CR1) gene, named Sl2 and bMcC, occur at high frequencies, consistent with selection by malaria. Previous studies have been inconclusive. Using a large case-control study of severe malaria in Kenyan children and statistical models adjusted for confounders, we estimate the relationship between Sl2 and bMcC and malaria phenotypes, and find they have opposing associations. The Sl2 polymorphism is associated with markedly reduced odds of cerebral malaria and death, while the bMcC polymorphism is associated with increased odds of cerebral malaria. We also identify an apparent interaction between Sl2 and α+thalassaemia, with the protective association of Sl2 greatest in children with normal α-globin. The complex relationship between these three mutations may explain previous conflicting findings, highlighting the importance of considering genetic interactions in disease-association studies.Malaria has been a major driving force in the evolution of the human genome. In sub-Saharan African populations, two neighbouring polymorphisms in the Complement Receptor One  in certain human genes can protect against malaria. Over time, mutations that protect people living in Africa from dying from malaria have been passed down through generations. A good example is the sickle cell mutation, which causes red blood cells to be of an unusual shape, but also affects the ability of malaria parasites to grow normally within red cells. Finding new mutations that protect against malaria may help scientists understand how severe malaria happens and eventually develop new drugs and vaccines against the disease. Some studies have found that mutations in a gene called complement receptor 1 (CR1) may be protective, although others have disagreed.Now, Opi, Swann et al. show that children with one of the CR1 mutations were one-third less likely to get cerebral malaria and half as likely to die as children without the mutation. In the study, genetic and health information on more than 5,500 children in Kenya were analyzed to see if the severity of malaria differed depending on whether they had a CR1 mutation. They also found that the CR1 mutation is only protective against severe malaria when the child does not have another malaria- protective mutation called α-thalassemia. In children with α-thalassemia, the CR1 mutation does not make a difference.The interaction between the CR1 mutation and α-thalassemia may explain why some studies did not show a benefit of CR1. If the researchers did not include α-thalassemia in their assessment, they could not have seen the whole picture. Future studies showing how the CR1 mutation protects against cerebral malaria could help identify new treatments that prevent severe disease or death. More study of interactions between genes that play a role in malaria may also be helpful. CR1 is nd McCb) . The nonectively   and uninfected RBCs, known as rosettes  that mediates rosetting by iRBCs, potentially protecting against severe malaria by reducing rosetting  were comparable to other African populations , we found a non-significant association between the Sl2 allele and severe malaria overall, with the Sl2/Sl2 genotype being associated with an OR for severe malaria of 0.90  . A significant protective association was observed for Sl2 in the recessive form (adjusted Odds Ratio (aOR) 0.78; 95% CI 0.64–0.95; p=0.011), which was most marked for cerebral malaria  , and death among children admitted with a specific diagnosis of cerebral malaria in the full adjusted analysis   . We attep=0.006) . The Sl2p=0.007) . Unexpecgenotype . We foun malaria , or with density .bMcC and increased susceptibility to severe malaria overall . These analyses suggest an additive protective association with the aSl2/McC haplotype , with broadly consistent results observed for analysis of genotype combinations   . Once aggenotype . We foun malaria .bMcC in the Kenyan population, and suggest that other life-threatening childhood diseases may have been responsible for selection of bMcC. We therefore used the same longitudinal cohort study to investigate whether the bMcC and Sl2 alleles influence the risk of other childhood diseases. bMcC was associated with borderline significant protection against several common infectious diseases including LRTIs, URTIs and gastroenteritis  and the a/McCaSl2/Sl2-McC genotype combination was associated with protection against cerebral malaria . As such, we considered samples from this population to be appropriate for testing rosetting as a potential mechanism of action. The median rosette frequency (percentage of iRBC that form rosettes) was significantly lower in P. falciparum isolates from malaria patients with one or more Sl2 alleles than in isolates from Sl1/Sl1 donors    and haptt (HbAS) . It is pquencies , and conlatforms , insteadlatforms . Replicaoversial .Sl2 allele might influence cerebral malaria by studying P. falciparum rosetting, a parasite virulence factor associated with severe malaria in African children    show redcontrols . Therefocontrols , blood gcontrols  and RBC controls , it is pcontrols  may in putations . In addiutations . Howeverutations  have notbMcC homozygotes are relatively infrequent in Kenya, which limited our power to detect associations with bMcC in the homozygous state. Our longitudinal cohort study generated several values of borderline statistical significance for the bMcC allele which are inconclusive. Studies with larger sample sizes will be needed to examine the specific associations of bMcC on assorted childhood diseases. Another limitation is that our functional  and epidemiological (Kenya) studies were conducted in different populations. The mechanisms of rosetting and associations with malaria severity are thought to be similar across sub-Saharan Africa . Ideally, future epidemiological and functional studies of specific polymorphisms on malaria should be conducted within a single population, although this remains logistically challenging.Our studies have several limitations: n Africa , suggestSl2 allele may have reached high frequency in African populations by conferring a protective advantage against cerebral malaria, our data suggest that bMcC arose due to a survival advantage afforded against other non-malarial infections  are widely used in genetic epidemiological studies of malaria due to the logistical challenges of sample collection in malaria endemic countries and the changing epidemiological patterns of disease.All epidemiological and clinical studies in Kenya were carried out in the area defined by the Kilifi Health and Demographic Surveillance System (KHDSS), with Kilifi County Hospital (KCH) serving as the primary point of care . MalariaP. falciparum infection complicated by one or more of the following features: cerebral malaria (CM) (a Blantyre coma score (BCS) of <3) n = 943; severe malarial anaemia (SMA) (hemoglobin concentration of <5 g/dl) n = 483; respiratory distress (RD)  n = 522 or ‘other severe malaria’ , hypoglycemia and hyperparasitemia) n = 318. Controls (n = 3829) consisted of children 3–12 months of age who were born consecutively within the KHDSS study area between August 2006 and September 2010 and were recruited to an ongoing genetic cohort study  were also excluded  in association with a P. falciparum positive slide at any density. The most common non-malaria-related clinical events reported during the study period included upper respiratory tract infections (URTIs), lower respiratory tract infections (LRTIs), gastroenteritis, helminth infections and skin infections, as defined in detail previously  or uncomplicated malaria , and for whom Sl and McC genotyping was available were analyzed.This study has been described in detail previously . BrieflyP. falciparum isolates from patients recruited into the Mali case-control study was determined by microscopy after short term culture (18–36 hr), as described in detail previously .The rosette frequency (percentage of mature infected erythrocytes forming rosettes with two or more uninfected erythrocytes) of eviously . Of the eviously , 167 werSl and McC alleles were genotyped using either the SEQUENOM iPLEX Gold multiplex system  (Kenyan study)  or using QIAamp DNA Blood Mini Kits . SNPs giving rise to the n study)  or by ann study) . Genotyplsewhere .Sl and McC alleles were examined in genotypic, dominant, recessive and additive models of inheritance, with the best fitting model selected based on Akaike information criterion (AIC). Analyses for the Kilifi case-control study were performed in R  (The effects of the Austria)  using thAustria) , while aSl and McC genotype were included together in a statistical model to examine their associations with malaria susceptibility. Odds Ratios (ORs) and 95% Confidence Intervals (CI) were generated using mixed effect logistic regression analysis both with and without adjustment for ethnicity and location of residence as random effects, and sickle cell genotype, α+thalassaemia genotype, and ABO blood group (O or non-O) as fixed effects   . The ethifi area . 2000 boMcC genotype , Sl genotype  sickle cell genotype, α+thalassaemia genotype, ABO blood group, ethnic group, season (defined as 3 monthly blocks), and age in months as a continuous variable.For the Kenyan longitudinal cohort study, Incidence Rate Ratios (IRRs) and 95% CIs were generated using a random effects Poisson regression model that took into account within-person clustering. Data were examined with and without adjustment for confounding by +thalassaemia genotyping was not available for the Malian study and sickle cell trait is extremely uncommon in this population, therefore neither variable was included in the model. 2000 bootstrapped iterations were run to give adjusted ORs.For the Malian case-control study, ORs and 95% CIs were computed using mixed effect logistic regression analysis with adjustment for location of residence as a random effect and age, ABO blood group (O or non-O) and ethnicity (Dogon or non-Dogon) as fixed effects. αCorrections for multiple comparisons were not performed, instead all adjusted odds ratios, confidence intervals and p values have been clearly reported. This approach has been repeatedly advocated, particularly when dealing with biological data . A detai In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.+thalassaemia" for consideration by eLife. Your article has been favorably evaluated by Prabhat Jha (Senior Editor) and three reviewers, one of whom, Madhukar Pai (Reviewer #1), is a member of our Board of Reviewing Editors.Thank you for submitting your article "Two complement receptor one alleles have opposing associations with cerebral malaria and interact with αThe reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this letter to draw your attention to significant concerns that you would need to address before this work could be considered for publication.Summary:This is an interesting but complex study with different study designs, looking at interactions between 3 mutations and malaria. The study raises hypotheses that will need to be confirmed in future studies.CR1 and several malaria phenotype  as well as non-malarial disease. The authors found that 1) the Sl2/Sl2 genotype is associated with protection against cerebral malaria and death, p=0.006 and p= 0.002 respectively, 2) the bMcC allele is associated with increased susceptibility to cerebral malaria and death, p=0.008 and p=0.046 respectively, 3) the Sl2/Sl2 genotype was associated with protection against uncomplicated malaria p<0.001, and 4) the bMcC allele was associated with protection from non-malarial disease p=0.02. Finally, the authors demonstrated that the allele Sl2 was associated with reduced ex vivo rosette frequency, whereas McC had no significant effect on P. falciparum rosette frequency. The paper is interesting and suggests the role of CR1 polymorphisms in susceptibility/resistance to malaria and non-malarial disease. However, the reviewers have major concerns on several points.The study evaluated the relationship between 2 SNPs (rs17047661 and rs17047660) of Essential revisions:1) Given the dramatic reductions in severe malaria and deaths in the past decade, it is a bit strange that the studies were done with data collected during 2001-08 (case control study), and 1998-2001 (cohort study). So, a decade later, the authors have gone back to analyze stored samples. The implications of this are not clear and need to be clearly addressed. Are there time trends that can confound the associations? What about use of old samples and sample quality? Were the hypotheses pre-stated or generated post-hoc? (presumably the latter).2) As regards the case-control study, I would need more convincing that cases and controls were derived from the same study base. The difference in age distribution will likely not matter for the genetic mutations, but what about implications for disease severity?3) The authors indicated that the study included 5545 children from Kenya consisting in 1716 severe malaria cases and 3829 community controls.a) The authors performed the analysis on a subset of the samples used previously by Rockett et al. (2014). The authors should clarify why they did not use the total sample set of 2268 severe malaria cases included in Rockett et al. and how the 1716 samples were selected.