Plasmodium falciparum and Plasmodium vivax infection. However, little is known about loss of CRPs on RBCs during mild malarial anaemia and in low-density infection.Anaemia is a major consequence of malaria, caused by the removal of both infected and uninfected red blood cells (RBCs) from the circulation. Complement activation and reduced expression of complement regulatory proteins (CRPs) on RBCs are an important pathogenic mechanism in severe malarial anaemia in both P. falciparum and P. vivax-infected patients from a low transmission setting in Sabah, Malaysia; and, (2) malaria-naïve volunteers undergoing P. falciparum induced blood-stage malaria (IBSM). For clinical infections, individuals were categorized into anaemia severity categories based on haemoglobin levels. For IBSM, associations between CRPs and haemoglobin level were investigated.The expression of CRP CR1, CD55, CD59, and the phagocytic regulator CD47, on uninfected normocytes and reticulocytes were assessed in individuals from two study populations: (1) P. falciparum and P. vivax mild malarial anaemia compared to healthy controls. CRP expression was also reduced on RBCs from volunteers during IBSM. Reduction occurred on normocytes and reticulocytes. However, there was no significant association between reduced CRPs and haemoglobin during IBSM.CRP expression on RBC was lower in Malaysian individuals with Plasmodium infection even in mild malarial anaemia and at low levels of parasitaemia.Removal of CRPs occurs on both RBCs and reticulocytes during  Plasmodium species is often complicated by anaemia, which is a major contributor to morbidity and mortality in malaria endemic regions [Human infection with  regions , 2. Youn regions –5. The p regions  with red regions , 8. Diff regions , 10. Des regions –13.Plasmodium infection through the binding of antigen–antibody complexes to RBC CRPs [Activation of the complement system can occur under the classical, alternative, and lectin cascade pathway, all of which are regulated by CRPs. Membrane-bound CRPs are expressed on the surface of cells, including RBC, and serve to protect from complement attack . Three dRBC CRPs , 15, 16.RBC CRPs . MacrophRBC CRPs . A recenRBC CRPs .Plasmodium falciparum infection [Plasmodium vivax infection [P. falciparum and P. vivax-infected patients from low transmission settings of Sabah, Malaysia and malaria naive volunteers undergoing P. falciparum induced blood-stage malaria (IBSM).Significant reductions of CR1 and CD55 have largely been reported in patients with severe anaemia from nfection , 13, 20,nfection . One stuWritten informed consent was obtained from all study participants, with consent obtained from parents or guardians in the case of children enrolled in the Malaysian studies. For clinical cohorts, sample collection was approved by the Ethics Committee of Menzies School of Health Research, Darwin, Australia and from Medical Research and Ethics Committee, Ministry of Health Malaysia. The IBSM trial was approved by QIMR Berghofer Ethics Committee, Brisbane, Australia.Plasmodium infection by PCR.Patients with malaria were enrolled from an observational study conducted in Sabah, Malaysia, described previously . BrieflyP. falciparum = 10, P. vivax = 10, healthy control = 4). Samples were selected based on availability. Selected samples were grouped into anaemia categories based on World Health Organization (WHO) recommendation [Glycerol-preserved RBC samples were obtained from 24 individuals  was collected at day 0 prior to infection , and immediately prior to treatment (day 8), and 10, 12, 13, 15, 17/18, and 45 days after inoculation from two cohorts in one infection study. Haemoglobin was measured at days 0, 8, 11, 22, 29, 36, 42, and 45.The administration of blood-stage parasites to healthy volunteers, including inoculum preparation, volunteer recruitment, viable parasite quantification, monitoring and treatment were performed as previously described . BrieflyFrozen glycerol-preserved RBCs from patients were thawed using 3.5% NaCl in distilled water and PBS. To account for variation between thawing and staining batches, median fluorescent intensity (MFI) were standardized using RBCs collected from malaria naïve, Australian individuals (n = 3), cryopreserved in multiple aliquots for use across study. Antibody staining of CRPs was done in individual panels with the addition of SYBR-Green for parasite staining and CD71 to distinguish normocytes and immature reticulocytes  and GraphPad Prism (version 7.03). Differences in CRPs and CD47 expression were compared using Wilcoxon signed-rank test. For comparisons between anaemia group, Mann–Whitney nonparametric test was used. Spearman’s nonparametric method was used to determine correlations between CRPs and haemoglobin level.P. falciparum and P. vivax-infected patients living in Sabah, Malaysia. Demographic and clinical characteristics of the study participants from Sabah, Malaysia are summarized in Table P. falciparum infection, 10 with P. vivax infection, and 4 uninfected healthy controls.To establish whether changes in CRP expression on RBC and reticulocyte was a feature of mild anaemia during malaria in low transmission settings, RBC samples were examined from P. falciparum-infected individuals, CR1 (p = 0.043) and CD55 (p = 0.021) expression on uninfected normocytes was lower in mildly-anaemic patients compared to healthy controls  and CD59 (p = 0.053) on reticulocytes compared to non-anaemic malaria patients, respectively . Percentage loss of CR1 was significantly greater in reticulocytes than in uninfected normocytes at all time-points except for day 8 and 12 Fig. c. For CDP. falciparum infection, haemoglobin was reduced at all follow-up time-points compared to baseline (day 0), except for day 11 and 42  patients from a low malaria transmission region with uncomplicated falciparum and vivax malaria and mild anaemia; and, (2) volunteers undergoing  anaemia , 19, the anaemia , 25, sugP. falciparum and P. vivax infection, suggesting that the removal of CRPs is occurring during early stages of anaemia. While well-documented in severe malarial anaemia [P. falciparum-infected RBCs demonstrated that parasitized RBCs were more resistant to complement-mediated lysis due to CD59 expression [In Malaysian malaria patients, CRPs on normocytes and reticulocytes were reduced in patients with mildly anaemic  anaemia , signifipression , suggestP. falciparum infection. However, the magnitude of the loss of CR1 was greater on reticulocytes, suggesting that reticulocytes are more susceptible to complement-mediated attack compared to normocytes. Higher expression of CRPs on reticulocytes compared to normocytes has been described [Expression of CR1, CD55 and CD59 on normocytes and reticulocytes were reduced in volunteers after escribed , 27–29, escribed , 31. Theescribed , 16, 32.P. falciparum infection prior to the onset of anaemia. This is consistent with a previous observation that shows complement activation is increased in volunteers with P. falciparum sporozoite induced infection [The current study investigates longitudinal loss of CRPs for the first time and demonstrated that reduction of CRPs occurs even during low density nfection . Past clnfection , 19, 20.nfection , 9, 34. nfection , 36 and nfection , 38. VolPlasmodium infection takes place early during infection and are consistent with CRP loss on RBCs as an important driver of the development of malarial anaemia.This study shows that the expression of CRPs on normocytes and reticulocytes is reduced in mild anaemia in patients with falciparum and vivax malaria. Further, reduction of CRPs occurs early in infection, during low density parasitaemia and prior to the onset of anaemia. Taken together, the results demonstrate that removal of CRPs from RBCs during


The overlap of malaria and chronic hepatitis B (CHB) is common in endemic regions, however, it is not known if this co-infection could adversely influence clinical and immunological responses. This study investigated these interactions in pregnant women reporting to antenatal clinics in Ghana.Plasmodium falciparum , mono-infected with chronic hepatitis B virus (CHB group) and co-infected .Clinical parameters  and cytokine profiles were assayed and compared across four categories of pregnant women: un-infected, mono-infected with Malaria+CHB maintained appreciably normal hemoglobin levels (mean±SEM = 10.3±0.3 g/dL). That notwithstanding, Liver function test showed significantly elevated levels of alanine aminotransferase, aspartate aminotransferase and total bilirubin [P<0.001 for all comparisons]. Similarly, the Malaria+CHB group had significantly elevated pro-inflammatory cytokines, including tumour necrosis factor alpha (TNF-α), interleukin (IL)-1β, and IL-6 [P<0.05 for all comparisons]. In women with Malaria+CHB, correlation analysis showed significant negative association of the pro-inflammatory cytokines responses with malaria parasitemia . On the other hand, the pro-inflammatory cytokine levels positively correlated with HBV viremia . Also, for women in the Malaria+CHB group, parasitemia was observed to diminish HBV viremia .Women with Malaria+CHB could exacerbate inflammatory cytokine responses and increase susceptibility to liver injury among pregnant women in endemic settings.Put together the findings suggests that  P. falciparum infections is common, and an increased prevalence, from 0.7% to 1.7%, of this co-infection has been reported among pregnant women in Ghana . That notwithstanding, parasitemia was similar between the Malaria+CHB and CHB groups , IL-1β , IL-6 , IFN-γ , IL-2  and IL-12 ], and viremia was significantly lower in the Malaria+CHB compared to the CHB group .In women with ≥ 11g/dL are considered to have normal level [P. falciparum causes anemia by reducing red cell counts, HBV on the other hand is postulated to increase Hb levels by increasing the release of erythropoietin from regenerating hepatic tissues [Malaria+CHB maintained intermediate levels of hemoglobin . This observation may suggest that in women with Malaria+CHB, activities of the plasmodium parasites in reducing red cell count may be compensated for by the activities of the virus, thus maintaining an appreciable hemoglobin concentration. The significant association of CHB with Hb ≥11g/dL further justifies the possible impact of HBV in increasing hemoglobin levels among the pregnant women. However, this might not necessarily translate into improved pregnancy outcomes, since cases of gestational diabetes, antepartum hemorrhage and preterm delivery are observed to be more frequent in pregnant women with CHB [Maternal anemia is an issue of important public health relevance. During pregnancy, women with Hb <11g/dL are diagnosed as anemic while those with Hb al level . P. falc tissues –17. It iwith CHB –32.Malaria or CHB groups have been previously reported [Malaria group is a common finding amongst African multigravidae mothers with P. falciparum infection [Relative to the un-infected Figs  and 3, treported , 8–14. Infection –35, and nfection .Malaria and CHB may lend credence that the elevated levels in those with Malaria+CHB resulted from additive activities of both pathogens. The synergistic elevation in levels of the liver biomarker in the Malaria+CHB group may be attributed to immune factors that limit the infections at the liver-stage. Particularly, natural killer (NK) and natural killer T (NKT) cells which are abundantly available in the liver, interact with pathogens and initiate liver-stage cell-mediated immunity [Malaria+CHB, cytokines released in response to P. falciparum could further activate the apoptosis of HBV-infected hepatocytes, and exacerbate liver damage.Similarity in levels of the liver biomarkers between women with immunity , 38. Forimmunity . TherefoMalaria and CHB, the pro-inflammatory cytokines were significantly increased in those with Malaria+CHB, which further suggests a possible additive effect of the infections. The correlation analysis with the Malaria+CHB group suggests that increased pro-inflammatory cytokine levels as a necessary immune response against malaria helped in reducing HBV intensity. This corroborates with studies indicating that P. falciparum malaria modulates viremia in chronic hepatitis B virus infection [Malaria+CHB may suggest susceptibility to cytokine imbalance (towards Th1). In particular, placental cytokine imbalance is noted to be associated with threatened abortion, recurrent spontaneous miscarriage, and preterm delivery [While peripheral levels of TNF-α, IL-1β and IL-6 were similar in women with nfection , 41. IL-delivery , 42. Thadelivery , 44.P. falciparum would have been paramount in substantiating the compensatory effect of the viral infection. Again such an approach would have enabled us to see the kinetics of Malaria+CHB co-infection and to identify times when the markers of liver injury and inflammatory responses are enhanced. In addition, such an approach would have enabled us to substantiate our findings by profiling placental cytokines responses, malaria parasitemia and HBV viremia, and associating the results with pregnancy complications. Also profiling of innate immune cells and T-cell populations would have given a better insight of the effect of the co-infection on the immune response. Nonetheless, the current study provides evidence on the need to take into cognizance the possible deleterious impact of Malaria+CHB on pregnant women. In this regard, liver functions test which is important in guiding diagnosis and treatment of liver diseases in pregnancy must be readily accessible to pregnant women on ANC clinics.A longitudinal approach on changes of Hb levels in the co-infected cohorts after clearance of Malaria+CHB could exacerbate inflammatory cytokine responses and increase susceptibility to liver injury among pregnant women in endemic settings.Put together the findings suggests that S1 Table(DOCX)Click here for additional data file.


