Background: Malaria is caused by one of five currently knownPlasmodium parasite species causing disease in humans. While modelling has provided information of the vector, the same is not entirely the case for the parasite. The World Malaria reports of 2014 to 2016 reported 100% of confirmed cases from Nigeria being due toPlasmodium falciparum. Generally, about 98% of cases of uncomplicated malaria in most regions surveyed in Nigeria recently is due toP. falciparum, with the remainder being due toP. malariae. This study aimed to determine the proportions ofPlasmodium parasites causing uncomplicated malaria in Wamakko Local Government Area of Sokoto State, north-western Nigeria.Methods: The study was a descriptive, cross-sectional study conducted during the rainy season and dry season in north-western Nigeria. The area has a ‘local steppe’ climate and Sudanian Savannah vegetation. Sampling was via multistage cluster sampling. Selected participants were examined for pallor, palpable splenomegaly and signs of complicated malaria. Blood samples were also taken for rapid diagnosis of malaria and thick and thin films to identify parasitaemia and the parasite species. Participants found to have malaria were treated with Artemether/Lumefantrine and those with complicated malaria were referred to the nearest hospital. Results: We found a parasite prevalence of 34.8% overall, which was higher in the rainy season (49.3%) than in the dry season (20.2%). There was monoparasitaemia ofPlasmodium falciparum throughout the study area, irrespective of the clinical status of the participant. Mapping of the parasite was extended throughout the Local Government Area and the State.Conclusions: Despite the intermediate endemicity in the area.P. falciparum monoparasitaemia affirms theories of disappearance of other parasite species, either due to faltering control ofP. falciparum or more efficient control of other species. Plasmodium species causing diseases in humans. These areP. falciparum, P. vivax, P. ovale, P. malariae andP. knowlesi. Scientists have modelled the anopheles mosquito vector extensively based on its characteristics, but not for the parasite, it has been difficult to predict its preponderance and distribution, with notable exceptions1. An absence of the Duffy antigen on red blood cells of West Africans has long been postulated to be responsible for the absence ofP. vivax in these areas2, but cases ofP. falciparum,P. malariae andP. ovale, in order of decreasing occurrence, have been found. The World Malaria Reports of 20143 and 20154 reported 100% of confirmed cases in Nigeria as being due toP. falciparum. It is generally thought to account for about 98% of all malaria cases, withP. malariae accounting for the rest, often as a co-infection withP. falciparum5. This figure likely over-estimates the proportion of cases asP. falciparum is responsible for most severe cases of malaria; these are the cases most commonly reported alongside confirmed cases of malaria, which are tracked by passive surveillance in Nigeria. It may also be because of limited expertise in identifying other species ofPlasmodium.Malaria is caused by one of five currently knownP. malariae in a study at a time when most of Nigeria was considered holoendemic for malaria.P. malariae was often seen in coinfection withP. falciparum, particularly among younger age groups.P. ovale was responsible for 5% of malaria infections, being more common in children under five years of age, andP.falciparum ranged between 84.4% and 90.5% across age groups6. The proportion ofP. malariae was high, probably because the data was obtained from a survey of both asymptomatic and symptomatic participants.Available data from across Nigeria shows a mixed picture; large areas across northern Nigeria in 1967/68 found an average proportion of 22% of malaria parasitaemia due toP. malariae rate as low as 1.6%, withP. falciparum responsible for 98.7% of infections, sometimes in co-infection withP. malariae5. Children aged less than 10 years and all individuals in every third household were selected for this abridged malaria indicator survey (MIS). Crucially, however, noP. vivax or P. ovale species were seen either in this location or another in south-eastern Nigeria, which was shown to have a higher rate ofP. malariae infections (around 30%) and lower rate ofP. falciparum infections (68.1%) in a study also conducted in 20107. This study, however, included 2,936 individuals from 1400 clusters in Abia state, spread out across the state. Quality control measures in the identification of parasite species were implemented in the study, including a WHO-certified malaria microscopist, giving credibility to the results obtained7. In south-western Nigeria, a study in Ikorodu in 2012 recruited 1,496 participants of all ages, which included 237 children under the age of five years and 509 children aged 15 years and below. Microscopy and DNA evaluation was used to determine parasite species, which found that 93.6% of participants hadP. falciparum infection, with the remainder beingP. malariae8. This is in contrast to previous studies in 1976 around the same location in south-western Nigeria, which found that 13% to 16% of parasitaemia was due toP. malariae, with 62 to 76% being due toP. falciparum9. These proportions were the age-group specific parasite prevalence in the study, which included mostly children aged five to ten years  in an attempt to compare spleen and parasite rates among individuals with sickle cell trait and those with normal adult haemoglobin. It also foundP. ovale in 2% to 3% of participants in 5–10 and 2–4 year age groups, respectively. These findings, although limited in scope, perhaps suggest a changing trend, with the disappearance ofP. ovale from Nigeria over time.P. falciparum is an undisputed leader in all the studies performed. Its high proportion perhaps accounts for high rates of malaria-related anaemia in most studies, explained by the ability of the parasite to invade and destroy both young and senescent red blood cells10. Most of the data regarding the distribution of plasmodium is local and specific for locations where the studies are performed and the national estimates are mostly based on estimations. The knowledge needs to be updated constantly, in view of the changes over time, to help in appraising the efforts at controlling malaria.More recently, in 2010, prior to the commencement of nationwide LLIN distribution, a study including 4209 individuals in Jos, northern Nigeria, found aWe conducted this study to determine the true relative proportions of parasites causing clinical malaria in Sokoto, north-western Nigeria.Ethical approval was obtained from the Independent Ethics committee of Usmanu Danfoidyo University Teaching Hospital, Sokoto, Nigeria with ethical approval number UDUTH/HREC/2014/No. 246. Ethical approval was also obtained from the Independent Ethical committee of the Sokoto State Ministry of Health with the approval number SMH/1580/VIV. Permission was also obtained from the district heads of the included communities in the study to visit the communities.2, with a projected population of 260,860 by 201911. It is located at coordinates 13°2′16″N 5°5′37″E. The geography of the area is predominantly flat plains with Sudan Savannah-type vegetation and it stands at an altitude of 292m above sea level, near to the confluence of the Sokoto and Rima rivers. Its climate is tropical, described as local steppe climate.The study was conducted in Wamakko Local Government Area of Sokoto State, located in the north-western geopolitical zone of Nigeria. It has an area of 732.146kmThe study was a two–point, cross-sectional prospective descriptive study conducted during the rainy season and dry season. In April and November 2016, we screened and recruited participants simultaneously until we reached the target population.12, assuming a prevalence of 50% based on a previous survey13, and 500 participants gave a power of at least 80% to show reliable results.We determined the minimum sample size using Cochran’s formula14, approximately 892 households were required to meet the target of at least 500 participants per season based on the assumptions stated earlier. This was surpassed by the estimated number of households within the eight settlements selected. All children in the secondary clusters who fulfilled the inclusion criteria, and whose parents consented to participate, were included in the study.As is the norm for MIS’s, multistage cluster sampling in proportion to size was employed. The sample was stratified in two stages. First by the political wards and second by settlements. The samples were selected at each stratum independently. In the first stage, the strata were selected proportionate to their size. The details of the settlements are in the supplement number 1. The primary clusters were four randomly selected wards of the eleven political wards within the Local Government Area (LGA), with secondary clusters being eight settlements randomly selected from the four wards; proportionate to size, making up the total sample size. Based on the assumptions of a 70% response rate and that 80% of households include at least one child less than five years of age, in