+thalassaemia genotype and ABO blood group were available in the previous study of Rockett for the Kenyan population.b) As indicated by the authors, 407 individuals are excluded as lived out with KHDSS . Why? The authors should clarify this point. DNA not available? It would be surprising because all CR1 genotype (rs17047661 and rs17047660), sickle cell genotype, ac) It is not clear for me whether new genotyping has been performed for this study or if they re-used the genotypes obtained in the Rockett's study.d) Why did the authors use controls recruited to an ongoing genetic cohort that were representative of the general population  as indicated in the subsection “The Kilifi case-control study” rather than used the controls of the previous study  that were also representative of the general populations? Is there a scientific reason? Are the Rockett controls not relevant? It would be interesting if the authors performed statistical analysis with the Rockett controls to confirm the results.e) According to the sample size even if the p-value was lower than 0.05 and due to multiple-testing, the statistical results indicated only suggestive associations. As the p-value is borderline, these findings need to be replicated in an independent sample set to be convincing.CR1 polymorphisms in the multi-centre candidate gene study , but the cases of the present study come from the Rockett's study and were compared to another control group. This information is confusing. It would be very important to confirm the association by using the Kenya controls from the Rockett's study to exclude potential selection bias in the control group. To perform this analysis, the authors should also take into account the complex interactions between bSl2, McC and α+thalassaemia detected in the present study.f) In the Discussion, the authors indicated that no significant association was seen with 4) This reviewer's primary struggle with this paper is that it does not fully address how the known interaction between α-thalassemia and Sickle may be influencing or overlapping with these results. As the raw data are not included in the supplementary for these loci, the reader is forced to interpret these results with only the models and genotype frequencies that the authors have presented. This work uses substantially larger populations with better exposure controls than past reports on this topic, and thus after addressing several concerns, this work will be a valuable contribution to the community.Sl, and Mc together in each patient? Ideally this would also be broken down by disease outcome as well.5) What is the population breakdown for the combined genotype that includes α-thalassemia, Sickle, Sl2/Sl2 genotype is associated with protection against cerebral malaria in Mali” would appear to be miss-specified in light of Williams, 2005. It would seem more appropriate to model the double deletion vs. single or normal; or perhaps better in the early models to allow all three categories to compete for Sickle and Swain interactions. During model building the α-thalassemia-Sickle interaction may have been missed because of this, and it makes it difficult to determine whether the α-thalassemia-SL interaction is independent. Although the main effect term for Sickle is included in downstream adjusted models, there is not enough information to assess whether this factor would account for the α-thalassemia-Sickle interaction.6) The binary parameterization of α-thalassemia described in Appendix 1 subsection “The 7) Cerebral malaria numbers are reported for the Mali cohort in Supplementary file 2, however associations with Knops are not discussed. It appears that these numbers may conflict with the trends in Kenya, and yet rosetting is still tested against these genotypes and presented as a potential mechanism of protection. Please reconcile this section or consider limiting the mechanistic connection to citing Rowe, et al. Essential revisions:1) Given the dramatic reductions in severe malaria and deaths in the past decade, it is a bit strange that the studies were done with data collected during 2001-08 (case control study), and 1998-2001 (cohort study). So, a decade later, the authors have gone back to analyze stored samples. The implications of this are not clear and need to be clearly addressed. Are there time trends that can confound the associations? What about use of old samples and sample quality? Were the hypotheses pre-stated or generated post-hoc? (presumably the latter).Making full use of existing datasets is of major importance in malaria genetic epidemiological studies, and there is no evidence to suggest that malaria phenotype/genotype associations vary over time. Historic datasets represent a huge investment of time and funding in establishing and collecting appropriate samples under logistically challenging conditions. Moreover, in many of the institutions with the greatest capacity for the ethical collection and processing of carefully phenotyped patient samples, the rates of severe malaria have declined in recent years. This is evident in some of the traditionally low-moderate malaria transmission areas of sub-Saharan Africa such as Kilifi in Kenya, the main focus of the current study. Unfortunately, most areas with continuing high malaria transmission and associated high mortality do not yet have the scientific infrastructure necessary to carry out large, high quality case-control studies. Hence, it is currently difficult to perform epidemiological studies on malaria using newly collected samples. We briefly describe these issues in the “Datasets studied” section of the Materials and methods which states:“Historic datasets (i.e. >10 years old) are widely used in genetic epidemiological studies of malaria due to the logistical challenges of sample collection in malaria endemic countries and the changing epidemiological patterns of disease.”All the samples used were of high quality and underwent stringent quality control. The “Sample processing and quality control for the Kenyan case-control study” section in the Materials and methods has been expanded to cover the quality control steps employed in sample collection and genotyping.The hypotheses addressed in this study were generated after collection of the specimens, but prior to any exploratory analysis of the relevant datasets.2) As regards the case-control study, I would need more convincing that cases and controls were derived from the same study base. The difference in age distribution will likely not matter for the genetic mutations, but what about implications for disease severity?The cases and controls studied here were all derived from exactly the same area, which is the geographic region defined by the Kilifi Health and Demographic Surveillance System (KHDSS) . This is described in the Materials and methods, subsection “The Kenyan study area”, and a precise description of the cases and controls is described in an expanded section in the Materials and methods, subsection “The Kenyan case-control study”.The controls were infant samples that were used to estimate the relevant genotype frequencies in the population from which the cases arose. This method has been widely used in African genetic association studies  and is supported by general commentators . This is currently the most logistically feasible way of collecting sufficiently large numbers of control samples in many sub-Saharan African settings.Text describing the rationale for using infant control samples has been added to the Materials and methods, subsection “The Kenyan case-control study”.3) The authors indicated that the study included 5545 children from Kenya consisting in 1716 severe malaria cases and 3829 community controls.a) The authors performed the analysis on a subset of the samples used previously by Rockett et al. (2014). The authors should clarify why they did not use the total sample set of 2268 severe malaria cases included in Rockett et al. and how the 1716 samples were selected.We apologise for the confusion caused by the lack of detail on how our study design differs from Rockett et al. The differences between our study and Rockett et al. is now fully explained in the “Comparison between this study and Rockett et al.” section in the Materials and methods . See also the comments below.+thalassaemia genotype and ABO blood group were available in the previous study of Rockett for the Kenyan population.b) As indicated by the authors, 407 individuals are excluded as lived out with KHDSS . Why? The authors should clarify this point. DNA not available? It would be surprising because all CR1 genotype (rs17047661 and rs17047660), sickle cell genotype, aWe excluded the severe malaria cases from outside the KHDSS because all of the controls came from within the KHDSS. Using only cases and controls from exactly the same area allowed the use of location as a random effect in the final statistical model, which greatly improved model fit. This is now described in the “Comparison between this study and Rockett et al.” section in the Materials and methods.We have repeated our analysis including the severe cases of subjects who lived outside of the KHDSS study area (Supplementary file 1K), and this gives the same overall result as that shown in the main text. This is stated in the Materials and methods subsection “Comparison between this study and Rockett et al. ”.c) It is not clear for me whether new genotyping has been performed for this study or if they re-used the genotypes obtained in the Rockett's study.Sl and McC polymorphisms were originally typed as part of a larger study by Rockett et al., which included case-control data from 12 global sites .”We re-used genotypes from the Rockett’s study. This is now explained in the “Sample processing and quality control for the Kenyan case-control study” section of the Materials and methods, which states “The +thalassaemia, as described in the Materials and methods, subsection “Laboratory procedures”.The only additional genotyping of the Kenyan samples that was done for our study was for sickle cell trait and α d) Why did the authors use controls recruited to an ongoing genetic cohort that were representative of the general population  as indicated in the subsection “The Kilifi case-control study” rather than used the controls of the previous study  that were also representative of the general populations? Is there a scientific reason? Are the Rockett controls not relevant? It would be interesting if the authors performed statistical analysis with the Rockett controls to confirm the results.The controls in our study and the controls in Rockett et al. are the same. This is now explained in the Comparison between this study and Rockett et al.” section in the Materials and methods, which states:Sl, McC, sickle cell genotype,α+thalassaemia genotype and ABO blood group data were available.”