Plasmodium falciparum and Plasmodium vivax was determined by quantitative PCR (qPCR) and showed a seasonal variation with values fluctuating from 1.7% to 4.2% for P. vivax and 0% to 1.3% for P. falciparum. Ninety percent of infections were asymptomatic. The annual molecular force of blood-stage infection (molFOB) was estimated by microsatellite genotyping to be 0.24 new infections per person-year for P. vivax and 0.02 new infections per person-year for P. falciparum. The distribution of infections was heterogenous, that is, the vast majority of infections (>80%) were found in a small number of individuals (<8% of the study population) who tested positive at multiple timepoints. Significant risk factors were detected for P. vivax infections, including previous clinical malaria, occupation in agriculture and travel to Myanmar. In contrast, indoor residual spraying was associated with a protection from infection. These findings provide a recent landscape of malaria epidemiology and emphasize the importance of novel strategies to target asymptomatic and imported infections.Over the past decades, the malaria burden in Thailand has substantially declined. Most infections now originate from the national border regions. In these areas, the prevalence of asymptomatic infections is still substantial and poses a challenge for the national malaria elimination program. To determine epidemiological parameters as well as risk factors for malaria infection in western Thailand, we carried out a cohort study in Kanchanaburi and Ratchaburi provinces on the Thailand-Myanmar border. Blood samples from 999 local participants were examined for malaria infection every 4 weeks between May 2013 and Jun 2014. Prevalence of  The malaria incidence and mortality rates of Southeast Asia declined by approximately 50% between 2000 and 2015 . In the Plasmodium spp. infections. Historically, Plasmodium falciparum was the predominant parasite species in Thailand, but Plasmodium vivax has recently taken over as the primary parasite whereas Plasmodium malariae, Plasmodium ovale and Plasmodium knowlesi are only found sporadically    were use22.1Plasmodium vivax and 1.4% P. falciparum prevalence in August-September of 2012. The study village in Suan Phueng subdistrict is located approximately 160 km from Bangkok. The village is located in a mountainous area on the Tanaosri mountain range. Our survey in September-October of 2012 indicated a prevalence of 3.1% for P. vivax and 1.2% for P. falciparum at this site  were tested for malaria infection on-site using a rapid diagnostic test  and referred to a nearby malaria clinic for treatment if the test was positive. The study was approved by the Ethics Committee of the Faculty of Tropical Medicine, Mahidol University, Thailand .2.3Plasmodium 18S rRNA genes .Finger prick whole blood (200 μl) was collected from each participant into an EDTA-containing microtainer. After plasma removal, blood pellets were stored at −20 °C until DNA extraction. DNA was extracted using FavorPrep 96-well Genomic DNA Extraction Kits , following the standard protocol provided by the manufacturer. The final purified DNA was eluted into 100 μl of elution buffer. A volume of 4 μl of purified DNA  was used as the template for malaria parasite detection by a genus-specific qPCR assay targeting the NA genes . For samc assays  were useescribed . The com2.4molFOB) was determined as described previously . An observed infection, as identified by a specific genotype, was considered to be ‘new’ if the same genotype had not been seen in the two previous active or passive case detection visits. As such, the molFOB can be determined for each study participant or as a sum over the entire study population or subpopulations.The molecular force of blood infection (eviously . Briefly2.5molFOB); ii) being parasite-positive for P. vivax and/or P. falciparum and iii) being subject to a clinical episode, defined by fever + parasitemia detectable by light microscopy , and is overdispersed, a negative binomial regression model was chosen in which the exposure time at risk is used as tge offset (µ*j = exp(βxj + offsetj + νj), where offsetj = log(exposure time) and eνj follows a gamma distribution. Because using the collapsed data to model the molFOB for each individual does not allow for the analysis of time-changing covariates, factors influencing the frequency of parasite positivity and frequency of clinical episodes within the study period were explored using multiple failure time models allowing for time-changing covariates (Factors influencing i) the overall rate of acquisition of new blood infections .To test whether infections were spatially correlated, the 33.1In total, 999 participants were enrolled into this study in May 2013. Eight hundred and twelve participants were from Bong Ti, Kanchanaburi and 187 participants were from Suan Phueng, Ratchaburi. n = 799, 80%) were seen 13 or more times (interquartile range (IQR): 13–14; range: 1–14) during the study period resulting in 12,559 blood samples from active case detection (ACD). In addition, 281 blood samples were obtained through passive case detection (PCD) when participants presented at local malaria clinics due to illness. The median time that the participants remained in the study was 368 days . An overview of the characteristics of the study population is given in Of the 999 participants, the large majority  analysis. Plasmodium vivax monoinfections constituted 84.6% (n = 433/512), P. falciparum monoinfections 9.2% (n = 47/512) and mixed species infections 6.3% (n = 32/512). As such, mixed species infections were over-represented by a factor of approximately 10  indicating a strong clustering of infection. A proportion of 8.5% (37/433) of P. vivax infections and 21.3% (10/47) of the P. falciparum infections were classified as clinical, i.e., detectable parasitemia was accompanied by a measured or reported fever in either PCD or ACD visits. The difference is statistically significant  and suggests that P. falciparum was more likely to cause clinical symptoms. Notably, none of the 32 mixed infections was classified as a clinical episode.From samples collected at both ACD and PCD visits, the genus-specific PCR assay detected 735 infections in the study participants, of which 512 (70.0%) were successfully genotyped for the P. falciparum and P. vivax showed seasonal variation with prevalence varying from 4.2% to 1.7% for P. vivax and from 1.3% to 0% for P. falciparum  3.3molFOB  is statistically significant for P. vivax (goodness of fit test for Poisson distribution P < 10−6), suggesting either a non-uniform risk of acquiring new infection through mosquito bites or relapses of parasites from the liver. Spatial analysis suggests that the P. vivaxmolFOB in Bong Ti, Kanchanaburi was clustered at both the individual level  and, more loosely, at the household level . The low number of infections precluded an in-depth analysis of heterogeneities in the risk of P. falciparum infection.A number of study participants experienced a disproportionately high molFOB . The exc3.4molFOB for P. vivax revealed a higher number of new blood-stage clones in adolescents and adults compared with children  as a significant factor associated with reduced risk of infection.In order to assess time changing covariates, risk factors associated with me model . In geneP. vivax infection including season, age, occupation, and reported previous clinical malaria, were also significantly associated with clinical episodes of malaria  corresponded to a clinical episode, possibly reflecting parasite-parasite interaction or co-development of host protective immunity against these sympatric species.Several predictors of  malaria . Notably malaria , Table 3 malaria . This in3.5P. falciparum, risk factors for increased molFOB were not determined due to the small number of observations . Predictors of infection were determined only from positivity data. In the univariate analysis, only travel frequency to Myanmar was found to be a predictor of parasite positivity  were used to genotype P. vivax. Because the combined He of the two loci was 0.89, approximately 10% of all new clones are expected to have been missed. This, together with the limited sensitivity of molecular genotyping , would lead to an underestimation of the true molFOB. These limitations are shared by our previous studies using the same methodology  and P. vivax (1.7–4.2%) were similar to the 4.9–5.7% Plasmodium prevalence previously reported in Kanchanaburi and Ratchaburi in 2012  than asymptomatic infections (Pv: 91.5%). The predominance was most striking in the number of genetically distinct blood-stage infections acquired during follow-up (molFOB) with only 7.4% of all newly acquired infections due to P. falciparum, resulting in an average molFOB of 0.02 and 0.24 new infections per person-year for P. falciparum and P. vivax, respectively. The proportion of P. vivax infection relative to P. falciparum was much higher in our cohort than among clinical cases recorded by the Thai health system , the high risk in children 7–17 years of age and the association of IRS with protection indicate ongoing local P. vivax transmission, including in or near people’s houses. While the high risk in male adults and those regularly crossing the Myanmar border has been well established  = 2.9) adults (aHR = 10.0) with an excess risk also during the rainy seasons and in areas where IRS had been conducted. The higher risk in people who traveled frequently across the border is a common feature of the residual burden both in this  estimated for blood-stage infection in Thailand (Compared with parasite positivity, the e molFOB  for bothThailand .P. falciparum and P. vivax to Thailand’s declared goal of eliminating local malaria transmission by 2025. In line with our earlier studies in Tak Province (P. vivax transmission in Thai villages along the western border. Most of the P. vivax infections were asymptomatic and often of very low density and would not have been detected by the standard surveillance methods based on microscopy and centered around passive case detection. Efficient elimination of P. vivax from Thailand will thus require additional novel strategies targeting this asymptomatic reservoir, including the silent hypnozoite reservoir (P. falciparum infections were rare. With a large proportion of infection linked to recent travel to Myanmar, it will be important to strengthen malaria control measures on both sides of the border and to raise awareness of the travel-associated risk.In summary, our study highlights the different challenges posed by Province , we haveeservoir . On the