accordance with a previous Nigeria MIS in 201036. Recruitment was carried out on consecutive days until the entire village was covered. Each participant was evaluated once except for those who had parasitaemia without symptoms, who were followed up by a field assistant for up to 48 hours for the development of symptoms. The period of recruitment was about a month in each season.Participants were visited at their homes and while in the house, after identifying the household head. They were provided with information regarding the study and all eligible children within the household invited to participate. Those who accepted to have the children in the household included in the study signed or thumb-printed the informed consent form. All children in the selected settlements who met the age criteria of two to 10 years, with or without symptoms of malaria, were recruited for the study, provided they had been residents of the study area for at least two weeks. They were, however, excluded if they were suspected to have taken any medication with antimalarial properties within the two weeks prior to enrolment15. The WHO criteria for severe malaria was used16 to diagnose severe clinical malaria. Using a single use lancet, we collected capillary blood by pricking the index finger of the child’s left hand. A drop of blood was collected each for a thick and thin malaria parasite film for estimation of parasite density and species identification, respectively.We conducted the study procedures at a central location in each of the study villages. Field assistants went from house-to-house and recruited the participants and then brought the consenting participants to the central location. The lead investigator screened potential participants for eligibility and the caregivers of eligible participants were required to sign informed consent forms. All recruited subjects were issued with a unique study number, with which they were identified for the entire study. He performed a physical examination for each participant and graded splenomegaly according to Hackett’s criteriaP. falciparum.Concomitantly, we did rapid diagnosis of malaria using a drop of blood with CareStart® Malaria HRP2 rapid detection tests (RDTs) , which can detectDiagnosis of malaria parasitaemia was done using malaria microscopy. Each day, we transported the samples to the paediatric department laboratory of the Usmanu Danfodiyo University Teaching Hospital and fixing of thick films was done with methanol. Thin films were stained immediately and stored in the lab. We analysed the samples in a completely anonymized manner in pairs of thick and thin films; examining the thin film if we found the thick film positive for malaria. The study numbers were the only identifiers for the thick films, which were kept apart from the thin films. A trained malaria microscopist performed the analysis, under the supervision of a medical parasitologist. We examined at least 10 fields before a slide was declared negative for malaria parasites.17.The tail segment of the thin films was viewed by the lead investigator to identify the species of malaria parasite, using the typical description of parasite species, having been trained on parasite identification Quality control of the diagnosis of the parasitaemia was provided by a trained medical microbiologist re-examining 10% of the slides selected at random. A discrepancy of 10% or more would have necessitated reanalysis of all the thick films and the thin films subsequently. The discrepancy was 3% (kappa score of 0.71) and as such, this was not necessary.18 but only the first dose was directly observed. Those with severe malaria were determined using the WHO criteria for severe malaria. These children were treated with an initial intramuscular dose of artesunate dosed according to the age19 and referred immediately to the nearby tertiary hospital (UDUTH).Study participants were determined to have clinical malaria, by the presence of at least one symptom of malaria and a positive RDT or thick blood film. These were treated by the study paediatrician at home with Artemether-Lumefantrine. Children were dosed according to standard dosingWe analysed the data using SPSS version 22. We determined the prevalence of malaria by parasitaemia and RDT by determining proportions no tested positive by each method/ no tested. We used descriptive statistics to determine averages and proportions. Participants with missing data were excluded from the analysis. We carried out sub-group analysis for age, gender and season and used kappa analysis to control the quality of malaria diagnosis.20.We screened a total of 1136 participants for inclusion in the study after they consented to participation in the study. We excluded 109 because they had been treated with antimalarials in the two weeks prior to enrolment and excluded 10 from the analysis due to incomplete data. We included 1017 participants in the analysis 20.The age-sex distribution showed that all ages were equally represented in the study, as shown inWe found an overall prevalence of malaria for the study of 34.8% using microscopy and 33.8% using RDT as shown inWe saw the highest age-specific prevalence among participants aged two years, with the lowest among ten-year olds. Children aged three years of age at the time of the study had the highest frequency of uncomplicated clinical malaria (42.7%), while the highest frequency of severe complicated malaria was seen among 2-year-olds (9.8%). Children aged 10 years, had the lowest proportion of infected children showing complicated or uncomplicated clinical disease (66.7%)P. falciparum malaria, irrespective of the season and nature of their clinical presentation. The relative proportions of the results of malaria infection are depicted inOf the 354 children included in the study with malaria parasitaemia by microscopy, 279 participants were found to have clinical malaria across the seasons and all of them had21. The number of severe malaria cases was significantly lower in the dry season than the rainy season, as shown inAside the uncomplicated clinical cases of malaria, 9.6% had complicated malaria, as indicated by the WHO criteria for severityP. falciparum.The prevalence of malaria parasitaemia during the rainy season was significantly higher than the dry season, with prevalence rates of 49.3% and 20.2%, respectively, all due toThe mean parasite density was much higher during the rainy season (1006.13) than during the dry season (405.45). The details are shown in14 and 201522 shows a progressive reduction; from 48.1% to 37.1% for north-western Nigeria, and a prevalence of 46.6% for Sokoto in 2015 compared with 34.8% for our study. Prevalence in the MIS’s was measured among children aged six to 59 months and is probably higher than for the children included in this study because including the children from 6–10 years is likely to reduce the overall prevalence, as is excluding those aged six months to two years, who generally have a higher prevalence rate23. This suggests that the prevalence and intensity of malaria transmission has declined over time, particularly when it is juxtaposed against the rate of uptake of Long-Lasting Insecticide Treated Nets (LLINS)22.The prevalence of malaria in this study, when compared with serial MIS’s performed in 2010et al.13 in Sokoto; however, samples in the previous study were collected from patients visiting two hospitals within the metropolis and was thus not community-based. Furthermore, all ages from 0 to 65 years were included in the study, which is likely to further dilute the findings and give a falsely low prevalence because the incidence of malaria is generally lower among adolescents and adults, as indicated in the study. Further lending credence to the claim of a reduction in the prevalence of malaria, likely owing to better access to malaria prevention and increasing urbanisation; both of which cause a decline in malaria parasite rates generally24. Although there were studies performed in the past in Sokoto, they are limited in comparison to the present study by virtue of having been conducted in a different age group, or hospital in lieu of community setting and the seasons in which these studies were conducted. The prevalence of 34.8% found here was higher than the 27.9% found by Abdullahiet al.25, conducted in Sokoto between 2007 and 2009. Additionally, it was lower than the prevalence of 49.6% found among children under the age of five years in the same study. Considering both age-specific prevalence rates, there is a reduction in prevalence, although being a hospital-based study, the prevalence for the former study is likely to be higher than the current. It is, however slightly, higher than the projected national average of 29% for 2015, with wide inter-regional differences26. The Nigerian MIS of 2015 found a higher prevalence of 46.6% than this study, although the age of included participants ranged from six to 59 months, which will limit the comparability of results from this study due to the different age ranges of participants22. This decline in the prevalence should reflect in the distribution of the parasites as theorised by Lucas and Gilles27 who propounded a theory of disappearance