“In both our study and Rockett et al. , the control samples were identical and all came from within the KHDSS. Our study has 120 fewer controls than Rocket et al.  due to missing genotypes, because we only used controls for whom full e) According to the sample size even if the p-value was lower than 0.05 and due to multiple-testing, the statistical results indicated only suggestive associations. As the p-value is borderline, these findings need to be replicated in an independent sample set to be convincing.Sl2 and cerebral malaria was first reported in a small case- control study from western Kenya , but most subsequent studies have been underpowered. Our study is thus the first adequately powered independent sample set that replicates the protective association between Sl2 and cerebral malaria. Furthermore, our study shows for the first time that bMcC and α+thalassaemia influence the protective association of Sl2 on cerebral malaria risk. Hence, our study contributes significantly to this debate and provides novel insights that may explain previous conflicting findings on CR1 polymorphisms and malaria.We agree that there is evidence, but not unequivocal evidence, for the suggested associations. The protective association between +thalassaemia results from a deletion mutation, not a SNP, it cannot be detected on classical SNP-genotyping platforms, and has to be performed manually using labour intensive PCR-based methods , as in our study. The attempts of our collaborators in the MalariaGen consortium to impute α+thalassaemia genotypes from existing SNP genotyping data have not yet been successful. Hence, currently, to our knowledge, there are no other large sub-Saharan case-control studies that are typed for α+thalassaemia and Sl and McC polymorphisms that could be used for replication. Future work will address this need, but this is beyond the scope of the current manuscript, which is already complex, incorporating as it does results from two different epidemiological studies and functional data.We agree that further replication of our novel findings will be required. Unfortunately, because αWe have added text discussing the important issues of replication in the second and fourth paragraphs of the Discussion.b and α+thalassaemia detected in the present study.f) In the Discussion, the authors indicated that no significant association was seen with CR1 polymorphisms in the multi-centre candidate gene study , but the cases of the present study come from the Rockett's study and were compared to another control group. This information is confusing. It would be very important to confirm the association by using the Kenya controls from the Rockett's study to exclude potential selection bias in the control group. To perform this analysis, the authors should also take into account the complex interactions between Sl2, McCAs stated in response to 3d above, the controls used in our study are the same as the controls used in Rockett’s study.As explained in response to 3a and 3b above, our study excludes some of the cases included by Rockett et al., due to their residence outside of the KHDSS. However, re-analysis including the additional cases studied by Rockett et al. (Supplementary file 1K) returns the same results as those shown in our main text. In other words, the difference in inclusion criteria does not explain why our results differ from Rockett.The key distinctions that explain why we obtain a different result to Rockett et al. are:Sl and McC in the same statistical model and adjust for confounding factors, including the statistically significant interaction with α+thalassaemia, whereas Rockett et al. looked at each SNP in isolation. This is now stated in the Materials and methods, subsection “Comparison between this study and Rockett et al. ”, last paragraph.i) We include Sl and McC together in the same statistical model is that the two SNPs are only 33 bp apart in the CR1 gene, and each causes a change in amino acid charge (Sl: rs17047661 R1601G and McC: rs17047660 K1590E) with potential to impact upon the structure and function of the CR1 protein. Hence, it is biologically plausible that Sl might influence McC and vice versa.The rationale for examining the effects of ii) We are examining data from a single region in Kenya, whereas Rockett et al. analysed pooled data from 12 global sites. They state in their paper “…it is undoubtedly also the case that authentic genetic associations might be missed in multicentre studies if there is heterogeneity of effect across different study sites”.bMcC and α+thalassaemia influence the protective association of Sl2 with cerebral malaria, and that the frequencies of bMcC  and α+thalassaemia are known to vary geographically, it would be predicted that the association of Sl2 with cerebral malaria will vary by location, and may be missed by pooling data across different study sites.Given that our data suggest that We have summarised these arguments in the third and fourth paragraphs of the Discussion.4) This reviewer's primary struggle with this paper is that it does not fully address how the known interaction between α-thalassemia and Sickle may be influencing or overlapping with these results. As the raw data are not included in the supplementary for these loci, the reader is forced to interpret these results with only the models and genotype frequencies that the authors have presented. This work uses substantially larger populations with better exposure controls than past reports on this topic, and thus after addressing several concerns, this work will be a valuable contribution to the community.+thalassaemia” in Appendix 2, and in new tables . See also comments below.The potential effect of the α-thalassemia/sickle interaction on our results is answered in detail in a new section “Exploration of the negative epistasis between sickle trait and α5) What is the population breakdown for the combined genotype that includes α-thalassemia, Sickle, Sl, and Mc together in each patient? Ideally this would also be broken down by disease outcome as well.+thalassaemia and Sl for each clinical outcome in Supplementary file 1P.We have added data for the combined genotypes compromising sickle trait, α6) The binary parameterization of α-thalassemia described in Appendix 1 subsection “The Sl2/Sl2 genotype is associated with protection against cerebral malaria in Mali” would appear to be miss-specified in light of Williams, 2005. It would seem more appropriate to model the double deletion vs. single or normal; or perhaps better in the early models to allow all three categories to compete for Sickle and Swain interactions. During model building the α-thalassemia-Sickle interaction may have been missed because of this, and it makes it difficult to determine whether the α-thalassemia-SL interaction is independent. Although the main effect term for Sickle is included in downstream adjusted models, there is not enough information to assess whether this factor would account for the α-thalassemia-Sickle interaction.+thalassaemia used in our model i.e. no α+thalassaemia alleles  vs. one or more α+thalassaemia alleles was chosen in accordance with a previous report showing that both heterozygous (single deletion) and homozygous (double deletion) α+thalassaemia genotypes are associated with protection against severe malaria and death in the Kilifi area . A description of the parameterization of theα+thalassaemia variable can now be found in the Materials and methods, subsection “Statistical analysis”, second paragraph.The parameterization of α+thalassaemia is now described in the “Exploration of the negative epistasis between sickle trait and α+thalassaemia” section in Appendix 2. Analysis of our dataset confirms the existence of negative epistasis between sickle trait and α+thalassaemia in this population (Supplementary file 1N). However, of interest, this negative epistatic interaction was only seen in the severe malaria cases without cerebral malaria, whereas the α+thalassaemia/Sl interaction was specific to cerebral malaria cases. Therefore, the two interactions appear to be mutually exclusive. Therefore, we can confirm that for cerebral malaria in this dataset, no significant interaction exists between sickle trait and α+thalassaemia. This is the case no matter which α+thalassaemia parameterisation is used.Investigation of interaction between sickle trait and α7) Cerebral malaria numbers are reported for the Mali cohort in Supplementary file 2, however associations with Knops are not discussed. It appears that these numbers may conflict with the trends in Kenya, and yet rosetting is still tested against these genotypes and presented as a potential mechanism of protection. Please reconcile this section or consider limiting the mechanistic connection to citing Rowe, et al.Sl2/Sl2 genotype and cerebral malaria was identified on analysis of the Mali dataset  and the a/McCaSl2/Sl2-McC genotype combination was associated with protection against cerebral malaria . As such, we considered blood samples from this population to be appropriate for testing rosetting as a potential mechanism of action.There is no conflict between the Mali and Kenya data. A protective association between the Sl2 and cerebral malaria in the Mali case-control to the Results, subsection “The Sl2 allele was associated with reduced ex vivo rosette frequency in P. falciparum clinical isolates from Mali”.To make this clearer we have now included a sentence describing the protective association between


Though the burden of malaria is declining, challenges in control continue globally, regionally and nationally as the transmission of malaria is dynamic and determinants differ by place and time, and across populations. The current level of knowledge on malaria prevalence and associated factors in specific communities, such as pastoralist communities of Ethiopia, is lacking.A community based cross-sectional survey was conducted among pastoralist communities from December 2011 to January 2012. Background information and peripheral blood samples were collected from 461 randomly selected study participants. Multivariate regression analysis was done to explore the risk factors associated to malaria.Plasmodium falciparum and Plasmodium vivax was 64.3 %  and 21.4 % , respectively, while mixed infection was 14.3 % . The infection rate was higher among lactating  and pregnant  women compared with other community groups like infants (12 %). Mosquito net coverage of the study population was 90.1 % with an average of 1.8 per household. Traditional practices related to malaria prevention and treatment were not significantly associated with malaria infection (p > 0.05). Pregnancy  and saving mosquito net for later use  were independently associated with prevalent malaria infection.The prevalence of malaria among 461 examined study participants was 6.1 % . The infection rate with In spite of high coverage of mosquito nets, prevalence of malaria in this pastoralist community was high, affecting pregnant and lactating women at a higher rate. Pregnancy and saving mosquito nets for later use were identified as the associated risk factors. Health education on prevalence of malaria and knowledge on risk factors might be able to change the health behavior in this pastoralist community which consequently can decrease the malaria morbidity and mortality.ISRCTN73824458, Registered 28 September 2014.ISRCTN  Malaria has been a global challenge for many years , 2. EvidMalaria in Ethiopia has remained a public health problem; even though, its burden has been declining following the mass distribution of Long Lasting Insecticide Treated Nets (LLITNs) and Arthemisine Combined Therapy (ACT) –8. As thMajor challenges in controlling the spread of malaria include the vector’s resistance to Indoor Residual Spray (IRS) and the parasite to drug therapy , 21, 22.