Plasmodium vivax in the invasion of red blood cells. The host–parasite relationship has revealed new perspectives regarding the association between Duffy polymorphisms that can impact both the parasite density of this Plasmodium and the symptoms of this type of malaria. This study investigates the impact of Duffy polymorphisms on parasite density in patients infected with P. vivax in the Brazilian Amazon region.The Duffy glycoprotein acts as the entry point for merozoites of P. vivax. The diagnosis of malaria was performed using a specialized team with a standardized clinical-laboratory method, while the Duffy genotyping was performed through the Bead Chip BioArray system. Both teams are reference services in Brazil.Genotypes and Duffy polymorphism allele frequencies were compared in 287 patients with malaria, presenting low, medium and high density of FY*01 and FY*02 alleles were found in all three parasite density classes: low, medium and high, but when these alleles form genotypes with FY*02N.01 and FY*02W.01 alleles, they are found only in patients with low parasite density and low symptomatology. Another interesting finding found in this study is the presence of the genotype FY*02N.01/FY*02W.01 in one of the patients, presenting a very low parasite density and malaria considered subclinical, a genotype which had not been previously described in the literature.The FY*02N.01 and FY*02W.01 alleles may have an impact on the reduction of clinical manifestations in malaria, leading to the development of subclinical malaria, making the infected individual an undetected natural reservoir, which may hinder the eradication of malaria in the Amazon.The presence of  Plasmodium vivax predominated, with 82% of recorded cases. In recent years, a pattern of abnormal clinical complications associated with fatal infections caused by P. vivax, has been reported from Brazil [Malaria is a major parasitic disease, affecting around 91 countries worldwide. In the year 2017, the World Health Organization (WHO) estimated 219 million cases of malaria worldwide, with about 435,000 deaths. In Brazil, 178,613 cases of malaria were registered, and the state with the highest number was the Amazonas with 77,344 cases. Among these, the infections caused by Plasmodium vivax is the species with the broadest geographic distribution and greatest prevalence in the world, except in the African continent, causing a debilitating illness affecting the quality of life and economic productivity of infected individuals. Malaria caused by P. vivax has been reported as benign and is rarely fatal, however, recent studies in Papua New Guinea, Indonesia, and Brazil, revealed, the existence of severe cases of malaria related to this Plasmodium. Infection can be followed by complications, such as, cerebral malaria, acute respiratory syndrome, liver dysfunction, severe thrombocytopenia and low weight in newborns derived from placental infection, symptoms that are more frequently observed in infections caused by Plasmodium falciparum [lciparum , 4.P. vivax. Studies in populations where malaria is common have demonstrated that erythrocytes that do not have Duffy antigens are relatively resistant to invasion by this Plasmodium. The antigens of the Duffy blood group system  are encoded by two co-dominant allelic forms designated FYA (FY*01) and FYB (FY*02) from DARC (Duffy Antigen Receptor for Chemokines) gene which differ by a SNP (single Nucleotide Polymorphism) at position 125 of exon [The Duffy blood group system is associated with invasion of reticulocytes by a and Fyb antigens. The SNP at position-67 T>C in the GATA promoter region of the DARC gene, most frequently found, is characterized by the FY*02N.01 allele (FYBErythroid Silent−ES), Fyb expression silencer in erythroid cells, determines the Fy (a− b−) phenotype, when in homozygous FY*02N, 01/FY*02N.01. Other less frequent nucleotide changes leading to the Duffy null phenotype have been described as shown in Table P. vivax susceptibility [This difference is characterized by the exchange of guanine (G) by an adenine (A) G125A), determining the expression of Fy25A, deteFY*02W, 01 (FYBWeak−W) alelle, associated with weak Fyb antigen expression are most often determined by c.256C>T and c.298G>A SNP, these polymorphisms occurring within the first intracellular loop of the Duffy protein with a frequency of approximately 2% in Caucasians. All polymorphisms of the duffy system found so far are described in Table The et a.l and Sellami et al. using flow cytometry technology have shown that individuals with two erythroid functional alleles (FYA/FYA) express approximately twice as much Fya antigens when compared to individuals with only one functional erythroid allele , express approximately only 50% of gpFy in their erythrocytes compared to homozygous individuals with both functional alleles , as shown in Table Tournamille et al. in an association study between the presence of FYX allele in heterozygosis, which is due to protein instability caused by the Arg89Cys mutation [Yazdanbakhsh et al. demonstrated, by flow cytometry, a 10% reduction in Duffy protein in the red blood cell membrane of individuals with the mutation .FYBW allele is associated with a reduced gpFy expression (approximately 10%) when compared to its expression from the FYA and/or FYB alleles [According to Zimmerman et al., the  alleles .6 epitopes, which is required for Plasmodium vivax invasion, was significantly lower in reticulocytes and mature red blood cells in the FYB/FYB genotypes than in the FYA/FYA or FYA/FYB genotypes. Therefore, the authors concluded that heterozygous individuals may have a greater amount of red cell receptor variations for P. vivax-binding parasitic proteins [Woolley et al. demonstrated in vitro studies differences in the level of expression of Duffy glycoprotein on reticulocyte surface of Caucasian and African–American individuals with Fy phenotype (a + b +) by flow cytometry. In their study, the expression level of the Fyproteins .P. vivax.This study aims to investigate the impact of Duffy polymorphisms on parasite density in Brazilian Amazonian patients infected by Plasmodium vivax, without co-infection with another Plasmodium species and without any associated disease, were randomly admitted.In this study, individuals of any gender, age and skin color who were at the first infection reported by Subjects were included according to the selection criteria of the research at the Tropical Medicine Foundation (TMF) Dr. Heitor Vieira Dourado, where blood samples were collected from January 2012 to April 2013 after the exposure of the research objectives to the patients. Participants were instructed on the objectives of the study and signed the Informed Consent Form (ICF). In case of minors under 18, the ICF was signed by the parent or guardian. Patients diagnosed with malaria were treated according to the Ministry of Health.The DNA samples and the clinical data of the patients were provided by the TMF, and these samples were sent to the Genomics Laboratory at the Hematology and Hemotherapy Hospital Foundation of Amazonas-HEMOAM, where they were analysed through molecular techniques for the detection of Duffy polymorphisms. This is a cross sectional study which the diagnosis of malaria was carried out at the TMF in the state of Amazonas, Brazil, through a specialized team with a standardized clinical and laboratory method.The diagnosis of malaria followed the standardized course of the TMH which is a national reference in the diagnosis and treatment of malaria. In this course a multiple reading of all the slides is carried out to confirm the parasitaemias, as well as the confirmation of the Plasmodium species detected by the polymerase chain reaction (PCR) method.FYB/FYES percentage found in the study by Albuquerque et al. was used as the basis for the sample calculation. This was the lowest frequency found in a total of 15.4% of patients with alleles of greater impact on parasitic density . We also used to compose the calculation, the annual average of 3100 patients treated at the Institute of Tropical Medicine of Manaus Doctor Heitor Vieira Dourado, positive for P. vivax.The 7.2% The sample was calculated using the program R Core Team statistical package (2013), using as parameters p probabilistic error of 0.05 and effect size of 0.5, with statistical power of 95%, so that the minimum sample determined was 122 individuals in total. Thus, the sampling of 287 was above the stipulated and thus we obtained an effect size and the statistical test increased .Parasitaemia was determined using a standard parasitological method, the thick blood smear, which involves collecting a drop of blood from the finger on a glass slide, followed by staining with vital dyes such as methylene blue or Giemsa. This technique is based on visualization of the parasite by means of optical microscopy. After staining, specific differentiation of the parasites is possible by optical microscopy, based on the analysis of their morphology and stages of development in the peripheral blood Fig. .Fig. 1DeThe determination of parasitaemia was based on the count of asexual parasites per 200 leukocytes and, in the case of less than 10 parasites identified in the reading, the count will continue up to 500 leukocytes. Microscopic counts greater than 500 parasites were interrupted after reading the last field (in which the number 500 occurred), even before reaching 200 leukocytes Table .Table 3SThe total number of white blood cells (leukocytes) of each patient was determined for the determination of the parasite density (PD). PD was calculated using the following formula:P. vivax were found. The implementation of the thick smear, as well as the definitions of parasitaemias and parasite densities (PD), was carried out according to the protocols of the Amazon Network for Surveillance of Resistance to Antimalarial Drugs - RAVREDA [The microscopic diagnosis with negative result was defined when, in at least 300 fields of the slide, no asexual forms of  RAVREDA . For div RAVREDA .Low parasite density: counting up to 7000 trophozoites per µL;Average parasite density: trophozoites counts between 7001 and 15,000 per µL;High parasite density: trophozoites number equal or greater than 15.001 per µL.This classification is based on counting parasites for every 100 leukocytes as described below:The limits of these categories were defined in the study by Alecrim et al. comparing the amount of parasites found and the symptoms presented by the patients studied. The clinical symptoms of malaria may be mild, moderate or severe, depending on the species of the parasite, the amount of circulating parasites, the time of disease and the level of immunity acquired by the patient .® Blood Mini kit . The concentration and quality of DNA was determined by measuring optical density in a Thermo Scientific Nano Drop 2000 apparatus. Genotyping was then performed using BioArray Human Erythrocyte Antigens (HEA) BeadChip , a high-throughput molecular assay that detects 38 red blood cell antigens and phenotypic variants. The BeadChip contains all probes of interest including internal positive controls, and negative controls of the reaction. Each probe is covalently attached to a microsphere type that can be distinguished on the basis of their spectrum qualities. The fluorescent signals emitted by different microspheres are then captured by imaging system (AIS400). Results obtained were analysed using (BioArray Solutions Information System) BASIS™ .Duffy genotyping was performed at the HEMOAM of the State of Amazons, Brazil, using the Bead Chip BioArray system. For genotyping, DNA from the patients were extracted using the kit QIAmpFYA/FYB - SNP 125 G>A; GATA - (Fy silencing) - SNP - 67 T>C and FY weak - SNP 265 C>T.In the determination of the Duffy system the following polymorphisms were analysed: 3 is showed in the Fig. P. vivax, it is possible to observe a statistically non-significant distribution in the Table The levels of parasite density found in the studied patients considering the number of parasites found per mmFYA*ES alleles, as well as FYA*W and even negative Duffy patients infected with P. vivax.Duffy genotyping was successfully performed on 287 patients as showed in Table FY*2 allele characterizing all polymorphic samples as FY*02W. 01 and FY*02.01 [In all samples studied, both polymorphisms at position 256C>T of the DARC gene and the SNP-67 T>C in the GATA promoter region were found only associated with the FY*02.01 .FY*01/FY*01; FY*01/FY*02 and FY*02/FY*02 were found in patients with three levels of parasite density , but genotypes formed with FY*01 