of species as control measures improve until complete elimination is achieved. The prevalence found in this study is also lower in comparison to the 45.4% prevalence rate found in a study by JiyaThe prevalence by age in this study roughly indicated a progressive decline with age. The highest age-specific prevalence was among two-year-olds (50.4%), with a statistically significant difference among the age groups. This finding is in conformity with the steady-state assumption and is like findings in previous studies that showed higher prevalence among younger age-groups. The prevalence of uncomplicated clinical malaria was highest among three-year-olds and two-year-olds, and lowest among ten-ten-year olds, also in keeping with the steady-state-theory. Considered altogether, the under-fives constituted the largest proportion of uncomplicated and complicated malaria cases, and this is to be expected, considering that they are the least immune to malaria.P. falciparum. This is similar to findings in recent studies in Adamawa28 and Cross River states10 in 2011 and 2013, respectively. Another study from Ihiala, in Anambra state of south-eastern Nigeria, foundP. falciparum mono-parasitaemia even though this study considered all types of malaria, both severe and uncomplicated29. This is, however, unlikely to affect the findings, as most cases of severe malaria in this area are due toP. falciparum29. An earlier report from Sokoto between 2005 and 2006, carried out at Usmanu Danfodiyo University Teaching Hospital by Jiya and Sani30 likewise did not find anyPlasmodium species apart fromP. falciparum, although they only considered cases of severe malaria, which are unlikely to be due to a different species ofPlasmodium within Nigeria. Meanwhile, only three cases out of 582 (0.01%) were positive forP.malariae in another study by Nwaorgu and Orajaka31 in Awka, south-eastern Nigeria. A major limitation of the studies described is the population selected for hospital-based studies, which was mostly children with severe, complicated malaria, for which there is likely to be monoparasitaemia. The community-based studies are expected to truly reflect the distribution of parasite species because in the absence of radical-cure treatment with primaquine as is the case in Nigeria,P. malariae and P. ovale infections are likely to persist in the population. Other studies in the past had not explicitly described the process of identifying other parasite species and that could be a weakness in those studies. However, in our study which was community-based, we poundP. falciparum monoparasitaemia in spite of methodologically searching for otherPlasmodium species. This leads us to believe that this is a trueP. falciparum monoparasitaemia, contrary to expectation. The finding ofP. falciparum mono-parasitaemia supports the likelihood thatP. falciparum is the dominant species ofPlasmodium in Sub-Saharan Africa, showing at tendency to exclude other forms of parasitaemia, as expounded by Lucas and Gilles27 in 1998 with time and sustained malaria control activities.With respect to the parasite species causing uncomplicated malaria, all parasitaemia in this study was found to be due toP. malariae either as mono-infection or coinfection withP. falciparum. In Abia and Plateau states (2010),P. malariae accounted for 32.0% and 1.4% of malaria infections, respectively7 in malariometric surveys In another community-based study in north-central Nigeria, 6.1% of examined participants hadP. malariae infection32 and as high as 41% and 4%, respectively, hadP. malariae andP. ovale infections in a historical study in Garki, Abuja (1968)33. Outside Nigeria, there has also been a documented shift towards mono-parasitaemia withP. falciparum, and this has been documented in the Horn of Africa34 and Benin in West Africa35. Some authors have suggested it be an evidence of failing control measures but this is at variance with data from this study, which shows a reduction in prevalence from previous data, including a reduction in the number of severe cases of malaria, which were very few in this study both in the rainy and dry seasons, reflecting better malaria control than seen in previous studies. Other studies have expectedly shown the presence of other forms of parasitaemia, notably with27 found that a third of all children admitted with malaria had a severe form of malaria.Severe malaria was seen in 26 of the 1017 participants analysed in this study, with an overall prevalence of 2.6%. It was higher during the rainy than the dry season, probably due to higher prevalence of the disease and higher parasitaemia, as earlier discussed. This is lower than expected from other hospital-based studies for which children presenting to the hospital are more likely to be ill than those found in a community-based survey such as this. In one such study in Ilorin by Olanrewaju and Johnson36.Uncomplicated, clinical malaria was seen in 279 of the children in the study (27.4%), which is relatively high, considering that it was community based. The proportion of tested children with malaria parasitaemia who had uncomplicated malaria was also high overall (86.2%) and higher in the rainy than the dry season. The role of Seasonal Malaria Chemoprophylaxis (SMC) would thus be relevant in reducing this percentage of positives with clinical malariaOur study is limited by the point estimation of malaria prevalence, for which a time-series would have been preferred to document consistently the changes over time. Also, the use of RDT kits, could have been complimentary to microscopy for the diagnosis of malaria species if we used a kit with the ability to detect other parasite species.P. falciparum monoparasitaemia. This suggests a disappearance of other parasite species, either due to faltering control ofP. falciparum leading to dominance by these species or more efficient control of other species. However, the trend of overall endemicity suggests the latter explanation, implying a need to intensify measures to controlP. falciparum, considering its strategic role in causing clinically severe malaria in SSA.We found that the area had an intermediate endemicity of malaria transmission. Despite this, there washttps://doi.org/10.6084/m9.figshare.11590542.v120.Figshare: complete data.xlsx.Creative Commons Attribution 4.0 International license (CC-BY 4.0).Data are available under the terms of the Major Comments:The title and results section still seems disconnected and not present what one would expect from the title. The monoparasitameia result is only mentioned in ‘Comparison of prevalence between the seasons’. The result section mostly describes malaria parasitaemia and severity by age and season.The paragraph heading “Parasite species causing malaria” does not include parasite species and the author might want to change the subheading to match the text.Comparing observed prevalence in the study with other studies is inappropriate because of seasonality. The authors should have used the discussion to discuss what monparastemia means for the control and elimination in Sokoto. What interventions are ongoing and how can program planners and policy makers use their findings?Minor Comments:The reported prevalence estimates throughout the results section are based on microscopy or mRDT . Maybe the authors could add a simple sentence in the methodologies that all prevalence are from microscopy if not otherwise stated?Table 4 still shows only severe malaria, although the objective of the study was described with a focus on uncomplicated.Abstract result “Mapping of the parasite was extended throughout the Local Government Area and the State” is not very clear, consider rephrasing “Mapping of the parasite”.In the section “Parasite density across the seasons” the units for the parasite density numbers are missing.Under “Age-specific prevalence rate of malaria parasitaemia” significance value (p=0.000) was changed from previously (p=<0.01), which seemed better practice, why the change?Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?PartlyAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:malaria epidemiology in school children, malaria surveillance, mathematical modelling of malariaWe confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. Most of my previous comments were addressed but some were not.Major concernAbstract The abstract states "...causing uncomplicated malaria....". This study should have enrolled only people with uncomplicated malaria. This sentence must be revised to reflect the total samples used.Minor concerns Results I still do not understand why some malaria indices were stratified by age and also by season and others including RDT positivity rate was not.Discussion "the prevalence" revise to state what prevalence you are referring to.