites per µl of blood under field conditions6.The Kenya national guidelines for diagnosis and treatment of malaria dictate that malaria treatment should be informed by parasitological diagnosis7: theP. falciparum-specific histidine-rich protein II (HRP–II) or lactate dehydrogenase (LDH) andPlasmodium aldolase, which is pan-specific8. RDTs are hailed for their rapidity, usage simplicity, suitability for use in remote settings with limited equipment and trained staff and display high Se and Sp under field conditions9. However, their Se may be limited in situations of low parasitaemia10.Rapid diagnostic tests (RDTs) are immunochromatographic tests that detect specific parasite antigensP. falciparum transmission rates and thus its prevalence within the country11, low parasite densities in the population are anticipated that may compromise the Se of LM and RDTs9. This situation may warrant alternative tests capable of detecting diminished levels of parasitaemia. Molecular-based techniques such as polymerase chain reaction (PCR) assays are touted as being less subjective and affording high Se and Sp in low parasite density settings13. Nevertheless, since PCRs may detect non-viable parasites – quite sensibly common in elimination settings – their utility in guiding national guidelines for clinical case management is vague. Empirical evidence on the performance of these diagnostics in low-transmission settings is thus necessary to better inform management and surveillance efforts forP. falciparum malaria.With declining18. A drawback of this approach is that, given the imperfection of these references, the index tests’ characteristics are subject to bias. Moreover, for index tests presumed to have superior accuracy to the existing reference test, their evaluation based on the reference test is impractical. In the absence of a reliable reference test, latent class models (LCMs) allow for the simultaneous estimation of Se and Sp of two or more tests without any assumption about the underlying true disease status of each individual19. LCMs can be fit using either maximum likelihood or Bayesian methods20. Essentially, Bayesian methods are preferable when observed data are insufficient21.The diagnostic performance of RDTs has previously been evaluated using LM/PCR as a reference testP. falciparum infection in children, while evaluating the effect of specific covariates on the performance of the tests.In heterogeneous populations, when information on some covariates perceived to influence the performance of index tests is available, stratified estimates of Se and Sp are computable and, reasonably, are more relevant than singular estimates. Of note, estimates of Se and Sp are characteristics specific to a test. However, once the test is applied in any given population, our interest rests on predictive values since the present concern is whether a particular tested individual has/does not have the disease in question given his/her test status. Therefore, the objective of this study was to estimate (within a Bayesian framework) the Se and Sp and predictive values of LM, RDT and PCR diagnostic tests for22. Notably, the KHDSS area spans a population of approximately 260,000 persons in an area of about 891km222. The area experiences a bimodal rainfall pattern, with long rains coming in the months of April to July and short rains in October and November. Malaria is endemic and transmission occurs throughout the year, with annual entomological inoculation rates ranging between 30 and 1002.The study participants comprised children aged <15 years presenting with fever (axillary temperature ≥ 37.5°C) to the Ngerenya dispensary, Kilifi County between March and December, 2014. This facility is situated within the Kilifi Health and Demographic Surveillance System (KHDSS) area on the Kenyan coast where, among other infectious diseases, malaria screening is conducted routinelyP. falciparum infections. Specifically, a 50 µl finger prick blood sample was collected for RDT, a slide for LM and an EDTA for PCR. Rapid diagnosis was carried out by trained health workers at the facility while slide and EDTA blood samples were stored in cooler boxes and transported to the KEMRI-Wellcome Trust Research laboratory, Kilifi where the LM and PCR tests were run by trained laboratorians. Examiners for parasitaemia using any of the diagnostics were blinded to the results of the other tests. Besides the samples, the participants’ socio-demographic characteristics  were captured.At the dispensary, blood samples were collected from the study participants for immunological examinations and assessment ofParents/guardians of enrolled children provided written informed consent agreeing to their children’s participation in the study. In addition, assent was secured from the participating minors. Approval for the study was obtained from the Kenya Medical Research Institute (KEMRI) Ethical Review Committee (SSC No. 2617).P. falciparum parasite or its HRP-II antigens/products or debris at any concentration level.The latent (unobserved) infection status (referred to here as parasitaemia) targeted for detection by the three tests: LM, RDT and PCR, represents a blood sample containing either the live23. Briefly, thick and thin blood films were stained in 3% Giemsa solution for 45 to 60 minutes and examined under a light