or FY*02 alleles in heterozygosity with FY*02N.01 and FY*02W.01 alleles, were found in 34 (11.8%) patients who presented only low parasite density as shown in Table FY*02N.01/FY*02W.01 in one of those patients infected with P. vivax with the lowest parasite density found (78 parasites/mm3) presenting a type of malaria considered subclinical, being that this genotype, to date, had not yet been described in the literature.The genotypes FY*02N.01 and FY*02W.01 alleles, low parasites density. It was made a search to found other associations relationing the Duffy mutated alleles, age and gender of the participants as showed in the Table Distribution of Duffy allele frequencies in respect of low, medium and high parasitic density is showed in the Table 2.One of the 27-year-old male participants was heterozygote with GATA and FY 256 allele and parasitic density with 78 parasites per mmNo female participant showed the mutation FY 265.All participants showing Duffy mutations had also low parasity density.P. vivax was performed only in a comparative and inferential manner.Flow cytometry to quantify Duffy glycoprotein expression in patients with low parasitic density could not be performed due to limitations of the institution’s technical and infrastructure for this purpose. However, reference was made to other studies  and weak duffy (FY*02W.01) alleles in heterozygosis with FY*01 or FY*02, showed low parasite density, demonstrating a possible reduction in P. vivax adhesion caused by the reduction of the Duffy glycoprotein due to the presence of the polymorphic alleles, as demonstrated by King et al. who support the hypothesis that erythrocytes, expressing the FY */FY*02N.01, have a significant reduction in parasite adhesion when compared to erythrocytes expressing FY*02/FY*02, [All participants with the genotype composed of one of the polymorphic alleles as the mutated GATA  by the flow cytometry technique. This expression was significantly lower in reticulocytes and mature red blood cells (RBC) in the FY*02/FY*02 genotypes than in the FY*01/FY*01 or FY*01/FY*02 genotypes. The authors concluded that heterozygous individuals may have a greater amount of erythrocyte receptor variation for binding parasite proteins of P. vivax [Woolley et al. demonstrated in their study differences in the expression level of FyP. vivax .FY*02N.01 allele results in a 50% reduction of that protein on the surface erythrocyte invasion by P. vivax, although Twohig et al. reported evidence of Duffy-negative individuals (FY*02N.01/FY*02N.01) in regions endemic in Africa. which may be linked to the very low expression of glycoproteins, parasite P. vivax-like or even the existence of an alternative gateway found by the parasite.The results also agree with another very important study on the expression of the Duffy glycoprotein published by Tournamille et al. and Wolley et al. which showed that the presence of the FY*02W.01, due to a protein instability caused by the Arg89Cys polymorphism, which probably explains the reduction of the parasitic density in cases found in the Brazilian Amazon. Although the initial finding was related to a reduction in the incidence of malaria and not to the density of the parasite, this aspect is also important to address since it may be related to sub-clinical or asymptomatic malaria as found in results of this study.Yazdanbakhsh et al. demonstrated by flow cytometry a 10% reduction of the Duffy protein in the erythrocyte membrane of individuals with the heterozygous allele FY*02W.01 only in 3 patients who had a very low parasite density (78–513 trophozoites/μL), showing that this allele may be associated with subclinical malaria, confirming data published by Albuquerque et al. [P. vivax into erythrocytes, such as the Duffy glycoprotein polymorphisms in the host.It was possible to find e et al. . The parP. vivax infection, sporadically reported in some parts of the world were not quantified. According to the results, these cases occurred particularly more frequently in patients with FY*02 allele, demonstrating that these variables may potentially be associated.Cases of high parasite density related to FY*02N.01/FY*02W.01 genotype in one of the infected patients. This genotype was observed for the first time in the population studied. As expected, this patient had a very low parasite density, phenotyped as Duffy negative and presenting few symptoms of the disease. This genotype may be contributing to subclinical malaria in the Brazilian Amazon. However, only one individual was found, requiring a broader search for the confirmation of this new association study with malaria.Another interesting finding was the presence of the P. vivax infection [Kasehagen et al. conducted a cross-sectional malaria prevalence surveys in Papua New Guinea (PNG), where they have previously identified a new Duffy-negative allele among individuals living in a region endemic. This study provides the first evidence that Duffy-negative heterozygosis reduces erythrocyte susceptibility to nfection .FY*02N.01/FY*02W.01 genotype presenting the lowest density (78 parasites/mm3) and did not present symptoms of fever, chills and pain, among other characteristics of malaria, corresponding to 0.34% of the 287 patients studied. Despite the almost imperceptible symptomatology presented, this patient sought the medical service because relatives living in the same residence were infected and with symptoms characteristic of the disease. In a simple calculation of population projection based on these results, considering a region of approximately 12 million inhabitants living in an endemic area of malaria in the Brazilian Amazon, considering also the real statistical possibility of finding individuals with polymorphic duffy genotypes as described, it was infered that in addition to the Duffy negative individuals existing in the region, there is a considerable amount of inhabitants that may be serving as human reservoirs for the spread of malaria in the Brazilian Amazon making malaria eradication difficult.34 patients (11.8%) were found with a mutated Duffy allele that may have interfered with malaria infection, and in particular one patient with the P. vivax. The FY*02N.01 and FY*02W.01 alleles were found to be associated with low parasitic density in infected patients. Therefore, these polymorphisms appear to have a significant impact on the population in areas where malaria is endemic, and may lead to partial defense mechanisms against P. vivax.The present study presented new perspectives on the relationship of Duffy polymorphisms with parasitaemia and symptoms of malaria caused by


Plasmodium infection prevalence at household and village level in three villages in Ratanakiri Province, Cambodia. A two-level logistic regression model with a random intercept fitted for each household was used to model the odds of Plasmodium infection, with sequential adjustment for individual-level then household-level risk factors. Individual-level risk factors for Plasmodium infection included hammock net use and frequency of evening outdoor farm gatherings in adults, and older age in children. Household-level risk factors included house wall material, crop types, and satellite dish and farm machine ownership. Individual-level risk factors did not explain differences in odds of Plasmodium infection between households or between villages. In contrast, once household-level risk factors were taken into account, there was no significant difference in odds of Plasmodium infection between households and between villages. This study shows the importance of ongoing indoor and peridomestic transmission in a region where forest workers and mobile populations have previously been the focus of attention. Interventions targeting malaria risk at household level should be further explored.Heterogeneity in malaria risk is considered a challenge for malaria elimination. A cross-sectional study was conducted to describe and explain micro-epidemiological variation in  Plasmodium parasites and transmitted by female Anopheles mosquitoes, occurs throughout much of the world’s tropical and subtropical regions. Morbidity and mortality due to malaria has decreased worldwide with substantial upscaling of malaria control interventions, and a global malaria eradication goal has been declared2. However, at regional and local scales, there is substantial variation in distribution of malaria risk, in terms of population at-risk and intensity of transmission, due to climatic, geographic and temporal variations, and variations in human, vector and parasite ecology4. As malaria control moves towards elimination, there has been increased attention towards estimating and characterizing the total human Plasmodium infection prevalence, including asymptomatic and sub-patent infections as well as clinical cases5. In most settings, prevalence of asymptomatic infections is substantially higher than clinical malaria cases6. Though it remains unclear the extent to which asymptomatic infections contribute to malaria transmission7, achieving malaria elimination will likely require reduction of the prevalence of Plasmodium infection to zero for sustained interruption of transmission5. Characterising and addressing determinants of heterogeneity in total malaria risk, including symptomatic and asymptomatic infections, presents one of the key challenges in malaria elimination8.Malaria, an infection caused by Plasmodium infection9. Malaria can also cluster spatially in ‘hotspots’ of higher-than-expected malaria prevalence compared to surrounding areas11, and can be detected at spatial scales from sub-village to regional-level12. The importance of hot pops and hotspots relates to the hypothesis that a ‘parasite reservoir’ of asymptomatic, subpatent infections sustains malaria transmission14. The assumption behind identifying and targeting malaria hotspots is that infections within hotspots contribute to maintaining the parasite reservoir in a way that infections outside the hotspots do not, and that eliminating malaria from hotspots would lead to interruption of transmission in adjoining areas11. Evidence for this premise remains scant; the first trial of its kind showed no effectiveness of hotspot targeting on community-wide malaria prevalence in Kenya15.Heterogeneity in malaria risk is frequently conceptualised in terms of ‘hot pops’ and ‘hotspots’. Hot pops refers to population-subgroups defined by a cluster of demographic characteristics who are at higher risk of P. falciparum strains that are resistant to artemisinin-based combination therapies, the current first-line treatments for P. falciparum worldwide16. There is substantial heterogeneity in malaria risk throughout the GMS17. Part of this complexity relates to biology and ecology of the parasite and the vector; there are five Plasmodium species that cause human malaria infections in the GMS, and there is enormous diversity in the habitats, behaviours and vector competence of the numerous Anopheles vectors20. In the GMS, there is emphasis on ‘mobile and migrant populations’ as a key malaria risk group (i.e. hot pop)25, and malaria hotspots have been identified at different spatial scales28. Malaria persists at highest incidence in the GMS in remote forested regions inhabited by ethnic minority populations17, who frequently move between houses in the village and at forest farms according to work requirements29. Sleeping overnight at farms was previously shown to increase risk of Plasmodium infection27, and outdoor evening activities have been postulated as increasing risk of infection through exposure to early evening, outdoor biting vectors29.The