‘Boronge’- is a practice of giving the leaf juice of ‘Tseeako’  herb for malaria  patient every morning or night till the symptoms subside. ‘Ara’- is a practice of applying freshly slaughtered small intestine of a goat or sheep on the face of an acutely sick chinkilo patient and feeding the patient the meat. ‘Dugo’ – is a mechanism of blowing mosquitoes out from inside of a ‘dugo’ house . Witchcraft – a consultation of witches to perform a magic healing for chinkilo patient. Rhanto/Rhae – is a practice of piercing chinkilo patient’s frontal vein to get the dark blood out thinking that it could have caused the disease.A community based cross-sectional study was conducted from December 2011 to January 2012 in Benna Tsemay district, Southern Ethiopia. The district is located 735 kilometers south west of Addis Ababa and the population is estimated to be 62,362 whose livelihoods are based primarily on rearing animals . The altitude of the district is 1500 m above sea level with average annual temperatures ranging from 26 °C (during cold months) to 40 °C (during dry months). The rainfall distribution is bimodal with average annual rainfall of 800 mm. The district has a long dry season from December to the beginning of March, while June and July is a short dry season . TraditiA priori sample size was estimated with the assumption of 50 % prevalence of malaria, 95 % confidence level and 5 % margin of error with a design effect of 1.2 for compensation of loss of efficiency [th) with a goal of enrolling 461 subjects. Sampling frame of each cluster was obtained from the district health office.ficiency . Among tPlasmodium spp. quantification and the thin for Plasmodium spp. identification. The negative or positive slides were determined after careful observation of 100 fields of a single slide by experienced laboratory technicians at Tercha Hospital. A laboratory technician at regional laboratory center confirmed each 5 randomly selected low positive and negative blood films according to the current WHO guideline for external quality assurance without prior knowledge to the original results [After consent and enrollment, blood samples were collected by using Rapid Diagnostic Test (RDT) and blood slides. The laboratory diagnoses were performed following the standard WHO laboratory procedures . Trained results .In addition to blood smear collections, a structured and pre-tested questionnaire was used to collect information from each HH member including associated factors such as background characteristics, mosquito net (MN) use and traditional practices related to malaria infection. Observation of MNs in the HH was also recorded by trained data collectors. Regarding children under five, their parents or guardians were interviewed. Questionnaires were designed in the English language and translated to the local languages (Tsemako and Benegna). All subject questionnaire data and the corresponding smear results were compiled and cross-checked by using subject identification numbers.p < 0.2 by bivariate analysis were entered into multivariate analysis. The method used in multivariate model was Backward Stepwise (Likelihood Ratio). The Hosmer and Lemeshow Test was used to assess the fulfillment of basic assumptions of logistic regression while the computed change of -2Log Likelihood and Omnibus tests were used to assess the goodness of model fitness for the variables explained.All data were entered into EPI Info version 3.5.3 software for cleaning and then transferred to SPSS version 20 software for analysis. Univariate analysis was used to determine frequencies while an Open Source Epidemiologic Statistics for Public Health (Open Epi) software version 2.3.1 was used to estimate prevalence of malaria and its 95 % CI after cross tabulating by SPSS version 20. Bivariate and multi-variate analyses were performed to examine the association of variables with malaria prevalence. All variables with The research was ethically approved by Hawassa University Institutional Review Board and South Omo Zone Health Department. The study participants were clearly explained about risks, discomfort, procedures, benefits, incentives, and issue of confidentiality and safety of the study.A total of 461 participants from 91 HHs provided blood samples and questionnaire data, and no HHs or individuals declined to participate in the survey. The median age of subject participation was 13 years, ranging from 9 months to 65 years. Men were 220 (47.7 %) and women in the reproductive age group were (age 15 to 49) were 129 (28 %), among which 17 (3.7 %) and 18 (3.9 %) were pregnant and lactating women respectively  visited ‘witchcraft’ practitioners (Table Participants from Tsemay 41.4 %) and Benna (50.1 %) tribes constitute 422 (91.5 %) and 383(83.1 %) were traditional believers (neither Muslim nor Christian by religion). A total of 164 MNs were observed, of which 152 (92.7 %) were LLITNs. The coverage of at least one mosquito net per HH was 90.1 % with the average MN per HH of 1.8. One-hundred-sixty five (39.4 %) of the respondents reported that they were using MN all the time at night and used MN the night before the survey day. However, only 4 (23.5 %) of pregnant and 4 (22.2 %) of lactating women reported that they always sleep under a MN. Two-hundred-nine (45.3 %) of the study participants practiced .4 % and Plasmodium falciparum, Plasmodium vivax and mixed infection constituted 18 , 6  and 4 , respectively. Malaria prevalence was 12.0 %  among infants and 9.8 %  among children under-five years old. Eight per cent of children aged 5 to 9 years were infected. But, the infection rate among those aged 10 to 24 years  was 2.9 % . A similar rate of malaria infection was observed among the 35 to 44 year old group , while no infection was observed among participants 45 years of age and older. Generally, the rate of infection declined as the age increased; though a significant rise was seen among the 25 – 34 year old age group . Stratifying by sex, women and men were infected at comparable rates at 6.6 % and 5.5 %, respectively. However, the infection rate among lactating  and pregnant  women was much higher compared to other segments of the population. The infection rate was higher among those who practiced at least one traditional practice (8.1 %) compared to those who did not (1.9 %)  cases were reported positive for malaria. Out of these, p < 0.05). However, variables such as religion, ethnic group, age groups, school attendance, pregnancy and sex did not significantly associate with infection of malaria , living within three kilometers of potential mosquito breeding site , being a lactating woman , irregular or no use of MNs , MNs not over sleeping areas , visiting Witchcraft , practicing ‘Ara’  and exercising at least one traditional practices  were significantly associated with the malaria infection  and saving MN for later use  were found to be independently associated with malaria infection in the study , and much lower than we had anticipated. However, this rate was similar to recent results reported from different parts of Ethiopia including the National Malaria Baseline survey of 2007 (4.1 %) , integraPlasmodium falciparum is responsible for 64.3 % of malaria infections compared to 21.4 % by Plasmodium vivax in the study area. This was similar with the result of the National Survey and other studies conducted in Ethiopia [P. vivax than P. falciparum [P. falciparum is responsible for 100 % of infections in Kenya and 95 % in South Sudan [Our study has revealed that Ethiopia , 12, 13.lciparum . One facIn this study, the highest prevalence of malaria was recorded among lactating women (22.2 %) followed by pregnant women (17.6 %) and infants 12 %). Prior studies have not reported prevalence as high as these figures among such vulnerable populations in Ethiopia. One study conducted in Logos, South West Nigeria conducted from March 2007 to February 2008 among pregnant women in an antenatal care program reported a prevalence of 7.7 % 25) which is much lower than the current findings. Among various age groups, under-five years (9.8 %) had the second largest morbidity of malaria next to infants. This result is inconsistent with the findings from a longitudinal parasitological survey conducted in high land fringes of Butajira in central Ethiopia . It is c which is %. PriorP. falciparum which could end up with adverse effects on a mother, fetus and new-born. Affected women may suffer from anemia, fever, cerebral malaria, hypoglycemia and puerperal sepsis and mortality. In regard to mother and fetus health, it commonly causes abortion, still birth and congenital infection while the effect on a new-born leads to low birth weight, pre-maturity, intrauterine growth retardation, illness and mortality [Malaria during pregnancy was common among participants of this study, particularly ortality , 12, 25.The coverage of at least one mosquito net per HH was 90.1 %, of which 92.7 % were LLITNs. The use of MNs prior to the survey day was only 39.4 %, with hanged MNs being observed in 46.8 % of these HHs. This finding is consistent with the result of a study done in Oromiya (91 %) and Amhara regional states in 2007 , and higFactors such as unavailability of MNs, irregular use of MNs, saving MNs for later use, using MNs for other purpose such as keeping grain, not hanging MNs and unsafe MNs (with multiple holes) were evaluated to determine association with malaria infection. In this study, only participants from HHs who saved (not used MN) MN for later use were 9.6 times more likely to be infected by malaria compared with those who did not save MNs for later use. This result was consistent with the findings reported by Alemu et al. from Jimma town in which those who did not use MNs were 13.6 times more likely to be infected by malaria compared to those who used ITNs . WhereasLocal traditional practices such as ‘Boronge’, ‘Ara’, ‘Dugo’, witchcraft and ‘Rae/Rhanto’, related to malaria infection were also evaluated. Despite the higher malaria cases observed among performers of traditional practices and a significant statistical association of malaria infection by the bivariate analyses, no significant association was found for such traditional practices by multivariate regression model. This study found that these local practices specific to the study area were not favoring malaria infection. However, attention must be given while performing these practices as higher infection rate was observed among performers of at least one traditional practice (8.1 %) compared to non performers (1.9 %) in the study area.Since a cross-sectional study design was used in this study, the results cannot be generalized. Information bias was limited by providing orientation for study participants through local languages, training interviewers and blinding blood sample examiners. With these, accuracy was assured and information bias was reduced.In spite of good coverage of MNs, malaria in pastoralists communities predominantly affects lactating and pregnant women, infants and under five children. Information, Education and Communication approaches should strongly and regularly be undertaken in a way that it could favor MNs utilization in the pastoralist communities with priority to high risk groups through close monitoring and evaluation at each level of health administration.