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Recombinant DNA technology and Malaria transmission, Plasmodium species identification, gametocytes and serology as well as host geneticsI 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. Plasmodium species causing diseases in humans." - Rephrase the sentence to read, "In Nigeria, malaria is caused predominantly by one of the five currently……………in humans.""Malaria is caused by one of five currently known "P. falciparum is an undisputed leader in all the studies performed." - Rephrase the sentence to read, "P. falciparum is an undisputed predominant parasite in all the studies performed."8,10." - This sentence is redundant and I suggest for it to be removed."Its high proportion perhaps accounts for high rates of malaria-related anaemia in most studies, explained by the ability of the parasite to invade and destroy both young and senescent red blood cellsI approve the manuscript to be indexed, however, I have some minor comments:Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?NoAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:MalariaI 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. Abstract/Introduction:What is monoparasitaemia? Do you mean mono species parasitaemia?Plasmodium species.The first sentence of the abstract/introduction should be revised as malaria in other animals is caused by otherThe reference WHO 2014 and 2016 are not current, what is the current data?What is meant by ‘parasite mapping’ and why is this important to the reader? P. falciparum.Check the text and remove spaces before full stops as well include a space before the falciparum in‘not so much the parasite’? I do not understand what this means. There is no modeling in this study so the second sentence in the introduction is not relevant, especially as it is very confusing.What is the definition of ‘confirmed cases?’What does ‘crucially’ mean?Methods:Is April the peak of the malaria season? The description of malaria indices in the study site is not sufficient.The blood draw procedure can be rewritten to enhance clarity. Overall, how many drops of blood were collected? And what processes/procedures were performed?Tables:Tables 1, 2, 3, and 5 can easily be merged. It would reduce the repetition.Table 2 can be stratified by age as the other tables.Table 4 should be age stratified and other cases separated into asymptomatic and uncomplicated cases.Figure 2: The title is wrong as it includes ‘no parasites’. No parasites do not cause malaria.There are items in the legend that are not on the graph, it would be best to remove and just state in the foot notes that none of those other species were identified.Results:Was the parasite density at the two time points significantly different?Discussion:It would be very easy to compare the results from the current study with the data in the MIS by comparing similarly aged children. The statement can be revised if the analysis is redone for children aged 5 years and below.I think the last paragraph should be a summary of the major findings and provide information related to the main aim or relevance to the title but it is presently not so.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Recombinant DNA technology and Malaria transmission, Plasmodium species identification, gametocytes and serology as well as host geneticsI 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. Abstract/Introduction:What is monoparasitaemia? Do you mean mono species parasitaemia?Yes, this is clarified in the textPlasmodium species.The first sentence of the abstract/introduction should be revised as malaria in other animals is caused by other It has been rephrased for clarityThe data was collected in 2016 and written up in 2017, the data is referencing the time around which the data was collected to ensure comparability, considering the constantly changing dataThe reference WHO 2014 and 2016 are not current, what is the current data?Parasite mapping refers to the description of geographical spread of the prasite species and how it can be extended to other parts of the state, based on climatic and geographic information.What is meant by ‘parasite mapping’ and why is this important to the reader? P. falciparum.Check the text and remove spaces before full stops as well include a space before the falciparum inChecked and corrected‘not so much the parasite’? I do not understand what this means. There is no modeling in this study so the second sentence in the introduction is not relevant, especially as it is very confusing.Reference to modelling is deleted, the statement has been rephrasedWhat is the definition of ‘confirmed cases?’ confirmed cases is defined as those with a positive malaria parasite test and clinical symptoms.This has been elaboratedWhat does ‘crucially’ mean?Changed to 'notably'Methods:Is April the peak of the malaria season? The description of malaria indices in the study site is not sufficient.Some information has been providedThe blood draw procedure can be rewritten to enhance clarity. Overall, how many drops of blood were collected? And what processes/procedures were performed?It has been re-written to increase clarityTables:Table 3 contains more data including data on the age distributionTables 1, 2, 3, and 5 can easily be merged. It would reduce the repetition.Table 2 can be stratified by age as the other tables.The data is provided in table 3Table 4 should be age stratified and other cases separated into asymptomatic and uncomplicated cases.The data is provided in table 3Figure 2: The title is wrong as it includes ‘no parasites’. No parasites do not cause malaria.There are items in the legend that are not on the graph, it would be best to remove and just state in the foot notes that none of those other species were identified.The figure has been changed entirely in version 2 Results:There was no test of significance performed but it is much higher in the rainy than the dry season.Was the parasite density at the two time points significantly different?Discussion:It would be very easy to compare the results from the current study with the data in the MIS by comparing similarly aged children. The statement can be revised if the analysis is redone for children aged 5 years and below.The prevalence of malaria is described as it relates to the parasite species distribution and the impact of malaria endemicity. The metric for endemicity is the prevalence of falciparum malaria among children 2 to 10 years of age, which is the age group we studied. We also did not collect any data in children 6 months to 2 years and so even if we consider children under 5 years, we still would not be able to compare the data directly with MIS data.I think the last paragraph should be a summary of the major findings and provide information related to the main aim or relevance to the title but it is presently not so.It has been revised Plasmodium parasite species causing uncomplicated malaria in human in the area. The diagnosis of malaria was performed using mRDTs (for the detection of the presence of infection) and thick (for assessing parasite density) and thin (for species identification) smears. The key finding is Plasmodium falciparum monoinfection in the study area. This article presents findings from a cross-sectional study conducted in Wamakko Local Government Authority, in Sokoto State in Nigeria with a broad objective of determining the prevalence of Major Comment The authors have failed to answer the following questions so as to convince readers, and thus should be addressed: What is the aim of this study? Why do you want to understand the prevalence of different malaria parasite species present in that part of Nigeria? How does the understanding of the prevalence of the parasite species contribute to the management, control and prevention of malaria in general? Try to explain this so as to lay down the significance of this study.         AbstractBackgroundThe first sentence…………'Malaria is caused by one of five currently known Plasmodium parasite species’…the sentence is not clear. Where do the authors refer to where malaria is caused by that one of the five species?What information on vector does the modeling provide? The sentence is redundant; I suggest to be omitted. Plasmodium species infecting humans in the study area.The sentence………’This study aimed to determine proportions of Plasmodium parasites’………is not in line with the true aim of the study. It would sound clear if it was stated that the aim was to determine the proportions of Methods‘Selected participants were examined for ………. signs of complicated malaria'. However, there is nowhere in the abstract were it has been stated that this was either a hospital or community based study, and whether only symptomatic or both symptomatic and asymptomatic individuals for malaria infection were included in the study. How were the study participants selected, randomly or conveniently? What was the age limit of the study participants? ‘…………and thick and thin films to identify parasitemia and parasite species’. Which one of the tests was used to identify parasitemia, and which one was used to identify species? Be specific.‘………. with complicated malaria were referred to the nearest hospital’………but you are silent about those individuals with uncomplicated malaria, were they treated?Results‘There was monoparasitemia of Plasmodium falciparum’…………. I suggest to rewrite the sentence and read……………. There was Plasmodium falciparum monoinfection throughout…….On the other hand, detection of parasite species was based on microscopy thin smears, where there any efforts to detect the parasite species using more sensitive methods such as PCR?