Greater Mekong Sub region (GMS) is a global priority region for malaria elimination, due to the multiple emergence and spread of 31. Risk factors for individual-level infection such as age do not explain spatial clustering of malaria except where these demographic characteristics are over-represented, for example at mine sites and in forestry work31. Apparent spatial clustering of malaria may represent clustering of malaria at household level, and/or higher-level landscape effects such as local topography or elevation33, or village-level effects such as population size or access to malaria control programs31. Household-level determinants of malaria risk are not well characterised in the GMS, in part because it is frequently assumed that most or all malaria transmission occurs away from villages in most settings21. However, there are several regions in the GMS where village-based transmission likely persists, and there is some evidence for the importance of household-level characteristics as contributing to malaria risk through mechanisms other than individual-level mobility to higher-risk landscapes. Evidence of local transmission of P. vivax was found in a settlement on the Thai-Myanmar border that is a focal point for migrant movements, and variation in prevalence of P. vivax infection was attributed to differences in living conditions rather than migration patterns34. In Malaysia, a mix of individual and household-level characteristics relating to the peridomestic environment were risk factors for P. knowlesi infection35.In contrast to the emphasis on identifying hotpops and hotspots, there has been less attention towards explaining whether individual-level, household-level, or higher-level effects are the most important determinants of malaria risk, in the GMS and elsewherePlasmodium infections26. A follow-up study did not find evidence for Plasmodium hotspots in the same villages in the subsequent year, which will be presented in a forthcoming paper. To better understand the most appropriate units of analysis at which to characterise heterogeneity in malaria risk in this setting, we investigated the relative contribution of individual, household and village-level risk factors for Plasmodium infection.A recent dry-season survey of malaria prevalence in three villages in malaria hotspots in Ratanakiri province in Eastern Cambodia found several hotspots at sub-village level, however the detected hotspots contained only 60% of the Plasmodium infection data was available for 631 (88%) adolescents and adults, and 404 (93%) children. Plasmodium infection prevalence by PCR in adolescents and adults in 2016 and/or 2017 was 6.5% in Chamkar San, 10.9% in Phi and 16.6% in Tun, and in children, 4.1% in Chamkar San, 11.9% in Phi and 9.0% in Tun, and declined overall in the three villages between 2016 and 2017  and was treated with dihydroartemisinin plus piperaquine combination according to the national treatment guidelines, and one had a negative RDT.There were 713 respondents to the adolescent and adult survey, and 258 households (including 435 children) completed the household survey, representing 64% of individuals aged 12 years and over, 73% of children and 75% of households in the three villages. Participation in the surveys varied between the three villages  the night before the survey. Most children played outside every night (76%), and had similar frequencies of sleeping at farm/field and village locations in the rainy and dry season as adults Table .Table 4IMost households comprised up to 7 members (71%) Table . ConsidePlasmodium infection .In adjusted analyses, in the model with individual-level exposures only   Table . In the 6) Table . After i6) Table . Analogo6) Table .Table 8BThere was strong evidence of clustering at household level in the null model for children , which was not attenuated by adjusting for individual-level variables, but was substantially attenuated (71%) by adjusting for household-level variables, at which point there was no statistical evidence for the household-level effect (p = 0.12). Including village as a fixed effect did not further change the ICC . Farm machine ownership was protective for adolescents and adults but not children, possibly because farmers who have access to farm machines such as tractors spend fewer evening hours tending to their farms. There was negligible change from the unadjusted to the adjusted analyses, including after adjusting for village, which suggests that farm machine ownership is not a proxy for socioeconomic status, frequency of sleeping overnight at farms, or village-specific characteristics.Other household-level risk factors indicate the importance of peridomestic exposure to vector bites around houses and at farms. Satellite dish ownership is likely a proxy for hosting evening gatherings, which can include TV watching, and may indicate that groups of people congregate at these houses, potentially contributing to a pocket of transmission. Though satellite dish ownership was uncommon, the observation that the two Plasmodium infection prevalence. Soy bean farming remained strongly protective for children even after adjusting for village, however peanut farming, which occurred in Chamkar San and Tun but not Phi , increased risk. After including village in final model for adolescents and adults, the protective effect of cassava and soybean farming decreased, likely due to collinearity with village. Cassava farming was least common in Tun, which had the highest adolescent and adult Plasmodium infection prevalence, and soybean farming occurred mostly in Chamkar San, which had the lowest prevalence. Thus, these associations with household crop types could be causal, which could be explained by the effect of these crops on suitability of local farm landscapes for vector breeding, but crop type may also be a proxy for unmeasured characteristics.Crop type also had a significant effect on Plasmodium infection prevalence between households or between villages. Apart from age in children, no demographic characteristics were significant individual-level risk factors. Increasing prevalence of Plasmodium infection amongst older children likely reflects the age-shift in mean age at first infection in low transmission settings36, as well as plausibly increased exposure to biting vectors amongst older children.Individual-level risk factors did not explain differences in 37. That these groups were observed to often comprise individuals from multiple households may explain why individual-level risk factors increased the between-household variance. There may be a role for spatial repellents to protect people in peri-domestic farm spaces during vector biting hours.Amongst adolescents and adults, evening farm gathering frequency and hammock net use were the significant individual-level variables, which increased the between-household variance. Evening farm gatherings involve groups of people coming together to sit in the environs of the farm house  to partake in social drinking (‘parties’) and various ceremonies, mostly without wearing long clothing, and sometimes until late in the evening; thus participating individuals may be highly exposed to early evening, outdoor biting vectors38. Though the numbers using hammock nets were small, at least 50% of respondents who slept in a hammock net the night before the survey, or usually used hammock nets at farms and/or in the village, were malaria positive. Though the distributed hammock nets were insecticide-treated and provided by the national malaria control program, the last distribution occurred in 2012, therefore any insecticidal effect had likely subsided. In an elimination context, it is vital to ensure that distributed interventions reduce malaria transmission, and effects of hammock nets under conditions of actual use should be evaluated in a future study.Increased risk of malaria amongst adolescent and adult hammock net users is concerning, because hammocks have been distributed for use in this setting specifically to prevent forest malaria29. The data collection focused on specific activities, behaviours and characteristics that likely directly mediate exposure to vectors, rather than only general risk factors  that do not indicate potentially causal effects31. The multilevel modelling approach used in this study addressed a number of limitations of previous studies. Two multilevel studies of malaria epidemiology in Madagascar39 and Ethiopia40 included village-level but not household-level random effects, and concluded that village-level effects were important. However, the present study shows the importance of household-level effects in explaining differences between villages. Another study in Ethiopia investigated individual and household effects, but because the study was conducted within one administrative area, the authors could not address whether household-level effects explained differences between villages or analogous higher-level units41. A recent study in Peru42 compared risk factors in community-specific models to combined models, but reported variances of the random household-level effects were too small to allow for a sequential adjustment strategy as used here. None of these studies corrected for rescaling of variance after inclusion of covariates, which may have biased comparisons of variance between unadjusted and adjusted models. In general, multilevel modelling is underutilized in malaria epidemiology studies, with many studies fitting cluster-level risk factors in single-level models, despite recognition of the importance of contextual-level effects39.There were several strengths of this study, including the collection of data on an extensive list of individual and household-level variables, including several for which previous studies in the region have suggested could be linked to increased risk of malaria but for which epidemiological evidence was not availablePlasmodium infection in adjusted analyses, this may not have produced substantial bias in the findings. Similarly, though smaller households were under-represented, household size was not associated with odds of Plasmodium infection in the adjusted models for adolescents and adults, or children. Apart from village of residence, surveyed children did not significantly differ from non-surveyed children on demographic characteristics, so the findings from analysis of the children’s survey are likely to be least prone to bias. We were only able to conduct this survey at the mid-point between two malariometric surveys, however, as we focused on relatively stable risk factors, and as asymptomatic infections detected in the malariometric surveys were not followed up or treated, infection status in the first malariometric survey was unlikely to induce change in exposure patterns. We had no information on timing of infection, nor could we separate new from recrudescent P. vivax infections. In this study, species-specific analyses did not allow consistent estimation of whether individual and household-level risk factors explain differences in Plasmodium prevalence between the three villages because of correlation between Plasmodium species and village. For example, though Tun had the highest prevalence of Plasmodium infections overall, no P. malariae was detected in either year, and P. falciparum was detected only in 2016. Finally, as this study was only conducted in three villages, it remains unknown whether household-level risk factors would explain differences in Plasmodium infection prevalence in a larger number of villages and/or over larger areas. Future studies should include sufficient villages to allow a village-level random