PfHRP2 RDT for the diagnosis of malaria in children under-5 years of age living in a malaria endemic area.It remains challenging to distinguish malaria from other fever causing infections, as a positive rapid diagnostic test does not always signify a true active malaria infection. This study was designed to determine the influence of other causes of fever, prior anti-malarial treatment, and a possible seasonality of the performance of a PfHRP2 RDT in diagnosing malaria, the RDT results were compared with the gold standard  and test results were analysed by assuming that prior anti-malarial use and bacterial/viral infection status would have been known prior to testing. To assess bacterial and viral infection status blood, urine and stool samples were analysed.A prospective etiology study was conducted in 2015 among febrile children under 5 years of age in Burkina Faso. In order to assess the influence of other febrile illnesses, prior treatment and seasonality on the performance of a PfHRP2. Plasmodium falciparum malaria was diagnosed in 49.8% (340/683) by microscopy compared to 69.5% (475/683) by RDT-PfHRP2. The RDT-PfHRP2 reported 29.7% (141/475) false positive results and 1.8% (6/340) false negative cases. The RDT-PfHRP2 had a high sensitivity (98.2%) and negative predictive value (97.1%), but a low specificity (58.9%) and positive predictive value (70.3%). Almost 50% of the alternative cause of fever were diagnosed by laboratory testing in the RDT false positive malaria group.In total 683 blood samples were analysed with microscopy and RDT-PfHRP2 in a malaria endemic area may cause misdiagnosis of the actual cause of fever due to false positive test results. The development of a practical diagnostic tool to screen for other causes of fever in malaria endemic areas is required to save lives.The use of a malaria RDT- PfHRP2), which is specific to Plasmodium falciparum, and that can persist in the blood for weeks after treatment [PfHRP2-based RDT (RDT-PfHRP2) will remain positive, suggesting a malaria infection, whereas the actual cause of fever is due to another infection [PfHRP2 up to 3–4 weeks after successful malaria treatment [PfHRP2 allows to treat a large part of children who actually have malaria, the children with false positive results could be suffering from alternative causes of fever like bacterial or viral infections [With the recommendation of the World Health Organization (WHO) to confirm a malaria infection in a febrile child before commencing treatment, malaria rapid diagnostic tests (RDTs) have become indispensable in the screening of malaria-suspected fever cases . The maireatment –7. This nfection , 8. Thisreatment , 10. Thifections .PfHRP2 in different malaria transmission areas under controlled conditions. For example, Grandesso et al. [P. falciparum malaria [PfHRP2 is affected by other infections in malaria endemic areas, the end result might be that other potential causes of fever are being ignored, and that the fever is still being treated as if it is malaria.Up to date several studies have assessed the performance of malaria RDT-o et al.  showed t malaria . This spPfHRP2 significantly contributed to reducing anti-malarial prescriptions, mainly in children [PfHRP2 tests in relation to the accuracy of a RDT for the diagnosis of both malaria and malaria-attributable fever or to other infections [PfHRP2 for the diagnosis of malaria in children under-5 years living in a malaria endemic area.In Burkina Faso, like many other malaria endemic areas, the introduction of malaria RDT-children . Howeverchildren . Previoufections , 15. HowThe study was conducted in the health district of Nanoro, located in central-west part of Burkina Faso. Nanoro is around 100 km from Ouagadougou, the capital of the country. The data were collected in four peripheral health facilities of the health district of Nanoro  and the referral hospital Saint Camille of Nanoro. These peripheral health facilities have been chosen as study locations because of their accessibility and close distance (the most remote is 20 km) from the central laboratory. CMA  Saint Camille of Nanoro was included to increase inclusion of severe cases that were referred from peripheral health facilities. The district hospital CMA Saint Camille de Nanoro is the reference hospital of the health district of Nanoro with trained medical staff and equipped laboratory facilities for the management of difficult medical cases that are referred from the peripheral health facilities. The peripheral health facilities are the first point of medical contact within the community for the management of less complicated medical cases by Community Health Workers based on guideline of diseases management . MalariaPfHRP2 employed. Furthermore, clinical specimens like blood and urine for bacterial cultures, and stool for rotavirus and adenovirus tests were also collected systematically and analysed at the microbiology laboratory of the Clinical Research Unit of Nanoro (CRUN). This study was approved by the National Ethical Committee in Health Research, Burkina Faso (Deliberation No. 2014-11-130).This study has been conducted as part of a larger project that aims to improve the diagnosis and management of non-malaria fevers in children under-5 years of age in Nanoro, Burkina Faso. Briefly, all children under-5 years of age documented with axillary temperature ≥37.5 °C presenting at the participating health facilities were invited to participate in the study. Written informed consent was obtained from parent/guardian before any data collection. All participants were tested systematically for malaria infection with RDT and managed according to the test result as per National Malaria Control Programme (NMCP) guidelines. In addition, expert malaria microscopy was performed for the purpose of studying the fever aetiology and the accuracy of the RDT-Pf  detecting PfHRP2 and this test was performed by trained study nurses at the health facilities or the district hospital. The nurses recorded malaria RDT results as positive or negative on study case record forms. During the last WHO-FIND testing round 6 the specificity and sensitivity for this particular test was reported to be high (>95%) [The malaria Rapid Diagnostic Test recommended by the Burkinabe NMCP is the SD Ag Bioline h (>95%) .P. falciparum and others Plasmodium species. Parasites densities were determined by counting the number of asexual parasites per 200 white blood cells, and calculating per μl of blood by assuming the number of white blood cells to be at 8000/μl. Thick blood smears were considered negative when the examination of 100 fields per thick film did not reveal the presence of any asexual parasites. Each blood slide was read by two independent expert readers, and in case of discordance  by a third independent reader whose conclusion was decisive. Positive microscopy results were recorded as the geometric means of the two reader’s results or the geometric means of the two geometrically closest reading in case of third reading. These results were expressed as asexual parasites per microlitre by using the patient’s white blood cell (WBC) count. A selection of slides (5%) was re-read by an independent expert microscopist for quality assurance.Malaria diagnosis by microscopy was performed by expert laboratory technicians at CRUN. These expert microscopists are frequently submitted to an external quality control programme and only certified microscopists are allowed to read the slides. The LoD of this expert microscopy 10 parasites/µl. Thick and thin blood smears were prepared (in duplicate) from blood collected in the Ethylene Diamine Tetra Acetic acid (EDTA) tubes. Thin films were fixed with methanol and blood slides were stained with 3% Giemsa solution (pH 7.2) for identification and quantification of asexual 2 for Sheep Blood agar and chocolate + isoVitalex agar. Isolates were identified by standard microbiological methods like described in Mackie and McCartney Practical Medical Microbiology [For blood cultures, 1–3 ml of venous blood was collected into a paediatric blood culture bottle  and incubated in a BACTEC 9050 instrument (Becton–Dickinson) for a total of 5 days according to the manufacturers’ protocol. If flagged for growth the cultures were Gram stained, sub-cultured on Eosin-Methylene Blue (EMB) agar, 5% Sheep Blood agar  and chocolate + isoVitalex agar, and incubated at 35–37 °C for 24 h in atmospheric condition for EMB and at COobiology  and bioc5 colonies forming units (CFU)/ml were regarded as yielding significant bacteriuria. A count of ≤105 CFU/ml was regarded as negative. Mixed growths  were regarded as contaminated and therefore disregarded. A second urine sample was not collected. Pathogen identification was done by standard microbiology biochemical methods .Urine culture was done when a urine sample was positive for leucocytes and nitrite as indicated by a urine dipstick . Urine was inoculated on CLED (Cystine Lactose Electrolyte Deficient) and EMB agar. The cultures were incubated at 37 °C during 24 h. Only samples that generated pure bacterial growth of more than 10Stool samples were specifically analysed for group A rotavirus using one step rotavirus and adenovirus serotype 40/41 in human feces test  as these pathogens are considered to cause fever.For the purpose of this study bacterial bloodstream infections (bBSI), viral gastro-intestinal infection (vGII) caused by rotavirus and adenovirus, and urinary tract infections (UTI) were considered as alternative cause of fever, different from malaria –22.Double entry of data was performed by two different persons by using OpenClinica software. The data analysis was done by using STATA 13. Description of qualitative and quantitative variables were performed by using proportion and mean or median, respectively. The geometric mean was used to express the parasite densities. The performance of RDT was evaluated compared to microscopy by calculating the sensitivity, the specificity, negative and positive predictive value of the RDT.To assess the influence of alternative causes of fever as defined for the purpose of this study and prior use of anti-malarials on the RDT performance, it was assumed that infection status and prior anti-malarial use was known before RDT testing and, therefore, a correction was done by removing all confirmed cases of bloodstream infections, urinary tract infections, viral gastro-intestinal infections and prior use of anti-malarials within 2 weeks from the analysis either separately or together.The rainy season was from July to November and dry season from December to June, and an analysis, done by season next to a whole year, was done on the results The Cohen’s Kappa coefficient was computed to assess to agreement between microscopy and RDT. p ≤ 0.05 was considered statistical significant.In total 1447 children under-5 years of age attending the peripheral health facilities or the CMA Saint Camille of Nanoro between January to December 2015 were screened. Of these children, 684 children under-5 years with axillary temperature ≥37.5 °C at presentation were enrolled in the study. One child was excluded at a later stage because the malaria RDT was not performed at enrolment. The baseline characteristics of the remaining 683 febrile children are summarized in Table PfHRP2 is reported in Table Plasmodium falciparum infection was diagnosed by microscopy in 49.8% (340/683) and by RDT-PfHRP2 in 69.5% (475/683) of the febrile children. The proportion of fever attributable to malaria as determined by expert microscopy was lower in the dry season  than in the rainy season . Out of the 475 febrile children with a positive RDT result, 29.7% (141/475) were found negative by expert malaria microscopy and thus considered RDT false positive. Stratifying for seasonality showed that RDT false positives were more prevalent during the dry season  compared to the rainy season . There were 