‘Mapping of the parasite…….’This sentence is not part of the results but rather of the methods, move it to the methods section.ConclusionOmit the sentence……………...’Despite the intermediate endemicity in the area’…………. otherwise, how does the endemicity determine the presence of a certain malaria parasite specie?   IntroductionThe first sentence is confusing, same as in the abstract. See the above comment.The third sentence………...’scientists have modelled the Anopheles………...but not so much on the parasite’. This sentence is misleading, and which characteristics are you referring to? The sentence itself is redundant and I suggest to be omitted.This figure likely overestimated the proportion of cases………...tracked by passive surveillance in Nigeria’. The sentence is not clear, rephrase it to increase clarity.These proportions were the age-group specific parasite prevalence……………...sickle cell trait and those with normal adult hemoglobin. Rephrase this sentence to increase clarity.‘Plasmodium falciparum is an undisputed leader’……………. I don’t think the word leader suits well in this sentence, I suggest the use of the word ‘predominant/prevalent’.There is no aim of the study in the whole introductory section.MethodsStudy settingsHow many rainfall seasons are there in the study area? When does the rainfall season start and end? What are the major economic activities in the area? What are the major vectors? What are the major malaria control tools employed in the area?Study designWhere the participants selected randomly or conveniently?Was this a community-based or health facility-based study?Sample populationRewrite sentences 1 and 2 to increase clarity……...’after identifying the household head. They were provided with information regarding the study’………. To who was the information provided, the household head, or everyone in the household? Who gave the consent?‘Residents of the study area for at least two weeks’…………...with this very short time of being a residency in the study area, how sure are you that the malaria parasite species found in the assessed individuals have not originated out of your study area ?Except for those who had parasitemia without symptoms……...followed up………. for up to 48 hours for the development of symptoms. Is it ethical to not treat an infected individual and only wait for symptoms to occur?ProceduresDoes this mean that the field assistant recruited the study participants prior to obtaining consent from parents/guardians? Is this ethical?‘We examined at least 10 fields before a slide was declared negative’……….what is the standard number of fields that are required to be read before declaring a slide negative?Statistical analysis‘We determined the prevalence of malaria by parasitemia and RDT by determining proportions'. The sentence is not clear, rewrite it.ResultsCombine tables 1 and 3Combine tables 4 and 5Figure 2………..the prevalence of other parasite species is 0%, I suggest you find another method for presenting this, otherwise the figure is not convincing. The following sub-sections can be combined: Prevalence of malaria, age-specific and sex-specific prevalence of malaria, the prevalence of malaria by seasons, and parasite density by seasons. All these can be under one sub-section ‘Malaria prevalence’.You should have at least 3 sub-sections to include: Included participants, Prevalence of malaria, and Plasmodium parasite species.Parasite density across the season‘…………density was much higher during rainy…………., but the p-value is not given and the authors states that details are shown in Table 5, this is not proper.DiscussionPlasmodium species infecting humans in the study area was the main objective. Why then the first paragraph concentrate on the prevalence of malaria rather than of the infecting parasite species?Evaluation of the prevalence of malaria in the study area was not the main objective of the study, but rather the evaluation of the prevalence ofThe second sentence in the first paragraph is not clear, and what are you trying to suggest by ……...’as is excluding those aged 6 months to 2 years? How is malaria prevalence stratified by age, I mean what is the standard?The discussion has concentrated much on malaria prevalence rather than on the main objective of the study, which is the prevalence of Plasmodium species infecting humans in the study area.The conclusion is missing.ReferencesReference 2. World Health Organization…………. Nigeria. Geneva, 2014. Remove the name Nigeria.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?NoAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:MalariaI 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. plasmodium parasites causing uncomplicated malaria. The study included data collection in both, rainy as well as the dry season. The diagnosis of malaria in study participants was done via rapid tests and dried blood spots, which in the study closely aligned with each other (3% difference). The key finding is monoparasitaemia in the study population with all of the malaria infections caused byplasmodium falciparum.The paper presents findings from a cross-sectional study conducted in one LGA (Wamakko) in Sokoto State in Nigeria that aimed to determine the proportions of However, it is not exactly clear why this study was performed. The authors did not make a clear statement of the gap in the literature or how their study complements the literature. The studies that they cited suggests that the monoparasitemia as it relates to malaria in Nigeria is a known fact. Is their goal to confirm this for a different geographical location? A more clearly written aims and study motivation will convince readers of the importance of their studyMajor commentsIf cluster sampling proportionate to size was used, list all the wards and settlement in a table with their population sizes. This can be included in the supplement.How was cluster selection done? Did you stratify by ward and settlement sizes before random sampling? Be explicit about what was done and how it was done.Please elaborate on your methods.link on how to write a discussion section. There are other resources online as well.Please use the discussion section to discuss the implications of your study for treatment and control and the wider scientific community. What are the study limitations? The bulk of this section should not be spent comparing your findings with other studies. We would refer the authors to this unusual’ monoparasitaemia, as the discussion indicates that this could have been expected?  The authors may consider rephrasing the title or to add a stronger argumentation in the introduction and discussion (see major comment 1).In the discussion, studies are cited that report monoparasitaemia, which seems circular/contradictory to the title of ‘The conclusions are missing in the main text, but included in the abstract.either due to faltering control of P. falciparum or more efficient control of other species” (last part of the abstract conclusion) could be discussed more in the discussion as one would expect from the title.The potential reasons for the disappearance “Severe versus clinical malaria. The study aim states a focus on uncomplicated malaria, however, Table 4 only shows severe malaria, which should also show uncomplicated malaria (or instead). The WHO criteria for severe malaria were used, does that include criteria for uncomplicated malaria if not which criteria were used? . How were severe cases treated in the study did they also receive ALu at home or were referred to the next hospital or health facility? Moreover, it would be relevant to show uncomplicated malaria per age in addition to parasitaemia in Table 3.  Minor comments1 and prevalence curves that peak among school children while incidence curves peak in children under the age of five2. The article here found that parasitaemia is highest at age two and then decreases by age. A sentence for clarification on this would be helpful that explain the decrease over age?Previous studies reported the highest parasitaemia among school-aged childrenThe authors found 65% to be non-malaria fevers, this is interesting and the authors may consider highlighting it as a finding and adding it to the discussion .Scientists have modelled the anopheles mosquito vector extensively based on its characteristics, but not so much the parasite” the reference to this study and to niche models of vectors is confusing, as the author’s study is not doing niche modelling or geographic mapping of parasites. It would seem more appropriate to have a description of the geographical occurrence of parasites leading over to the next sentence.“An absence of the Duffy antigen on red blood cells of West Africans has long been postulated to be responsible for the absence of P. vivax in these areas, but cases of P. falciparum, P. malariae and P. ovale, in order of decreasing occurrence, have been found”).Missing reference for the Duffy antigen sentence line 6 to 9 in the first paragraph The authors cite the Nigerian national treatment policies for parasite co-infections, which however is not the main source which remains unclear, is there an actual study that could be cited?five to 10 years” write out numbers below twenty, or use numbers consistently.