effect to be fitted in addition to the household-level random effect. The inclusion of village as a fixed effect rather than a random effect would have biased the estimates of village towards being more strongly associated with the outcome in this study, so the finding that village was no longer significant after adjusting for household risk factors is robust to this bias.Limitations of the study include incomplete sampling, which was mostly related to inaccessibility of households and/or individuals, with frequent heavy rainfalls flooding rough access tracks to outlying households. This is reflected in the under-representation of individuals residing mainly at their farm houses in the sample, especially in Phi village Table . Younger21. This study found no association between Plasmodium infection and frequency of village or farm sleeping, in dry or rainy seasons, nor working in the forest, after adjustment for household-level risk factors. There has been insufficient recognition that risk of Plasmodium infection in populations with multiple residence patterns may be determined by the effect of characteristics and activities conducted within peridomestic spaces in combination with extent of local vector-supporting landscapes, rather than mobility patterns per se29. The potential continuing role of indoor transmission argues against any scaling back of the bed net distribution program. Furthermore, rigorous analysis of how risk factors for infection act at different levels of analysis is essential for the meaningful interpretation of spatial clustering of Plasmodium infections, whether detected as “hotspots” or using other spatial approaches. At small spatial scales, apparent “hotspots” may reflect aggregated household-level effects, thus characterizing household-level effects should be an integral component of spatial epidemiological approaches.It remains an important area of research to identify strategies to achieve malaria elimination, and whether the individual, household, hotspot or community, in village or non-village locations, should be the primary unit(s) for intervention. Household characteristics have been overlooked as determinants of malaria risk in regions of the GMS where local transmission occurs, with much more emphasis on individual-level characteristics, especially mobility patterns and occupational profiles linked to forest work6. A study of reactive household-based screening and treatment for asymptomatic infections in Western Cambodia showed no effectiveness compared to random screening43, but this was attributed to most infections occurring away from the villages in this setting. Further, this study did not analyse the degree of household clustering of Plasmodium infection prior to initiation of the intervention. Reactive screening and treatment would likely be less resource intensive than mass drug administration campaigns targeting entire villages or districts, for which emerging results have shown mixed effectiveness in other GMS settings44.There may be grounds for considering reactive household-based screening and treatment strategies in this and similar settings. Treating entire households for each confirmed case (with or without screening of household members) could be an effective intervention that could be implemented as part of routine malaria control, especially if more sensitive diagnostic tools for asymptomatic infections become available for operational usePlasmodium infection prevalence between households and between villages, and points to the importance of ongoing indoor and outdoor peridomestic transmission in a region where individual mobility patterns have previously been the focus of attention. LLIN coverage should be improved, and interventions targeting malaria risk at household level should be further explored. Amidst the urgency of eliminating malaria in Cambodia and the rest of the GMS, investigating how determinants of Plasmodium infections act at different levels should not be overlooked, which is important for understanding local malaria epidemiology and for identifying the most appropriate intervention targets.This study showed the importance of household-level risk factors but not individual-level risk factors in explaining differences in Plasmodium infection were investigated using a cross-sectional survey, conducted as part of a two-year study in three villages  in Ratanakiri Province, eastern Cambodia26. As part of the two-year study, two dry-season malariometric surveys were carried out in January/February 2016 and March/April 2017, in which fingerprick blood samples were collected for detection of Plasmodium infection by nested real-time polymerase chain reaction (PCR), as previously described26. During the malariometric surveys, axillary temperature was also measured, and participants were asked whether they had fever in the past 48 h. Individuals with fever or other malaria related symptoms were offered the possibility to take a rapid diagnostic test  and if positive, treated according to the national treatment guidelines. The questionnaires in the current study included items on demographic, social, behavioural and environmental characteristics that were putative risk factors for Plasmodium infection, based on a framework for micro-epidemiological malaria studies31, an exploratory field visit in the three study villages, and previous anthropological and epidemiological studies in the region29. The survey was conducted mid-way between the two malariometric surveys, such that the questionnaires included questions about activities during the previous dry season , and the rainy season .Individual and household-level risk factors for The three study villages represent distinct transmission contexts in Ratanakiri province. Chamkar San is closest to the provincial town of Banlung, and is also the furthest from the forest fringe, with deforestation partly a consequence of increased agriculture and plantations in the area Fig. . Tun and26, and was updated during the current study as required. Each household and each individual was assigned a unique study identifier. A household was defined as a family unit who habitually reside together in one or more dwellings, including village and farm houses. At any given time, household members may stay in their different houses, and move between residences according to seasonal work requirements.A census conducted in the three villages in January 2016 (n = 1792) formed the basis for the sampling frame23. Household heads or their spouses were asked to respond to a household questionnaire, which included questions about the individual-level characteristics of each child residing in the household. Temporary visitors (duration of stay <1 month) were excluded, though few were present.All resident individuals aged 12 years and older were eligible to participate in the individual survey, and information on children aged 11 years and younger was collected as part of the household survey. The 12 years age cut-off was chosen because adolescents often have different sleeping and activity patterns from their parentsBetween September and December 2016, trained surveyors went house by house supported by village guides to administer the individual and household questionnaires. Surveyors rotated between study villages weekly to reduce risk of bias in questionnaire responses. Surveyors made three attempts to reach households and individuals for participation. Survey data was collected on paper forms, and then double-entered and cleaned in EpiData .Plasmodium infection  detected by nested real-time PCR in either or both of the two malariometric surveys. Blood samples were collected and processed as previously described26.The primary outcome was The individual questionnaire focused on activity and mobility patterns that may affect exposure to biting vectors in the evening and at night. Frequency of overnight stays at farm and village locations were asked separately by season (rainy/dry). Outdoor evening activities included outdoor TV/DVD watching, indoor TV/DVD watching that occurred outside of a bed net, and evening outdoor gatherings/drinking parties. Frequency of evening activities and usual bed net use were asked separately for farm and village locations. Frequencies were collected as categorical responses . Usual sleeping time at farm and village locations were also collected. Usual frequency of evening activities in the forest was difficult for respondents to estimate during piloting, therefore respondents were asked whether they had been in the forest after 5 pm in the past year, and for which activities. Bed net use the night before respondent was interviewed was also collected.Plasmodium infection prevalence approximately homogenous at different ages within each age band. Age was not used as a continuous variable because there were imbalanced proportions of respondents reporting their age as 20, 30, 40 or 50 years, reflecting uncertainty about precise age amongst this population. Ethnicity was categorized as ‘ethnic minority’ or ‘Khmer’, as specific ethnicity co-varied too substantially with village to allow independent estimation.Other individual-level variables included age, sex, ethnicity, occupation, duration of residence and history of malaria. Age was initially examined in 5-year age groups, and then revised to four age groupings of 12–15 years, 16–29, 30–49, and 50 years or older, with A reduced set of individual-level variables were collected for children 11 years or under, including age , sex, ethnicity, frequency of overnight stays at farm and village locations by season, frequency of outdoor evening play, usual bed time and bed net use the night before the survey.45. House construction variables were recorded for the house where the interview was conducted, which was the household main residence at the time of the survey. An example of the different housing styles in the study villages is shown in Fig. Household-level exposure variables included household size, house construction, total number of houses owned, farms and fields owned, household wealth, cash crops grown, household water source and household mobility. Having a household member who stayed overnight at a plantation in the past year, and households hosting hired workers overnight, were also recorded. A household wealth index was constructed using principal components analysis on 16 variables reflecting household assets , buffalo or cow ownership, house construction  and number of farms and fields owned. The first principal component (20.4% explained variance), onto which motorbike, solar panel, battery and DVD/MP3 player ownership as well as roof and wall material loaded most strongly (eigenvectors >0.3), was retained as a household wealth index score. K-means clustering analysis was used to partition the wealth index score into 4 groups. Partition methods  and number of groups  were compared and the final model selected so that differences in mean scores between adjacent categories were similarPlasmodium infection. There were two objectives for the multilevel analysis; firstly, to identify risk factors for Plasmodium infection at individual and household level; secondly, to assess whether differences in odds of Plasmodium infection between households and between villages remained unexplained after adjustment for individual and household risk factors. To achieve these objectives, a step-wise modelling approach was used, as follows. First, a null model with household random intercepts only was fitted to calculate the crude household-level variation in odds of Plasmodium infection. Second, crude odds ratios and 95% confidence intervals were calculated