2.9% (6/208) false negative cases; i.e. children positive by microscopy but negative by RDT.The diagnostic performance of the malaria RDT-PfHRP2 were 98.2% (334/340), 58.9% (202/343), 70.3% (334/475) and 97.1% (202/208), respectively  in the dry season than during the rainy season   and negative predictive value (NPV) of the RDT-re 98.2% 34/340, 5PfHRP2 false positive group, 35.6% (26/73) in malaria RDT-PfHRP2 true negative and 15.1% (11/73) in malaria RDT-PfHRP2 true positive group. The difference of alternative causes of fever between malaria RDT-PfHRP2 false positive group 25.53% (36/141) and malaria RDT-PfHRP2 true negative group 12.38% (26/202) was statistically significant (p = 0.002). It was also observed that there was no significant difference (p = 0.632) in geometric mean parasite densities between the true RDT malaria positive children either with  or without  an additional cause of fever.In the RDT malaria false positive group, 25.5% 36/141) of the children were found to have other causes of fever based on the laboratory findings (Table 1 of the In the true (by microscopy) malaria negative group, 12.9% (26/202) of the children were infected by pathogens that are known to cause fever and that were assessed in this study. Of the children that were confirmed to be positive for malaria by microscopy, only 3.3% 11/334) were co-infected with other causes of fever that were considered in this study , could explain the influence of the seasonality on the performance of the RDT-uggested .PfHRP2 cases did not have an actual malaria infection and that PfHRP2 is less specific during rainy season compared to dry season, which is in line with the study of Bisoffi et al. [The most important finding of the present study is thus the relative high number of malaria RDT false positive results found, if expert malaria microscopy is considered as golden standard. The number found in the present study is in line with those reported by Maltha et al. and Tinto et al. in the same study area , 23 and i et al.  and confOne of the generally accepted reasons for false positive RDT results is persisting antigen after adequate treatment or spontaneous remission . HoweverPfHRP2 used in the present study was ordered in the framework of the implemented programme for the management of malaria in the health district. The research team did not have any control over the transportation and storage conditions of the tests and there is a certain level of uncertainty if these might have affected test performance. Albertini et al. [Secondly, the RDT-i et al.  showed ti et al. –25.PfHRP2 is a real concern as found in this study and also reported in several studies [It should be noted that this study was designed to assess the performance of the RDT under actual field conditions and therefore the mentioned limitations are in fact a reflection of the real-life situation. The observation remains that the overestimation of malaria infections by  studies , 23–25 aPfHRP2 in many malaria endemic countries is based on test performance as reported by WHO panel studies for this RDT [PfHRP2 and it emphasizes the need to further assess the true aetiology of the  fever in the sick child with a specific attention to other infections. In the routine practice of CRUN, patients will first be asked for symptoms and submitted to clinical examination prior to doing a RDT and obviously if they have clear symptoms of pneumonia or urinary or gastro-intestinal infections these will be treated too even if a RDT is positive for malaria.The justification to choose for the implementation of a malaria RDT-this RDT .The WHO this RDT ). The prPfHRP2 positives cases were in fact malaria negative, as determined by microscopy, and these children received, in line with the NMCP and WHO malaria treatment guidelines, malaria treatment as their test was positive, but unnecessary , as they actually do not have the disease [It is important to note that the low specificity and PPV found in this study can negatively affect the clinical management of febrile cases. Almost 30% of the malaria RDT- disease  and mostPfHRP2. This could leave clinicians and health workers with a huge dilemma in the case of a malaria positive RDT, i.e. either providing immediately anti-malarials or first further investigate other possible causes of fever. In a recent study a proposition of performing a two-step RDT with PfHRP2 and Plasmodium Lactate Dehydrogenase (pLDH) was made to improve the specificity P. falciparum diagnosis in high transmission settings with little loss of sensitivity [Moreover, the poor PPV resulted in the misdiagnosis of the actual cause of febrile illness in around 30% of the children that were tested positive by RDT testing, but actually had another disease that caused their fever. Importantly, almost 50% of the alternative cause of fevers found in this study were actually diagnosed in the children that had false positive results with the RDT-sitivity . HRP2 poIt is also essential to emphasize that clinicians and health workers must be aware that if after anti-malaria treatment with adequate drugs the fever does not subside alternative causes of fever must be considered. In the present study it was found that 3.29% of the children that had a confirmed malaria infection, also had another infection that causes fever and these also need to be adequately treated.Prior anti-malarial treatment mainly concerned principally RDT false positive (and thus microscopy negative) and true negative cases. This finding shows that the anti-malarials prescribed in the study region  are highly efficient. Therefore, RDT positive cases with prior anti-malarial treatment (<3 weeks) are likely to be false positive, and clinicians and health works should thus be aware of this phenomenon and always thoroughly ask parents or guardians about previous intake use of drugs .The risk of having incorrect results by microscopy is in the present study very low. The microscopists who took part in the present study are submitted to regular certification programmes to ensure the quality of the malaria slide reading performed. Therefore, the persistence of HRP2 antigens detectable up to 3 weeks after successful anti-malarial treatment is considered as an important cause of the false positives .P. falciparum parasites having deletion(s) in the HRP2 gene yield false negative RDT results [The present study found only few false negative cases ; i.e. children positive by microscopy but negative by RDT. There is increasing concern that  results , 31. ThiPfHRP2 have a good sensitivity and negative predictive value, but their use in malaria endemic areas may result in missing true causes of fever mainly in the malaria false positive group. This puts a dilemma to clinicians and health workers that could be circumvented by using a second malaria RDT based on a different target, such as pLDH and/or using other simple diagnostic tests like urine and feces dipstick. In addition, the development of practical tool to screen the other causes of fever in malaria endemic area, should contribute to save live, but also to improve the performance of the malaria RDT view the few cases of co-infection of malaria with these other causes of fever.In conclusion, RDTs based on


The protective effect of insecticide-treated bed nets against individual-level malaria transmission is well known, however community-level effects are less understood. Protective effects from community-level bed net use against malaria transmission have been observed in clinical trials, however, the relationship is less clear outside of a controlled research setting. The objective of this research was to investigate the effect of community-level bed net use against malaria transmission outside of a bed net clinical trial setting in Lilongwe, Malawi following national efforts to scale-up ownership of long-lasting, insecticide-treated bed nets.Plasmodium falciparum presence. The percentage of people sleeping under a bed net within 400-m and 1-km radii of all participants was measured. Mixed effects logistic regression models were used to measure the relationship between malaria prevalence and surrounding bed net coverage. Each year, 800 people were enrolled .An annual, cross-sectional, household-randomized, malaria transmission intensity survey was conducted in Lilongwe, Malawi (2011–2013). Health, demographic, and geographic-location data were collected. Participant blood samples were tested for From 2011 to 2013, malaria prevalence declined from 12.9 to 5.6%, while bed net use increased from 53.8 to 78.6%. For every 1% increase in community bed net coverage, malaria prevalence decreased among children under 5 years old [adjusted odds ratio: 0.98 ]. Similar effects were observed in participants 5–19 years [unadjusted odds ratio: 0.98 ]; the effect was attenuated after adjusting for individual-level bed net use. Community coverage was not associated with malaria prevalence among adults ≥20 years. Supplemental analyses identified more pronounced indirect protective effects from community-level bed net use against malaria transmission among children under 5 years who were sleeping under a bed net [adjusted odds ratio: 0.97 ], compared to children who were not sleeping under a bed net [adjusted odds ratio: 0.99 ].Malawi’s efforts to scale up ownership of long-lasting, insecticide-treated bed nets are effective in increasing reported use. Increased community-level bed net coverage appears to provide additional protection against malaria transmission beyond individual use in a real-world context.The online version of this article (doi:10.1186/s12936-017-1767-2) contains supplementary material, which is available to authorized users. Insecticide-treated bed nets (ITNs) are an important part of the effort to control and eliminate malaria. In previous randomized controlled trials, ITNs decreased both the prevalence of malaria and all-cause mortality in children under 5 years old . HoweverPlasmodium falciparum prevalence is unclear, with a decrease [In Malawi, malaria control efforts have focused on scaling up ownership and use of ITNs and long-lasting, insecticide-treated bed nets (LLINs) that do not require retreatment . ITNs ardecrease , 7 and ndecrease , 9. The decrease .Bed net usage in a community may affect a person’s risk of malaria, regardless of individual use –15, as mP. falciparum prevalence, conducted between 2011 and 2013, in support of a multi-site Phase III trial (GSK MAL 055) of the candidate vaccine RTS,S/AS01 [The malaria transmission intensity (MTI) study was an annual cross-sectional survey of S,S/AS01 . HousehoField data collection was conducted in teams of three, which included two community health workers, and one nurse. Community health workers were trained to administer questionnaires and collect GPS coordinates of participating households. Field nurses were trained to administer a rapid diagnostic test (RDT) using SD Bioline HRP-2 Kits . The questionnaire, administered by the community health workers, captured demographic, health and behavioural information, including individual-level bed net use the previous night, household mosquito repellent use during the previous 7 days, and household indoor residual spraying during the previous 12 months. Participants were also asked to report the number of household members using a bed net while sleeping. Household characteristics, including wall, floor, roof, window material, and electricity, were also recorded. Household GPS coordinates were linked to each participant.During the interview, a field nurse conducted a finger prick and collected blood from each participant for a rapid diagnostic test (RDT) and microscopy. The RDT was performed to test participants for the presence of malaria parasitaemia in the field. A field nurse assessed the RDT and clinical status of a participant and provided immediate care and treatment in accordance with national guidelines, and referred the participant