“Possible gender bias in writing ‘he’ for the pediatrician “He performed a physical examination for each participant and graded splenomegaly according to Hackett’s criteria”.Concomitantly, during the same session…” consider removing duplication? “The study numbers” is not explained before; do the authors mean participant identifiers or study participant numbers?“The tail segment of the thin films was viewed to identify the species of malaria parasite, using the typical description of parasite species, having been trained on parasite identification”, who has been trained?Unclear sentence: “We determined the prevalence of malaria by parasitaemia and RDT by determining proportions.” Maybe the authors could add formula pos mRDT/tested by mRDt; pos BS/ tested by BS to be clearer?Unclear sentence: “3.Consider reducing the black background in figures and tables and not using 3D plots, see some general rules on scientific figures inBe consistent with ‘malaria’ or ‘clinical malaria’ to distinguish malaria infection from clinical malaria, i.e. Fig 2 caption and title, and text description.Confusing Fig 2, as it reads as if ‘no parasite can also cause malaria’? Would a barchart be more appropriate? Or consider rephrasing the figure title.Reference number 36 is missing or not needed (sample procedures line 11), reference list goes only up to 33.The finding of P. falciparum mono-parasitaemia supports the fact that P. falciparum is the dominant species of Plasmodium in Sub- Saharan Africa’ Consider rephrasing like ‘confirms/ support the other findings of mono-parasitaemia’ to avoid the term ‘fact’.‘The discussion structure might need some revision for better understanding, for example, the last paragraph on severe malaria in the discussion might fit better after discussing uncomplicated malaria and before discussing monoparasitaemia in other studies.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?PartlyAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:malaria epidemiology in school children, malaria surveillance, mathematical modelling of malariaWe confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. If cluster sampling proportionate to size was used, list all the wards and settlement in a table with their population sizes. This can be included in the supplement.How was cluster selection done? Did you stratify by ward and settlement sizes before random sampling? Be explicit about what was done and how it was doneThis has been done, there were two strata, selected independently. The first stratum was proportional to size, i.e at the ward level.Please elaborate on your methods.link on how to write a discussion section. There are other resources online as well.Please use the discussion section to discuss the implications of your study for treatment and control and the wider scientific community. What are the study limitations? The bulk of this section should not be spent comparing your findings with other studies. We would refer the authors to this I have added sections and modified the discussion as per your recommendations. Implications to the wider scientific community are included.unusual’ monoparasitaemia, as the discussion indicates that this could have been expected?  The authors may consider rephrasing the title or to add a stronger argumentation in the introduction and discussion (see major comment 1).In the discussion, studies are cited that report monoparasitaemia, which seems circular/contradictory to the title of ‘It has been explained why the results are unusual, given the population studied i.e community-based. this is reflected in the introduction and conclusions as suggestedThe conclusions are missing in the main text, but included in the abstract.They have now been included in the main text.either due to faltering control of P. falciparum or more efficient control of other species” (last part of the abstract conclusion) could be discussed more in the discussion as one would expect from the title.The potential reasons for the disappearance “This has been included in the discussion.Severe versus clinical malaria. The study aim states a focus on uncomplicated malaria, however, Table 4 only shows severe malaria, which should also show uncomplicated malaria (or instead). The WHO criteria for severe malaria were used, does that include criteria for uncomplicated malaria if not which criteria were used? . How were severe cases treated in the study did they also receive ALu at home or were referred to the next hospital or health facility? Moreover, it would be relevant to show uncomplicated malaria per age in addition to parasitaemia in Table 3.Table 3 has been modified to include other parameters such as the age-specific prevalence of uncomplicated and severe, complicated malaria. Figure 2 has also been modified for more clarity  Minor comments1 and prevalence curves that peak among school children while incidence curves peak in children under the age of five 2. The article here found that parasitaemia is highest at age two and then decreases by age. A sentence for clarification on this would be helpful that explain the decrease over age?Previous studies reported the highest parasitaemia among school-aged children This has been explained as the steady-state assumption.The authors found 65% to be non-malaria fevers, this is interesting and the authors may consider highlighting it as a finding and adding it to the discussion .The figure has been changed for clarity. What is reported was that 34.8% of all children had malaria parasitaemia and the nature of parasitaemia i.e symptomatic and asymptomatic has been clarified.Scientists have modelled the anopheles mosquito vector extensively based on its characteristics, but not so much the parasite” the reference to this study and to niche models of vectors is confusing, as the author’s study is not doing niche modelling or geographic mapping of parasites. It would seem more appropriate to have a description of the geographical occurrence of parasites leading over to the next sentence.“The sentence has been rephrased.An absence of the Duffy antigen on red blood cells of West Africans has long been postulated to be responsible for the absence of P. vivax in these areas, but cases of P. falciparum, P. malariae and P. ovale, in order of decreasing occurrence, have been found”).Missing reference for the Duffy antigen sentence line 6 to 9 in the first paragraph Clarified, the household head gives permission and it could be a parent or other person.The authors cite the Nigerian national treatment policies for parasite co-infections, which however is not the main source which remains unclear, is there an actual study that could be cited?The treatment guidelines are the ones cited.five to 10 years” write out numbers below twenty, or use numbers consistently.“I thought this was one to nine, it has been edited.Possible gender bias in writing ‘he’ for the pediatrician “He performed a physical examination for each participant and graded splenomegaly according to Hackett’s criteria”.Clarified, the lead investigator is the corresponding author and is male.Concomitantly, during the same session…” consider removing duplication? “Done.The study numbers” is not explained before; do the authors mean participant identifiers or study participant numbers?“Study number is explained.The tail segment of the thin films was viewed to identify the species of malaria parasite, using the typical description of parasite species, having been trained on parasite identification”, who has been trained?Unclear sentence: “Clarified.We determined the prevalence of malaria by parasitaemia and RDT by determining proportions.” Maybe the authors could add formula pos mRDT/tested by mRDt; pos BS/ tested by BS to be clearer?Unclear sentence: “Formula provided for each instance.3.Consider reducing the black background in figures and tables and not using 3D plots, see some general rules on scientific figures in Figure changed.Be consistent with ‘malaria’ or ‘clinical malaria’ to distinguish malaria infection from clinical malaria, i.e. Fig 2 caption and title, and text description.Figure 2 has been modified.Confusing Fig 2, as it reads as if ‘no parasite can also cause malaria’? Would a barchart be more appropriate? Or consider rephrasing the figure title.Figure 2 changed.Reference number 36 is missing or not needed (sample procedures line 11), reference list goes only up to 33.References updated.The finding of P. falciparum mono-parasitaemia supports the fact that P. falciparum is the dominant species of Plasmodium in Sub- Saharan Africa’ Consider rephrasing like ‘confirms/ support the other findings of mono-parasitaemia’ to avoid the term ‘fact’.‘Fact has been deletedThe discussion structure might need some revision for better understanding, for example, the last paragraph on severe malaria in the discussion might fit better after discussing uncomplicated malaria and before discussing monoparasitaemia in other studiesSome modification has been done