for each individual-level exposure variable, and included in a combined multivariable model if p < 0.20. Manual backwards stepwise selection was used to retain variables significant at p < 0.05, with age retained as an a priori confounder. Village was then added as a fixed effect to determine if individual-level variables explained variation in odds of Plasmodium infection between villages. Household-level variables were similarly selected, and then added to the individual model, and the explained between-household variance was determined. Village was added to the final model as a fixed effect, and its significance assessed.Two-level logistic regression models with a random intercept fitted for each household were used to model the odds of individual Challenges interpreting the results of multilevel logistic regression models include the interpretation of cluster-specific odds ratios, and making appropriate interpretations of the variance of the cluster-level effect within and between models. These were addressed as follows:46. For individual-level characteristics, the interpretation is that the odds ratios reflect the change in odds of the outcome at each level of the exposure variable for individuals within the same cluster and conditioned on all other covariates. However for cluster-level effects, the interpretation is the change in odds of the outcome at each level of the exposure variable relative to the baseline category within the same cluster (and conditioned on covariates), which is problematic because cluster-level values are constant for all individuals within a cluster46. To address the difficulty in interpreting household-specific fixed effects, the approximate marginal (i.e. population average) effects were estimated by calculating and applying a shrinkage factor (equation 2 in46) to the household-level log-odds ratios and presented as supplementary to the main results.The covariate odds ratios in multilevel logistic regression models have a cluster-specific interpretationPlasmodium infection) is a latent continuous variable for the propensity to be Plasmodium infected, which manifests as a binary variable once an unobserved threshold is reached46. This approach allows both the cluster-level and individual-level variance to be measured on the log-odds scale, with the between-individual variance following the logistic distribution and fixed at π2/3. Thus, the ICC, which expresses the proportion of total variance that is due to the household-level variance can be estimated. Likelihood ratio tests were used to assess the null hypothesis that the ICC was equal to zero; i.e., no evidence of household-level clustering. To complement the interpretation of the ICC, median odds ratios (MOR) were also calculated47. MORs are a function of the household-level variance only, and can be interpreted as the increased median odds of Plasmodium infection if an individual living in one household moved to a household with higher odds of Plasmodium infection, conditioned on covariates48. A MOR of 1 indicates no difference between households. As it is expressed as an odds ratio, the magnitude of the household-level random effect can be directly compared to the magnitude of the individual or household-level risk factor odds ratios 48.The relative importance of individual-level compared to household-level effects in each model was assessed in two ways. First, the intra-class correlation coefficients (ICC) were calculated at each stage of model adjustment. The latent response formulation was used to estimate the between-subject variance on the log-odds scale, which assumes that underlying the observed binary outcome  was applied to rescale the random variance of the adjusted models to that of the null model, which permits direct comparison at each stage of model adjustment46.The proportion of explained variance at successive stages of model adjustment was calculated the difference between the variance of the random effect in each adjusted model and the variance of the random effect in the null model, expressed as a proportion of the variance of the random effect in the null model. However, as a consequence of the fixed between-individual variance in the latent response formulation, adjustment for individual-level covariates rescales the cluster-level variance, such that household-level variance may appear to increasextlogit, median odds ratios were calculated using xtrho, and marginal odds ratios and variance scaling factors were calculated directly46.In the analyses, frequency variables were first fitted as categorical variables, and then as frequency-weighted continuous variables for comparison; the latter were preferred as long as effect estimates for covariates did not meaningfully shift (>10%) compared to fitting categorical variables. Total number of farm houses and total number of village houses were fitted as linear variables. Missing data were addressed by complete case analysis. P-values were calculated using likelihood ratio tests. Statistical analyses were conducted in Stata/IC v13.1 ; specifically, multilevel logistic regression models and ICCs were estimated using Study protocols were approved by the institutional review boards of the National Ethical Committee on Health Research of Cambodia , the Institutional Review Board of the Institute of Tropical Medicine Antwerp  and the Ethical Committee of the University of Antwerp . After the study information sheet was read out, or provided to literate individuals, verbal informed consent to participate in the survey was obtained and documented. For minors, the informed consent of their parent or legal guardian was required, in addition to their own assent to participate. All individuals were free to refuse or withdraw participation at any time. We confirm that all research was performed in accordance with the Declaration of Helsinki Ethical Principles for Medical Research involving Human Subjects, and all other relevant guidelines and regulations.The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.Supplementary Tables


The WHO currently advocates parasitological confirmation of malaria before treatment is commenced. However, many arguments have emerged both for and against this new position. To contribute to the debate, this secondary data analysis was conducted to determine the likelihood of malaria parasitaemia in a child presenting with fever, vomiting, or cough in the Kassena-Nankana District. The dataset for this analysis was generated during a study to assess the incidence and risk factors for paediatric rotavirus diarrhoea in the Kassena-Nankana District. Over a two-year period, trained field staff recruited 2086 subjects with episodes of diarrhoea aged 24 months or below into the study. A standard case report form was used to collect data on histories of illness, symptoms, vaccination, and anthropometry. Blood smears were tested for malaria parasites. The data set generated was obtained, cleaned, and analysed using Epi Info version 7.1.1.14 statistical software. Of the 2086 subjects recruited, 2078 had blood smears done and 54.0% had malaria parasites. Fever and vomiting appeared to be associated with parasitaemia with odds ratios of 1.9 (95% CI: 1.5586–2.2370) and 1.2 (95% CI: 1.0352–1.4697), respectively. Cough however appeared protective with an odds ratio of 0.8 (95% CI: 0.6910–0.9765). The odds of parasitaemia appeared to increase where a child presented with more than one symptom. Nearly half (46%) of the subjects in this study presented with symptoms but had no malaria. Presumptive treatment of malaria may therefore be useful in situations where diagnostic tests are not readily available, its routine practice should however not be encouraged. Malaria still remains one of the greatest threats to the survival of the Sub-Saharan African child today. In 2015, an estimated 212 million cases of malaria occurred globally, out of which the WHO African Region accounted for 90.0% of these cases, followed by the WHO South-East Asia Region (7.0%) and the WHO Eastern Mediterranean Region (2.0%) [To ensure prompt treatment and avert the possibility of mortality, a practice of presumptive treatment was widely advocated by many. The WHO in its 2006 treatment guidelines advocated treatment of malaria on grounds of clinical suspicion in areas which have high stable transmission for children less than 5 years .Unfortunately, these symptoms singularly or in combination with other symptoms may be caused by other equally life threatening conditions such as urinary tract infections, meningitis, acute viral hepatitis, enteric fever, yellow fever, gastroenteritis, acute respiratory infections, pneumonia, and many more . The reaThe argument for or against the practice of presumptive treatment of malaria is one that is still raging on even though the WHO has since revised its position on the subject. The latest WHO Guidelines for the Treatment of Malaria state that “all cases of suspected malaria should have a parasitological test (microscopy or rapid diagnostic test) to confirm the diagnosis” . This la Plasmodium falciparum prevalence rate in children aged 2-10 years from 37.0% in the years 1985–1999 to 17.0% in 2007. In the face of evidence like this, fevers among children can no more be presumed to be from malaria. If this fact is ignored and malaria is still presumed to be the cause of every fever, then a lot of diagnoses will be missed and this will definitely have implications on morbidity and mortality [This position of the WHO is shared by many. One significant argument advanced is that malaria transmission has over the years declined so much that the once so-called highly endemic areas have now become less endemic. For example, there is a sharp decline in Sub-Saharan Africa of theortality , 7.A difficult challenge to evidence-based treatment of malaria is how to obtain laboratory confirmation in deprived settings. However, the introduction of malaria rapid diagnostic tests (RDTs) provides an answer to this challenge. RDTs have been shown to be reliable, easy-to-use, and inexpensive diagnostic tests. RDTs have a good sensitivity, require minimal training and retain their accuracy even after extensive storage under tropical conditions. Two separate meta-analyses have demonstrated that the performance of RDTs is comparable to that of expert microscopy , 9.In routine practice, these diagnostic tools have proved to be of high performance if only they are carried out well . Indeed,In an attempt to contribute to the debate and verify whether the mere presence of the so-called “malaria symptoms” is enough to warrant an antimalarial prescription, this study was designed. It is a secondary data analysis in which we sought to determine whether the mere presence of symptoms deemed to be malaria symptoms is associated with an increased likelihood of malaria parasitaemia in a child in the Kassena-Nankana District (KND) of Northern Ghana; and if it is associated, is the association strong enough to warrant an antimalarial prescription without laboratory confirmation? We hypothesized that presenting with vomiting, fever, and/or cough is associated with an increased likelihood of malaria parasitaemia in infants in the KND.2 and a population of about 160,000 and is one of the hyperendemic areas of malaria transmission. Navrongo, the district capital is home to one district hospital, and the Navrongo Health Research Centre (NHRC); one of the renowned health research institutions in the country. The Navrongo Demographic Surveillance System (NDSS) is run by the NHRC and monitors population dynamics in the area [The dataset for this analysis was generated during