microscope at 1000× magnification for malaria parasites. Parasite quantification was achieved by counting the number of malaria parasites per 200 leucocytes. Parasite density per µl of blood was estimated assuming 8000 leucocytes per µl of blood and reported by species i.e.P. falciparum,Plasmodium malariae andPlasmodium ovale. For analytical purposes,P. falciparum densities above zero constituted a positive result; otherwise negative.Malaria microscopy was performed as per standard guidelinesP. falciparum specific HRP-II antigens in the collected blood samples in accordance with instructions contained in the CareStart™ Malaria manual (AccessBio). A total of 5 µl of blood was added into sample wells followed by 60 µl of assay buffer solution added to assay wells. The blood-buffer mixture was then allowed to flow towards the test and control windows. The presence of two colour bands denoted a positive result; one band (the control line) indicating a negative result.A CareStart™ Malaria RDT kit  was used to test for the presence of25. Briefly, 30 µl of blood was used for DNA extraction using a QIAxtractor machine . In a subsequent step, the extracted DNA was eluted in a volume of 100 µl, after which 5 µl of sample DNA was amplified in a thermal cycler . Specifically, 5 µl of DNA was added to 45 µl of amplification mixture containing TaqMan buffer, 250 µM of each deoxynucleotide triphosphate, 0.125 U Amplitaq Gold polymerase, oligonucleotide primers and TaqMan probe (5’-FAM-AACAATTGGAGGGCAAG-NFQ-MGB-3’)24. In about 10 minutes at 95°C pre-incubation, PCR amplification was carried out for 45 cycles  using a TaqMan assay for the highly conservedP. falciparum multicopy 18S ribosomal RNA gene. Quantification was achieved based on theApplied Biosystems 7500 software v2.0.6. The method has a quantification limit of 4.5 parasites/µl of blood. Three negative control wells and seven serial dilutions of DNA extracted from anin vitro culture of theP. falciparum 3D7 parasite strain were included on each plate as standards24. Samples with PCR readings beyond zero were considered positive.The PCR analysis was conducted as described elsewhere26. Arguably, therefore, the facility data represented a sample drawn from a single target population that formed the basis for derivation of Se and Sp of the three tests.Organisationally, within the Kenyan health system, a dispensary denotes a primary care unit serving an immediate catchment populationOpenBUGS v3.2.227 but called fromR software v3.4.3 via the ‘BRugs’ package28 v0.9-0 was used to infer prevalence, the tests’ characteristics and corresponding predictive values. Notably, the analysis was informed by the guideline for standards for reporting diagnostic accuracy studies that use BLCMs (STARD-BLCM)29. Code used to run this analysis is available as underlying data30.Initially, based on the participants’ visit dates, a dichotomous ‘season’ variable  was generated. A Bayesian latent class model (BLCM) built in19. For our situation, the three tests were assumed to be conditionally independent given an individual’sP. falciparum infection status. This is sensible considering that the tests target different aspects of the parasite. As such, statistically, for an individual whose infection status is known, their probability of testing positive (or negative) to one of the tests remains the same regardless of their prior outcomes to the other tests. In order to evaluate the separate effects of ‘season’, ‘sex’ and ‘age’ (dichotomised into <5 yrs and ≥ 5yrs31) on the Se and Sp estimates of the tests, we relaxed the assumption on constancy of the tests characteristics by stratifying the single population into subpopulations defined by the levels of the covariates. This allowed for the computation of stratum-specific tests estimates. Hypotheses for the differences between the stratified estimates were evaluated using a BayesianP – value.In fitting a BLCM, three assumptions are necessary: (1) the target population should consist of two or more subpopulations with different prevalences, (2) the Se and Sp of the tests under evaluation should be constant across the subpopulations and (3) the tests should be conditionally independent given the disease statuskO) of the different test combinations  were assumed to follow a multinomial distribution of the form:Counts  in subpopulationk andkp is the specific prevalence for thethk  subpopulation.kProb is a vector of probabilities of observing the different combinations of test results, andkn reflects the number of individuals tested for thethk subpopulation. For instance, in the 1st subpopulation for an individual testing positive to each of the three tests,prob1 is given by:Wherek) and tests (i) fulfil the equation:k ≥i/(2i–1– 1)32.For each covariate, the resulting two subpopulations furnished 14 degrees of freedom sufficient to estimate 14 parameters  – suggesting identifiability of the model. Of note, model identifiability can at least be justified if the number of subpopulations  associated with testbeta) were used to fit the Bayesian model since no reliable prior information was available for any of the tests parameters. A separate (non-stratified) model ignoring differences in tests Se and Sp across covariate levels was also fitted and the relative goodness of fit for the nested models compared using the