Plasmodium falciparum malaria were analyzed using protein microarrays . A variable selection algorithm was applied to identify the smallest set of AAbs showing the best performance to classify malaria and bacteremia patients. The selection procedure identified 8 AAbs of which IFNGR2 and FBXW5 were selected in repeated model run. The classification error was 22%, which was mainly due to non-Typhi Salmonella (NTS) diagnoses being misclassified as malaria. Likewise, a cluster analysis grouped patients with NTS and malaria together, but separated malaria from non-NTS infections. Both current and recent malaria are a risk factor for NTS, therefore, a better understanding about the function of AAb in disease-specific immune responses is required in order to support their application for diagnostic purposes.A better understanding of disease-specific biomarker profiles during acute infections could guide the development of innovative diagnostic methods to differentiate between malaria and alternative causes of fever. We investigated autoantibody (AAb) profiles in febrile children (≤ 5 years) admitted to a hospital in rural Ghana. Serum samples from 30 children with a bacterial bloodstream infection and 35 children with  However, due to semi-immunity, asymptomatic parasitaemia is common in holo-endemic malaria regions, which impedes accurate diagnoses in the presence of co-infecting pathogens. Thus, a positive malaria rapid diagnostic test result does not rule out other concomitant febrile diseases. Recent studies on causes of fever in Ghana and Tanzania showed that half of the children with parasitaemia revealed other diagnoses apart from malaria3. To address this challenge, the WHO recommends a combination treatment with broad-spectrum antibiotics and antimalarials for all cases of severe malaria in endemic settings, leading to high antimicrobial drug usage4. A diagnostic test, which is able to distinguish between malaria, bacteremia or a co-infection would facilitate empiric treatment decisions without prescribing unnecessary antimicrobial medication.Differentiating malaria from alternative causes of febrile illnesses, in particular invasive bloodstream infections, is complex because of unspecific and overlapping disease symptoms. Reliable rapid diagnostic tests for malaria are available and in use5. It was shown that healthy individuals living in malaria hot-spots possess higher AAb levels than healthy individuals from malaria-free zones within the same country8. While AAbs are used for diagnosing several chronic inflammatory diseases11, little is known about their diagnostic potential in malaria, bacteremia or their use in the differential diagnoses of malaria from other infectious diseases.It has been shown that malarial infections lead to a range of characteristic immune responses, including hypergammaglobulinemia, polyclonal B cell activation and an increase in autoantibody (AAb) productionPlasmodium falciparum or with bacterial bloodstream infections.The aim of the analysis is to identify the smallest set of AAbs capable to classify children with malaria or bacterial bloodstream infection. Using protein microarrays spotted with more than 9000 recombinant human proteins, we screened the serum of children infected with Patients with bacteremia, malaria and controls were age and sex matched with a median age of 2 years IQR 1–3) and 49% (n = 37) females in the study group. The majority of study participants were sampled during the rainy season . The median parasite count in malaria patients was 181,670/µl  and the most frequently identified pathogen in the bacteremia group was NTS   were excluded from the analysis because of elevated negative control values. Furthermore, 291 (3%) proteins were excluded because of batch effects, which left 8615 (92%) for further analyses. The distribution of AAbs ordered by their respective negative control values are shown in the Supplemental Fig. The proportion of AAbs per study participant with signal measurements above the respective AAb-median was assessed for controls, bacteremia patients and malaria patients. These values allow a relative quantification of high measurements in fluorescence intensities across disease groups . The smallest classification error rate of 22% was observed in the 32nd model fitted with 8 AAbs. Selected AAbs are described in Table The proximity analysis highlighted the relatedness among malaria and NTS patients. Three patient-clusters were established from random forest’s proximity data, which are shown in the multidimensional scaling (MDS) map in Fig. Induction levels of the eight AAbs selected by random forest are shown in Fig. Robustness of the random forest selection approach was tested by repeating the selection algorithm 100 times. The median classification-error rate in the 100 selected models was 23% (IQR 22%–23%), compared to 22% in the applied model. The smallest classification-error was most often measured in a model containing eight AAbs , which is in line with the applied model. The smallest marker-set selected contained 3 markers and the largest 62. Figure 13. Multiple studies over the years observed a high incidence of ANA in healthy individuals living in malaria-endemic areas of Africa, but a lack thereof in people from malaria-free areas within the same country15. The occurrence of these ANAs together with high serum levels of anti-malaria antibodies led investigators to believe that this phenomenon might be malaria-induced8. Over the years, technological advances in biomedical research, broader autoantigen panels and high-throughput experiments in array format have now provided evidence for a greater number of AAbs to be associated with malaria21.We established AAb profiles using protein microarrays for children with malaria or bacterial blood stream infections in order to identify disease specific induction patterns. These patterns were then tested for their ability to predict disease status, in order to identify AAb candidates capable to detect the underlying pathogen responsible for the acute infection. In general, most individuals have low autoantibody titers, while high levels are associated with certain autoimmune diseases. Antinuclear antibodies (ANAs) for example are antibodies that recognize and bind to structures of the nucleus, like e.g. double-stranded DNA22. Previous studies have demonstrated an increased risk for malaria patients to have a concomitant or subsequent invasive NTS infection24. Inclusion criteria did not cover a history of fever dating back further than 48 h prior to enrolment in the study. Therefore, it is possible that the NTS group, or a fraction thereof, rather represents AAb profiles of a recent malaria episode instead of a current NTS infection.The present analysis demonstrates an increased number of recognized self-antigens by AAbs, a higher signal intensity and response variability in patients with malaria compared to those with bacterial bloodstream infections. Especially children diagnosed with non-NTS isolates could be well separated from malaria patients. Our results allude to a resemblance between AAb induction profiles between malaria and NTS patients. Malaria and invasive NTS infections have a similar age distribution and their prevalence overlap geographically26. Recently, tumor-associated AAbs have expanded the field of cancer immunodiagnostics. In that context, it was noted that AAbs could be viewed as imprints of the ongoing immune response in the body. Even though only a few AAbs have been shown to be disease associated, different profiles have been linked with different diseases and could be useful as diagnostic markers apart from autoimmune diseases28.While it is accepted that infections may trigger AAb production, functional consequences and molecular mechanisms leading to autoimmunity remain unclear. Molecular mimicry, epitope spreading, bystander activation, polyclonal B cell activation are a few hypothesized mechanisms that could be involved30, it has also been shown to have an aggravating effect for the course of infection in mice32. Transcriptional profiling of tissue cultures showed that the absence of IFN-γ receptor signaling led to an increase in parasite load in Toxoplasma gondii infection33 but contributed to experimental cerebral malaria pathogenesis in mice34.IFN-γ is a cytokine of the innate and adaptive immune system and has important functions in a number of immune-related processes. While IFN-γ plays a central role in controlling blood and liver stage malaria in humans and mice36. Autoantibodies against cytokines were found in the course of MSMD research, where anti-IFN-γ autoantibodies seemed to mimic inborn errors and interfere with IFN-γ signaling and correlate with disseminated opportunistic infections, including Salmonella37.Mendelian susceptibility to mycobacterial disease (MSMD) is a rare inherited condition where mutations in autosomal genes in pathways involving interferon-γ  cause a primary immunodeficiency and predisposes individuals to a wide range of infections, including NTS38. It contributes to the substrate specificity of the SCF complex and is also essential for its regulating during the cell cycle39. Despite its basic molecular function, nothing much is known with respect to its role in infection. It will be crucial to validate our findings and further elucidate the (diagnostic) role of FBXW5 in malaria or infections in general.The other selected candidate was FBXW5, a member of the family of F-box proteins