a study to assess the “incidence and risk factors for paediatric rotavirus diarrhoea in northern Ghana”, a study carried out in the Kassena-Nankana District of the upper east region of Ghana. The KND is one of the 230 districts in Ghana and lies in the Guinea Savannah belt. It is at the extreme north of the country  and sharthe area . Each coThe study was based at three health facilities: the Paga health centre, Kassena-Nankana East (KNE) health centre, and the War Memorial Hospital in Navrongo . Trained field staff working in these three health facilities screened and recruited subjects with diarrhoea who were brought to the health facilities by mothers and caretakers. Children were eligible for inclusion in the study if they were aged no more than 24 months and had passed three or more loose stools per day, on any of the previous 3 days. Once recruited, subjects were then treated for their diarrhoeal episodes and those who were very sick were referred to the district hospital for further management. Subjects were not followed up for a mortality endpoint. Fieldwork lasted from August 1998 to July 2000.A standard case report form was used to collect information on histories of illness, vaccination, and anthropometry. Height was measured using a length board, and weight using an electronic weighing scale. To permit calculation of the Vesikari score as a measure of diarrhoea severity, information was collected on duration of diarrhoea, peak number of stools passed per day, duration of vomiting and peak frequency of vomiting per day, degree of fever, presence and severity of dehydration, and treatment.A stool sample was taken if possible; otherwise a rectal swab was performed. The samples were transported to Accra for virus identification at the Noguchi Memorial Institute for Medical research. Detection of rotavirus was done by the enzyme-linked immunosorbent assay (ELISA) technique. Blood smears were taken by laboratory staff during field visits and blood films prepared and analysed for malaria parasites at the NHRC laboratory. Where films were positive, parasite load was determined by (1) counting the number of parasites amongst 200 white blood cells (WBCs), (2) dividing the number obtained by 200, and (3) multiplying the ratio by the total number of WBCs obtained from the patients full blood count (where available), or 8000 (WHO standard WBC count per uL). Mathematically, the parasite count could be expressed as Count/uL = Number of parasites/200 x Total WBC count of patient (or standard WHO figure of 8000).The forms were double-entered into a FoxPro database in Navrongo and data cleaning done before analysis. On obtaining the data, the dataset was converted into an excel file and analysed using Epi Info version 7.1.1.14 statistical software. Using this software, frequencies were calculated for demographic characteristics of participants, while bivariate analysis was conducted to obtain the odds of a child getting a positive smear for malaria if he/she presented with various symptoms. Symptoms were fever, vomiting, and cough. Diarrhoea was excluded since it had a 100.0% frequency. In the calculations, parasites were exposure variables, while symptoms were outcome variables. Odds ratios were calculated with associated 95% confidence intervals.The “incidence and risk factors of paediatric rotavirus diarrhoea in the Kassena-Nankana District of the upper east region of Ghana” project from which we extracted data for our analysis was approved by the ethics committees of the London School of Hygiene and Tropical Medicine, Ghana Health Service, and Navrongo Health Research Centre. Community entry in the form of a community durbar with chiefs and people present was done before start of the study. Prior to data collection, consent forms were given to parents/primary caretakers before subjects were enrolled. We sought permission from the investigators before extracting the dataset.A total of 2086 children aged up to, but not above 2 years, were recruited into the study as follows. 1138 (55.0%) were males and 948 (45.0%) females. About 2078 of these children had blood smears performed out of which more than half the number of blood smears (54.0%) was positive. In terms of symptom distribution, diarrhoea was the baseline criterion for inclusion into the study and therefore had a 100.0% distribution. However, vomiting constituted the commonest symptom apart from diarrhoea, occurring in 58.8% of children compared to 47.4% cough, and 38.8% for fever . This diSex did not seem to influence the occurrence of parasites or symptoms in study subjects as 54.0% of males and females each carried parasites in their blood. Fifty-nine per cent (59.0%) of both sexes also presented with vomiting, whiles 48.0% for males and 46.0% for females presented with cough. Fever had the least prevalence of 37.2% and 40.7% for males and females, respectively. The distribution generally did not seem be influenced by age group either. However, infants between 7 and 12 months appeared to have higher prevalence rates of parasites and symptoms than all other age groups .The results showed a seasonal variation in the prevalence of symptoms and parasite load . GeneralWhen individual symptoms were juxtaposed against parasites, fever appeared to be the symptom most associated with parasitaemia. The odds of testing positive for parasites given the presence of fever were 1.87(CI: 1.5586 - 2.2370). If children presented with vomiting, they had 1.23 Odds (CI: 1.0352-1.4697) of testing positive for parasites. Cough seemed to rather protect against the likelihood of parasites with an odds ratio of 0.82 (CI: 0.6910–0.9765). The odds of parasitaemia in a child increased as number of presenting symptoms correspondingly increased. Where a child presented with only one of the symptoms, the odds of parasites were 1.33. This increased to 1.36 for two symptoms and 1.88 for all three symptoms .Malaria in Ghana accounted for about 35.0% of Out Patients Department (OPD) attendance in hospitals in the late 1990s and some researchers believe this prevalence has increased over the years. This figure, however, varies greatly from region to region depending on the sociodemographic characteristics of an area. The Kassena-Nankana District has over the last two decades been recognized as one of the most endemic regions for malaria in Ghana . The parParasite prevalence has never been shown to be influenced by sex in malaria transmission. This is further evident from the sex distribution of parasites in this analysis. Age, however, appears to influence this. Typically, neonates have been generally thought to be more immune to malaria than older children owing to the fact that maternal antibodies are usually present in them and confer some immunity. From age one month to one year however, babies become more susceptible and show high parasite rates as shown in this analysis. The decline in maternal antibodies when their own immune systems are not yet well developed may be responsible for this increased susceptibility.The Kassena-Nankana District is generally characterized by a dry savanna climate. This situation however changes during the rainy season which extends from June to November. During this period, malaria prevalence increases as mosquito breeding places abound with pockets of water in various receptacles. It is therefore not surprising that this analysis shows higher parasite prevalence during the rainy season. Other studies in the study area have described similar trends , 14. ThiTypically, malaria is characterized by bouts of fever, chills, and rigors. Other symptoms such as vomiting, jaundice, dyspnoea, and many others are usually present. Fever has been found to be one of the most common presenting symptoms and has therefore often led to presumptive treatment. Results in this analysis however showed parasitaemia in only 23.0% of children presenting with fever. This compares well with results in other studies which report 15.0% of fever cases with parasitaemia [We found vomiting of children to be less indicative of malaria. This could be due to the fact that diarrhoea which was the main inclusion criterion in the recruitment of cases into this study often occurs together with vomiting as symptoms of gastroenteritis. Any association that may have existed between vomiting and parasitaemia will therefore be weak. It could also be a true indication that vomiting alone is not predictive of malaria as it is widely believed. In either case, the significance of this analysis remains the same; vomiting alone in general is not enough to indicate a presumptive diagnosis of malaria, and confirmatory laboratory tests would have been essential.Cough generally is more of a symptom of respiratory disease than malaria even though complications of malaria may occasionally present with cough and rapid breathing. In this analysis, the apparently protective nature of cough against parasitaemia is an indication that a cough in a child is not likely to be due to malaria. Such a child should be carefully examined for other causes of coughs such as respiratory tract infections.An increasing likelihood of parasitaemia when the number of presenting symptoms increases as is shown in our analysis is in keeping with the general rule in making clinical diagnosis in medical practice. Generally, the more a patient presents with signs and symptoms of a condition, the more likely it is that they have that condition. Indeed, it even becomes more certain where pathognomonic signs and symptoms (a particular sign/symptom whose presence means that a particular disease is present beyond any doubt) are present. In malaria however, no pathognomonic signs and symptoms exist, and the very classical signs and symptoms that suggest malaria also suggest other conditions such as enteric fever, urinary tract infections (UTI), respiratory tract infections, etc. A laboratory confirmation is therefore always necessary. The WHO's earlier call for presumptive treatment of malaria was in good taste and was intended to encourage prompt treatment and prevent unnecessary malaria deaths. However, considering the weight of the current evidence, it can only be hoped that many more deaths have not been caused instead.A primary limitation of our analysis is the use of a preexisting dataset which did not permit us to examine other symptoms beyond what was captured in the dataset, i.e., fever, diarrhoea, vomiting, and cough.Added to this limitation was the limitedness in the age category of study subjects. Given the opportunity, we would have expanded the age bracket to include older children and stratified the analysis to determine if variations existed between age groups.The results of our analysis showed that there was an association between malaria parasitaemia and symptoms such as fever, vomiting, and cough. The likelihood of parasitaemia also increased where these symptoms occurred together. However, not all children presenting with these symptoms had malaria parasitaemia. The implication of this finding is that, while it may be expedient to presumptively treat children suspected to be suffering from malaria in emergency situations and in instances where laboratory confirmation is not readily available, the routine use of this approach should not be encouraged. In these situations, presumptive treatment can be ongoing, while alternative diagnoses are actively considered to confirm or refute the presumptive diagnosis of malaria. This is necessary to prevent the over diagnosis of malaria and the misuse of antimalarials. Most importantly, this will help eliminate the risk of missing out on other potentially fatal diseases.