Deviance Information Criterion (DIC) .Non-informative priors .n = 1029) were <5 years of age, 47.3% (n = 739) were female and 34.5% (n = 492) made visits during the dry season.The cross-tabulated counts of the three tests’ outcomes by covariate level are displayed inP. falciparum are presented inP-value. Furthermore, the non-stratified model gave better fit (DIC =41.7) to the data than any of the covariate-stratified models  and was thus utilised for subsequent analyses.The stratum-specific estimates of Se and Sp of the three tests forP. falciparum are shown inResults of the estimates of Se and Sp of the three tests together with their respective predictive values and prevalence ofP. falciparum infection in children along with their associated predictive values. Enøeet al.20 contend that a BLCM framework permits derivation of true estimates of index tests devoid of classification errors that may be introduced by the utilisation of an imperfect reference test. Thus, the findings of this study can be considered readily generalisable to other settings with similarP. falciparum infection burden in children.Using latent class analysis we have estimated the accuracy of LM, RDT and PCR tests for the diagnosis of3, season33 and sex34, it is conceivable that the accuracy of malaria diagnostics may be influenced by these covariates. To test for this, the Se and Sp of the three tests were allowed to vary by the aforementioned covariate levels. However, it was shown that neither of the tests’ characteristics differed significantly across the levels of any of the covariates. This implies that the performance of the tests is not influenced by either the prevailing season or the age and sex of the presenting patient. Nonetheless, in São Tomé and Príncipe, LM was reported to have a lower Se in afebrile under-five children suggesting the inadequacy of the test in detection of low-density parasitaemias35.Since malaria transmission dynamics have been shown to differ by ageP. falciparum infection was estimated to be 5.6% , suggesting a low transmissibility of the parasite in the population. Accordingly, the PCR assay registered a higher Se estimate than LM but similar to RDT upholding its capability in detection of low density infections37. In particular, Manninget al.37 recorded comparable Se estimates for both a nested PCR and RDT in the diagnosis of severe falciparum malaria among Papua New Guinean children. The PCR’s superiority to LM in detection of low parasitaemias is owed to its low detection limit of <5 parasites/µl of blood39 compared to an LM’s limit of roughly 20 parasites/µl of blood in research settings6. Nonetheless, in some reference laboratories LM may detect parasite densities in the region of 10 parasites/µl40. It was further shown that both LM and RDT achieved comparable Se estimates, which coincides with observations of similarity in these estimates at ~100 parasites/µl of blood41.In the present study setting, the prevalence ofP. falciparum HRP-II genes are deleted from a large segment of the parasite population42. False negativity may also arise where parasitaemic levels fall below the detection threshold – that is, 100 parasites/µl of blood. Besides, in tropical settings, extreme heat and humidity may degrade the antibodies that bind antigens resulting in negative test outcomes43. As regards Sp, the three tests yielded comparable estimates that concur with findings observed elsewhere45. In a low-prevalence setting, false positive test results (that undermine a test(s) Sp) represent a key concern. False positivity in RDTs has been noted due to cross reactions in rheumatoid factor positive patients, gametocytaemia or in situations of persistent antigenaemia with HRP-II antigens in previously treated patients46. Especially due to HRP-II antigenaemia, RDTs that target the LDH antigens are evidently more suitable in monitoring treatment efficacy owing to their rapid clearance from blood47. False positives by PCR may be attributable to detection of non-viable parasites (parasite debris) in treated patients or contamination in the laboratory process.False negative RDT results that may compromise the test’s Se estimate, are reported to occur whenP. falciparum prevalence. A serial interpretation of the results of both RDT and LM raised the confidence to >98% in both positive and negative test outcomes. Consequently, in this low-transmission setting where false positives are increasingly expected, the most optimal testing strategy should be one that has all individuals initially screened by the more sensitive RDT test, with any resulting positives followed up with the more specific LM. Only those individuals positive to both tests should be eligible for treatment. This multiple-test approach is pivotal to reducing the risk of parasite resistance that can occur when individuals are unnecessarily subjected to artemisinin therapy48. The rationale for employing the RDT-LM test combination owes to the wide deployment and affordability of the tests in most primary care settings49 granting them promise towards informing clinical care and surveillance activities aimed at eliminatingfalciparum malaria. Moreover, as quantification of parasitaemias is central to the management of severe malaria and assessment of treatment response36, in this respect, LM affords an added merit. By