to the nearest health facility for treatment. Thick and thin blood smears were prepared. Slides were made in duplicate, and transported to the Area 18 health centre laboratory. For each slide, the presence of parasitaemia was determined independently by two trained microscopists. In the case of non-concordance, parasitaemia was determined by a third microscopist.ITNs were distributed to all participating households after completion of each annual survey.P. falciparum infection represented as a binary variable defined as the presence of any parasitaemia by light microscopy. An index variable representing household wealth was constructed using principal components analysis, and is a composite score of household characteristics including wall, floor, roof, window material, and electricity [The primary outcome for this study was ctricity . The comctricity .P. falciparum infection [Using the ‘buffer’ tool in ArcGIS 10.0, 400-m and 1-km radii were placed around each participant household. The intersect tool was used to identify households located within the 400-m and 1-km buffers, from which the total population and the total number of individuals sleeping under a bed net were calculated. The percentage of the study population sleeping under a bed net within each radius, excluding the individual participant was then calculated. Bed net use by close proximity neighbours can reduce individual risk of nfection , and comnfection . TherefoCommunity-level vaccine coverage was also measured to account for potential protective herd effects , 24. DatEuclidean distance  between household and the nearest body of standing water was also measured to capture potential exposure to mosquito breeding areas. Community bed net coverage, vaccine coverage, and distance variables were all constructed using ArcGIS version 10.0 software .Sample population characteristics were compared across the three survey periods using Pearson’s Chi square test for categorical variables and the Kruskal–Wallis test for ordinal variables.Spatiotemporal patterns of malaria prevalence and bed net use were examined using kernel density estimation. A roving window or kernel passes across the study area and computes the density of events within the spatial window. Density estimates are calculated at the window centroid and are based on the weighted values of all events in the window. Events are weighted according to distance from the centroid, with greater weight assigned to events near the centre of the window . Kernel Community-level bed net coverage (400-m and 1-km) between individuals with malaria and those without malaria was compared using a two-sample t test.P. falciparum infection was examined using mixed effects logistic regression to account for clustering of individuals within each survey period. Models were stratified by age group . Percentage bed net use among study participants within 400-m and 1-km radii were examined separately. Variables selected a priori included individual ITN use, age, and household wealth. The percentage of vaccinated persons living within 400-m and 1-km of participants were considered at a statistical significance level of p < 0.10. Additional variables considered at a statistical significance level of p < 0.10 included living within 1-km of a river or a large standing body of water, household commercial mosquito repellent use, and indoor residual spraying. Predictive margins were also plotted to examine the probability of P. falciparum infection given the percentage bed net coverage within 400-m and 1-km of each household.The relationship between community-level bed net coverage and This study was approved by the Institutional Review Boards at the University of North Carolina at Chapel Hill  and the National Health Sciences Research Committee, Lilongwe, Malawi. Study information was provided in both oral and written form to participants. Written consent was obtained from all participants and legal guardians.During 2011–2013, 2400 people  were enrolled. Fewer than 1.0% of participants were sampled in multiple periods. Overall, 8.8% (212) of participants tested positive for malaria  of participants reported sleeping under a bed net . As expected, malaria prevalence significantly decreased with individual bed net use  . The mixed effects logistic regression results measuring bed net use within 1-km were similar to the 400-m coverage models Table . The oddFor participants aged 5–19 years, the mean percentage of the population sleeping under a bed net was lower for those with malaria compared to those without malaria, both within a 400-m radius  and a 1-km radius . Individual bed net use had a significant protective effect in both the unadjusted and adjusted models Table . An incrThe mean percentage bed net coverage did not differ between adults with malaria and those without malaria within a 400-m radius  or a 1-km radius . In addition, neither individual bed net use nor community-level bed net coverage was associated with malaria  for all adults and children had community-wide benefits .The protective effects of community bed net use were most notable among children under 5 years sleeping under a bed net. While the observed effect size of community-level bed net coverage within 400-m in relation to malaria prevalence in children under 5 years sleeping under a bed net was small  to 2012 (28%) . The patIt is possible that additional malaria control efforts such as indoor residual spraying occurred simultaneously during the study period and may have influenced the study results, however most control efforts in Malawi focused on bed net distribution . In 2012The study area was located in a vaccine trial catchment area, and it is possible that the presence of the vaccine trial influenced bed net use behavior further impacting mosquito prevalence in the community. It was not possible to measure and evaluate these potential effects for this study. However, the percentage of vaccinated individuals living within 400-m and 1-km radii of study participant households were measured to account for possible protective vaccine herd effects , 24. TheThe similar prevalence observed between people sleeping under ITNs and those sleeping under untreated bed nets was surprising. These results are inconsistent with previous studies and may be due to inaccuracies in self-reporting of bed net type . AnotherThe findings of this study suggest that increasing levels of community bed net use can provide added protective benefits beyond individual use. With nearly 80% of the study population sleeping under a bed net in 2013, the results further suggest that Malawi’s efforts to increase bed net use and achieve universal coverage are effective . While bAdditional file 1. Mixed effects logistic regression results for children under 5 years stratified by bed net use.Additional file 2. Predicted margins with 95% confidence interval of Plasmodium falciparum infection in children <5 years old for per cent increase in bed net coverage within 400-m. a Children <5 years who sleep under a bed net; b children <5 years who do not sleep under a bed net.


Lao People Democratic Republic , a landlocked country in Southeast Asia, has made important progress in reducing malaria morbidity and mortality in the past 5–6 years, and the northern provinces have very low reported incidence. To support national progress towards elimination, it is critical to verify and understand these changes in disease burden.A two-stage cluster cross-sectional survey was conducted in four districts within four northern provinces . During September and October 2016, demographics and malaria risk factors were collected from a total of 1492 households. A total of 5085 persons consented to collection of blood samples for testing, by rapid diagnostic test (RDT) and polymerase chain reaction (PCR)-based testing. Risk factors for infection were examined using logistic regression; and a randomized subset of males was tested for glucose-6-phosphate dehydrogenase (G6PD) deficiencies using a combined PCR and sequencing approach.Plasmodium infections in 39  of 5082 analysable samples. The species distribution was Plasmodium vivax ; Plasmodium falciparum/P. vivax (5); P. falciparum (3), Plasmodium malariae (2), and P. vivax/P. malariae (1). In multivariable analysis, the main risk factors included having any other cases within the household ; and lack of bed net ownership within the household ; age, sex and forest-travel were not associated with parasitaemia. A total of 910 males were tested for the six most common G6PDd in SE Asia; and 30  had a G6PD variant allele associated with G6PD deficiency, with the majority being the Union (14) and Viangchan (11) polymorphisms, with smaller numbers of Canton and Mahidol.There were zero positives by RDT, and PCR detected Plasmodium infections by standard PCR methods, with P. vivax predominating in the surveyed districts. Clustering of cases within households, and lack of a bed nets suggest reactive case detection, and scale-up of coverage should be prioritized. The predominance of infections with P. vivax, combined with moderate levels of serious G6PD deficiencies highlight the need for careful rollout of primaquine towards elimination goals.This is the first rigorous PCR-based population survey for malaria infection in Northern Lao PDR, and found a very low prevalence of asymptomatic The online version of this article (10.1186/s12936-018-2367-5) contains supplementary material, which is available to authorized users. Plasmodium falciparum and Plasmodium vivax in northern areas by 2025, followed by elimination of all species nationwide by 2030 . This odds ratio is more than seven times what would be expected if infections were randomly allocated . Persons living within a household in the lowest wealth quartile, relative to the highest quartile, had increased risk for parasitaemia , which was attenuated from the univariate estimate . While not significant in univariate models , naming exposure to brochures or posters as a source of malaria knowledge was significant after covariate adjustment . One other factor showed marginal significance: having limited malaria knowledge  relative to having malaria knowledge , while any cases within the village not in the same household  was not significant.Age and sex were not significantly associated with parasitaemia in either univariate or adjusted models. While there was a significant association between parasitaemia and forest-going activities by any member of the household in univariate analysis , this was no longer a significant factor in the fully-adjusted model , potentially due to adjustment for wealth index.P. vivax mono-infections as the outcome  were largely consistent with overall results, with some important exceptions. Any forest-going by household members was a significant predictor of P. vivax infection, with an aOR of 3.40 ; and the presence of any other village-level cases was also significant, with an aOR of 4.93 ; age and sex remained not significant. Finally, presence of other cases within the household showed an increased association with parasitaemia with an aOR of 21.82 . This odds ratio also represents a biased estimate due to the low prevalence and should be interpreted with caution. This odds ratio is more than 12-fold higher what would be expected if infections were randomly allocated . In contrast, the finding of an association between forest-going and fections , 23 and fections .P. malariae infections in this survey have important implications, as the long extrinsic incubation period for this species implies the existence of long-lived vectors [P. knowlesi infections were identified in this survey. Human infections with P. knowlesi have been reported throughout the other GMS countries, but the species has only been reported in a single human sample from southern Lao PDR [While previously identified in Lao PDR  the P. m vectors , 27 in s Lao PDR .Anopheles spp. in