that make up one of the four subunits of the ubiquitin protein ligase complex , which in turn plays a role in protein degradation40. In addition, antibody decay is lower than parasite clearance rates. Chronic exposure in malaria-endemic regions leads to a constant background seroprevalence, which limits serological tests in their sensitivity and specificity for diagnostics in acute infections42. Further, the lack to distinguish patients with NTS from patients with malaria is a serious limitation with negative consequences for differential diagnostics in malaria endemic settings.The large number of AAbs, in combination with the limited number of patient samples, is likely to produce chance findings. Thus, the current analysis is of exploratory nature and does not allow to determine the predictive power of particular AAbs under study or to select combinations of markers to be applied in a clinical setting. The eight candidates identified in this analysis need to be confirmed with well-characterized patient samples from an independent study in order to determine their diagnostic potential. A general limitation of serological testing in acute infections is the fact that disease-specific antibodies need several days after the onset of fever before being detectable in peripheral bloodThe current study showed different AAb induction profiles in children diagnosed with malaria or bacteremia, whereby bacteremia cases infected with bacterial species other than NTS showed a distinct AAb pattern compared to malaria patients. In order to improve differentiation between malaria and NTS, better defined patient groups, e.g. with data about recent malaria infections, would be necessary. Taken together, this study identified candidates, which should be subject to further investigation. A validation of our prediction models is a promising next step in the development towards a new pathogen specific rapid diagnostic test.The study was performed in accordance with the relevant Ghanaian and German guidelines and regulations, and with the Declaration of Helsinki. Ethical approval for the study had been obtained from the Committee on Human Research, Publications, and Ethics, School of Medical Science, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana (Reference number: CHRPE/101/09) and the Institutional Review Board (IRB) of the International Vaccine Institute. Written inform consent was obtained from the participants. All parents or legal guardian were informed about the study’s purpose and procedures, and provided written informed consent prior to enrollment.43. Serum samples from 65 children (≤ 5 years of age) admitted to the children’s ward of the Agogo Presbyterian Hospital (APH) in Ghana with fever (≥ 38 °C) were used for this study. Thirty-five children had P. falciparum parasitaemia and a negative blood culture, while 30 children had bacteremia with a negative malaria slide. As control group, asymptomatic children without fever and no signs of infection were selected and sampled in the frame of another fever study2 at vaccination clinics in the surroundings of the APH. Data from control children were displayed as reference values, however not used in the classification analysis, because the low sample size does not allow to predict a third outcome group. Children in all groups were matched by age and sex.Recruitment took place between February 2010 and May 2012 in the framework of a pediatric fever studyP. falciparum.APH is a district hospital with 250 beds, situated in the Asante Akim North Municipality in Ghana. The region has a tropical climate and is highly endemic with 43. Bacterial identification was achieved biochemically with API tests  and Salmonella isolates were serotyped following the White-Kauffmann-Le Minor scheme. For data analysis bacteremia patients were classified as non-typhoid Salmonella  and non-NTS . Two independent slide readers conducted malaria microscopy on Giemsa stained thick and thin smears. In case of discrepancies in parasite counts, a third decisive reading by an additional reader was performed.Blood cultures were performed with pediatric blood culture bottles (Becton Dickinson (BD) BACTEC Peds Plus/F) using an automated BACTEC 9050 Blood Culture System  as described elsewhere44. Purified proteins were spotted on nitrocellulose-coated glass slides. These were blocked, washed and probed with a 1:500 dilution of selected human serum samples. A negative control assay incubated with buffer instead of serum served as a negative control to exclude non-specific interactions from the analysis. Alexa Fluor 647-conjugated goat anti-human IgG antibodies were used for detection and array signals were read using a Tecan PowerScanner fluorescent microarray scanner. The resulting signals were equated with AAb profiles. Relative Fluorescence Units (RFU) for each spot on the array was determined using GenePix 7 software  and signals were analyzed as described below.In order to investigate the autoantibody profile of the serum samples, protein microarrays were performed . Herein, 9345 human proteins were expressed as GST-tagged proteins in insect cells and purified under native conditions to maintain their native conformations and posttranslational modificationsth-percentile of the overall negative control distribution were deemed unspecific and excluded. Markers were analyzed in two batches. Antigens that were not recognized by any serum samples in either of these batches were removed from the dataset. No further batch effects, like varying induction intensity levels among batches, were detected.Pre-processing steps were applied to prepare data for analysis. Background correction was conducted using the normal-exponential convolution method. Negative control values, which capture the fluorescence intensity of a marker without serum, were evaluated. Markers with negative control values above the 9545. Random forest shows very good classification performance in high dimensional data, i.e. when the number of variables exceeds the number of observations, and when most predictor variables are noise46.Random forest was applied to identify the smallest set of AAbs showing the best performance to classify malaria or bacteremia patients in our dataset. Random forest is an ensemble learning method based on multiple classification and regression trees. Classification trees were used in our analysis, since we categorized observations according to their respective diagnoses. Each tree within a forest is built using a random subset of observations, and a random subset of variables are applied to group observations at each split. Using this approach, low-biased and low correlated individual trees are established, over which the final result is averaged. Classification error is estimated internally each time a tree is constructed by predicting the so called out-of-bag (OOB) observations, which were not considered while constructing a tree. This prevents overfitting since internally training and test datasets are utilized. Random forest calculates a variable importance measure for each variable, which is the increase in classification error if values of a variable would be permuted randomly.47. In a first step we fitted a full random forest considering all AAbs and we kept the variable importance data. Iteratively, the 20% of AAbs with the smallest variable importance were removed and the remaining variables were used to re-run random forest. Variable importance was not recalculated for predictor selection since this would cause overfitting. Finally, we selected the AAb set with the smallest OOB-classification error from the model47.To select a set of AAbs with best classification performance we followed the selection approach as described by Díaz-Uriarte et alThe final model, fitted with the selected set of AAbs, was evaluated to identify clustering among study participants. In random forest, the proximity of each observation-pair is computed based on the frequency cases occupy the same terminal node within trees, assuming that similar observations are likely to share a terminal node. The dimensions of the proximity matrix were reduced to two coordinates by multidimensional scaling (MDS) to visualize similarities between observations with a scatter plot. In order to partition patients into clusters, we applied the k- medoids algorithm on the proximity matrix.Random Forests were constructed with the following parameter setting: default number of variables considered per split , each forest contained 20,000 trees and the reciprocal frequency of malaria and bacteremia patients was used to weight classes  to account for imbalanced outcome groups. Each tree was unpruned and could grow fully to the largest extend possible. Random predictor and observation allocation in random forest influence model results and consequently the set of markers selected by the algorithm. Thus, the robustness of the selection procedure was evaluated by repeating the marker selection algorithm 100-times.R (version 3.6.1) using the packages PAA (version 1.10) for AAb pre-procession, randomForest (version 4.6–14) to fit random forest models and cluster (2.10) to partitioning patient clusters.All analyses were performed with Supplementary Information.