contrast, as PCRs demand hefty investment in equipment and reagents as well as highly trained personnel, their potential for routine use in low-resource field settings is limited.In this population, the three tests displayed comparable estimates of PPV and NPV. In particular, these estimates signify a reduced confidence in a positive compared to a negative test result ascribable to the lowP. falciparum malaria elimination efforts. Importantly, low-density parasitaemic individuals present as potential reservoirs of infection to uninfected mosquitoes so that, if undetected, transmission may be sustained silently36.The strong confidence realised in a negative test outcome is especially fundamental in a low-transmission setting where the preponderance of low-density infected individuals calls for their accurate detection not only to inform treatment but also to guide successfulP. falciparum infection in symptomatic care-seeking children as well as their associated predictive values. It was shown that the PCR assay’s Se was significantly higher than that of LM but similar to RDT. Nevertheless, the Sp estimates of the three tests were similar. Furthermore, the three tests produced comparable estimates of predictive values. In an elimination setting, a serial interpretation of the results of RDT and LM should guarantee high NPV and PPV; attributes that are indispensable in assuring treatment efficiency and guiding surveillance activities geared towards eliminating falciparum malaria in primary care settings.Using a Bayesian approach, we have derived the Se and Sp of LM, RDT and PCR for the diagnosis ofdgc@kemri-wellcome.org). The replication data and analysis scripts for this manuscript are available from the Harvard Dataverse.The raw dataset for the study is stored under restricted access since it contains sensitive participant information. Notwithstanding, accessibility is possible upon placing a formal request to our Data Governance Committee Ngerenya_tests_data.tab (Study dataset)Creative Commons Zero “No rights reserved” data waiver(CC0 1.0 Public domain dedication).Data are available under the terms of the I have no further comments.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Revisions have sufficiently addressed my concerns. I withdraw my reservations and would like to amend the status to ApprovedI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Thank you for taking the time to address my comments. The revised version of the paper is much improved. However, I still have one comment that I think merits some attention. Namely, the authors have carefully stressed that the population being studied is restricted to children. What is missing is that these are all 1) symptomatic/febrile and 2) care-seeking children. Although not all fevers are likely attributable to the malaria infection, any ones that are would typically be associated with higher parasite densities. Therefore it is not surprising that the performance of both RDT and LM tests was so good. This caveat with the population being studied is not made clear in the conclusions, both in the abstract and main text which is particularly important as it affects the generalisability of these results. For example, the performance of the diagnostic tests is good in symptomatic care-seeking children in this low transmission setting. This is a minor but important nuance.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. The main aim of the study was to estimate the sensitivity, specificity and predictive values for parasite prevalence estimated by light microscopy, HRP2 based RDT and PCR in a group of children.Abstract:Methods: Only the total number of children recruited was stated and the exact number of asymptomatic vs symptomatic children was not stated. Conclusions: LM and RDT tests RDT, rapid diagnostic tests ends with test so the test after RDT should be replaced or removed.Introduction:The sentence ''the tests target...” is inaccurate, there are other Plasmodium antibodies on malaria RDT kits other than P. fal HRP2 and LDH.Methods:The study comprises of "asymptomatic". This should be rephrased. The study comprised of healthy, asymptomatic and symptomatic children.The sample size for the three categories  of children should be stated.How much blood was collected? The volume should be stated.What is the definition of fever? And what is fever status?The sample collection section only stated blood was collected and used for thick and thin smears and RDT preparation. Where did the blood for the PCR come from?Technically 30ul of blood being eluted with 100ul of buffer suggests very low DNA concentrations and in an asymptomatic population, a very low concentration. Could the negative PCR results just be the result of very low template concentrations?The description for the PCR procedure was very confusing, please rephrase with clarity. Was 5ul of DNA and blood both used for the amplifications?Conclusion:No p-value in any of the tables were significant, thus this statement in the conclusion is very confusing and seemingly inaccurate.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Overall comments: This manuscript describes use of a latent class analysis to estimate the performance of three different diagnostic tools for malaria. The models and statistical methods are well described and the results are an interesting addition to the thinking about malaria diagnostic performance in a low transmission setting. However, I can only approve with reservations. As this paper is currently written, important nuances with the interaction between diagnostic test sensitivity and parasite densities , sufficient details on the study population for the results to be interpreted accordingly, and how this relates to the broader generalizations that can be made should be addressed. Specific comments:The background argument to justify the study should be reframed slightly to better reflect the nuances with malaria diagnostics. The diagnostic performance of RDTs and LM has been assessed vs PCR in many research settings and is now considered as the gold standard, including some of the references cited by the authors. The text suggests that this is not the case with LM being the main comparator.Similarly, the authors state that PCR has presumed superior accuracy, but PCR is known to have superior sensitivity compared to RDTs and LM. The key question with PCR, as the authors state, being does that matter in a clinical/elimination setting? There is evidence that standard PCR methods are not perfect with the harder we look, the more parasites we’ll find. This argument should be included here as a better justification of the approach taken. Samples are based on suspected clinical cases under 12 years of age and children 15 years of age sampled in the community. These populations are inherently different in terms of their likely parasite densities in infected individuals  and demographically in terms of factors associated with care-seeking behavior. This is a critical strata that is currently missing to assess any effects on the Sp/Se of the tests and may contribute to the lack of effects observed. As a related point, in the discussion, the authors state that Se/Sp of RDT and PCR have been found to be similar in the diagnosis of severe malaria in children in a clinical setting. This is not surprising as clinical cases of malaria are likely to have parasite densities well above the limit of detection of RDTs. This is very different than detection infections with expected low parasite densities. As above, the critical implications of the populations being studied on the interpretation of the results in this context should be more carefully expressed and acknowledged.et al., 20151). It is therefore critical to interpret the resulting Se/Sp estimates as detection of malaria infections in children. Results from this study are not generalizable to adult populations.Parasite densities in children are expected to be higher and more likely to be detectable using routine diagnostic tools .LDH tests are also much less sensitive in detecting infections so may not be the best choice for monitoring treatment efficacy.False positive PCR results may also be linked to contamination in the lab process.Although routine use of PCR in most malaria endemic settings is impractical as the authors suggest, in low transmission/pre-elimination settings would there be a role for reference labs to be set up for confirmatory testing?In the introduction the authors state that low density/PCR detectable infections are of unconfirmed importance, but the conclusion is that they are essential to remove as they are a potential source of onward transmission? This seems contradictory. In the introduction are the authors referring to the current WHO position? And in the conclusion the position from some of the research community?I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We are highly appreciative of your comments and suggestions towards improving the quality of this manuscript. However, there are a few issues you raise that we feel could be best addressed here: I’m not aware of any RDTs for Pf that detect LDH only. Do the authors mean detect HRP-II and LDH?1.Response: Some available literature does make specific mention of RDTs that detect only LDH – see for instance Wongsrichanalai et al.6 andWHO9.False positive test results are equally of concern in high-prevalence settings .2.Response: Going by PPVs, in a low-prevalence setting a test with a moderate Sp is likely to generate a much lower confidence in a positive result compared to using the same test in a high-prevalence location. Therefore, false positive results would, arguably, be of higher concern in the former settings.LDH tests are also much less sensitive in detecting infections so may not be the best choice for monitoring treatment efficacy.3.Response: Although in general LDH tests are less sensitive, when specific interest lies in monitoring treatment efficacy, a number of authors contend that Sp is a more desirable attribute6,9,47 – which disfavours HRP-II tests owing to antigen persistence.Although routine use of PCR in most malaria endemic settings is impractical as the authors suggest, in low transmission/pre-elimination settings would there be a role for reference labs to be set up for confirmatory testing?4.Response: Although, reference labs are indeed vital  in elimination settings, we believe that a suitable confirmatory test should be one that affords a high Sp and thus PPV. For this reason a serial combination of available diagnostics (such as RDT and LM as proposed here) should assure an almost complete confidence in a positive test result.