villages relative to secondary forests , but with important differences by landscape type when examined by specific vector species [The increased risk of malaria from lack of any type of bed nets within households in this work is somewhat unexpected within the GMS, where effectiveness is limited or equivocal . Propose species . The inc species . FurtherP. falciparum infections. In that setting, age, sex, and forest-based exposures were not associated with parasitaemia, and the only significant predictor for parasitaemia  was the presence of any other cases within the household, with an aOR of 24.33  [P. vivax mono-infections, but neither age nor sex were significant for P. falciparum mono-infections. Overnight stays in the forest within the previous 3 months were also associated with being parasitaemic with P. vivax, but not for P. falciparum. This divergent epidemiology between the two species has also been identified in other settings, including Cambodia, Indonesia, and Papua New Guinea [PCR-based testing from samples collected in 2013 in southern Lao PDR (Savannakhet province) found predominately < 0.001)  found thw Guinea –37.P. vivax (currently in development), and field-based platforms  is consistent with other recent studies with Lao PDR. In Savannakhet, a higher-burden province, there were two febrile persons (≥ 37.5 °C) among 888 participants  . These fod, LAMP ) should od, LAMP .P. vivax. While earlier schemes listed these variants as only moderate deficiencies (WHO class II or III), this classification may be problematic [There are limited data on G6PD deficiencies in Lao PDR, and the moderate levels of G6PD variants associated to G6PDd in males, consistent with other areas in the GMS , will stblematic , and theblematic . FinallyThis study suggests that malaria testing rates in public facilities may be sub-optimal . TestingP. vivax, where gametocytes are present in the earliest stages of infection [P. vivax infection at survey, as did another member of the same household.While RDT-based testing and subsequent treatment are free at all public health facilities in Lao PDR, the costs associated with care seeking were reported in this survey to be important barriers to early diagnosis and treatment. Delays in care-seeking of even a single day may provide opportunities for onward transmission of nfection . Indeed,Taken in summary, the findings from this survey suggest that expansion of several programmatic activities could have important epidemiological impacts. Specifically, case-based surveillance and response strategies should be rapidly implemented, and are especially feasible given the very low malaria case burden. To target vectors and sub-clinical malaria cases within households, a locally-appropriate variation of China’s “1,3,7” programme, aligned with the difficult terrain and access in Northern Lao PDR, should be considered . MoreoveP. vivax-only parasitaemia each represent substantial evidence for clustering of cases within households, as cases are overdispersed [This study is not without limitations. Firstly, the sampled districts may not be fully representative of all transmission settings in northern areas or within other provinces in northern Lao PDR. Important variation may exist, especially in light of the low prevalence by PCR. Secondly, although there were strenuous efforts to capture blood samples from all enumerated household members, some age groups were underrepresented, and could be parasite reservoirs in this population. Beyond producing wide confidence intervals for odds ratios, models based upon the limited number of PCR-confirmed infections also have the potential to produce biased point estimates , but theispersed .The Northern provinces of Lao PDR have made important progress in reducing the incidence of all malaria species in the past decade, but some areas of continued transmission remain, which will require targeted interventions towards sub-national elimination targets. The low parasite burden highlights the rapid feasibility of sub-national elimination, but some programmatic challenges remain.Targeting of interventions to highest-risk groups is essential as malaria burdens decrease to maximize the impact of inherently limited funding within the health sector. The findings from this study suggest that assumptions about adult males with forest- or field-based work exposures being the primary risk group should be reexamined, as cases were found equally in all demographics.Moreover, reactive case detection focused on household members of an index case may be a useful strategy, especially using sensitive analytical methods or mass test and treat of household contacts. Potential gaps in early diagnosis and treatment suggest that successful programming will also require addressing delays in care-seeking, including low reported facility-level testing rates, and towards increased net coverage. These in turn will require expansion of supportive supervision at provincial- and district-levels to promote consistent implementation. Attacking the substantial vivax hypnozoite reservoir will require routine G6PDd testing in a population having moderate levels of deficiencies, followed by consistent and complete primaquine treatment. In this context, the benefits of well-support village health workers should be considered in addressing many identified gaps in early diagnosis and treatment within northern Lao PDR for accelerated progress , 49.Additional file 1. Detailed population characteristics, malaria parasite and risk-factor survey, Northern Lao PDR .Additional file 2. Malaria early diagnosis and treatment (EDAT) cascade for self-reported febrile illness, Northern Lao PDR.Additional file 3. Multivariable Firth penalized-likelihood logistic model for PCR-based malaria parasite positivity , Northern Lao PDR .Additional file 4. Sensitivity analysis for the odds ratios, risk of parasitaemia with “any other case in household.”


Plasmodium parasites. To determine RBC infection rate, which is essential for malaria study and diagnosis, microscopic evaluation of Giemsa-stained thin blood smears on glass slides (‘Giemsa microscopy’) has been performed as the accepted gold standard for over 100 years. However, only a small area of the blood smear provides a monolayer of RBCs suitable for determination of infection rate, which is one of the major reasons for the low parasite detection rate by Giemsa microscopy. In addition, because Giemsa microscopy is exacting and time-consuming, automated counting of infection rates is highly desirable.Malaria is a red blood cell (RBC) infection caused by A method that allows for microscopic examination of Giemsa-stained cells spread in a monolayer on almost the whole surface of hydrophilic-treated cyclic olefin copolymer (COC) plates was established. Because wide-range Giemsa microscopy can be performed on a hydrophilic-treated plate, the method may enable more reliable diagnosis of malaria in patients with low parasitaemia burden. Furthermore, the number of RBCs and parasites stained with a fluorescent nuclear staining dye could be counted automatically with a software tool, without Giemsa staining. As a result, researchers studying malaria may calculate the infection rate easily, rapidly, and accurately even in low parasitaemia.Because the running cost of these methods is very low and they do not involve complicated techniques, the use of hydrophilic COC plates may contribute to improved and more accurate diagnosis and research of malaria.The online version of this article (doi:10.1186/s12936-017-1975-9) contains supplementary material, which is available to authorized users. Plasmodium spp. cells in red blood cells (RBCs), is a commonly used parameter in malaria diagnosis. Since 1904, microscopic examination of thick and thin Giemsa-stained blood films  has been the gold standard for malaria diagnosis [Parasitaemia, the count of iagnosis . Becauseiagnosis , and diaA rapid diagnostic test (RDT) or polymerase chain reaction (PCR)-based diagnosis are conventionally performed for malaria. RDT immunologically detects the malarial antigen in a simple manner with a detection limit similar to that of Giemsa microscopy –6. HowevPlasmodium parasites, stained with a fluorescent nuclear staining dye, on hydrophilic-treated plates by employing an image software analysis tool instead of Giemsa staining and microscopic examination was reported.The procedure for Giemsa microscopy consists of the following steps: preparation of a thin blood smear, fixation and staining of the smear, and microscopic observation of the parasites in RBCs. For quantification of parasitaemia, a monolayer region of the blood smear, where RBCs are sparsely distributed, is examined. This ensures identification and accurate counting of the parasites. However, although skilled technicians prepare the blood smears, only a small proportion of the smear will become a monolayer, thereby severely limiting the area (and number of RBCs) available for analysis. The low sensitivity of this method is its main disadvantage . A methoPlasmodium falciparum strain 3D7 was cultured as previously described [2EDTA) . Giemsa microscopy was also performed as described earlier [escribed . Blood f earlier . For autPlastic plates (25 × 75 mm) made of cyclic olefin copolymer  were rendered hydrophilic by reactive ion-etching treatment using a SAMCO RIE system  –13. The t test.Statistical analysis was performed with SigmaPlot ver. 12  using a Student’s P. falciparum-infected RBCs (1% parasitaemia) diluted to 1% of haematocrit with RPMI1640 medium were dropped onto the hydrophilic-treated COC plates. The plates were then left undisturbed for 10 min to allow the RBCs to settle and adhere onto the plate  composed of plastic, allowing 10 min for the RBCs to settle and adhere to the COC plate . The fluorescence signal intensity of the reticulocytes stained with SYTO21  was much weaker and larger in size than that of the parasites. Because the signals corresponding to reticulocytes were omitted in the analysis using MetaMorph software, reticulocytes did not show false-positive results. Howell–Jolly bodies were not observed in this study. It required less than 1 min to perform the automated counting. Taken together, these data indicate that accurate automated RBC counting can be performed easily and quickly with the hydrophilic-treated COC plate surfaces and MetaMorph Offline software.Figure Plasmodium-infected RBCs on hydrophilic-treated COC plates was attempted. Since, unlike parasites, RBCs do not have nuclei, it is possible to detect parasite-infected RBCs by nuclear staining. SYTO21, a cell-permeant green fluorescent dye, was used for staining of the parasite nucleic acids. The parasite-infected RBCs, suspended in the medium containing SYTO21, were added to hydrophilic-treated plates, followed by staining for 10 min and removal of non-adherent RBCs. Non-synchronized parasites, in which more than 60% of the parasites were in the ring stage and whose fluorescence signals were weaker than those of parasites in other stages, were used in this study. Figure Plasmodium nuclei stained with SYTO21 were detected (arrows). The signals were not identified in uninfected RBCs  were analysed by Giemsa microscopy and the automated counting technique to compare the two counting methods . These results indicate that automated counting of the parasite infection rate is possible without preparation of a thin blood smear, Giemsa staining, or microscopic observation.Automated counting of the detected fluorescence signals was possible using the MetaMorph Offline software, and the automated counting was performed with Integrate Morphometry Analysis . When the data obtained were combined with the number of RBCs automatically counted as described in Fig. Plasmodium detection is poor. In this study, the method for preparing RBC monolayers for Giemsa microscopy was improved. The number of RBCs available for analysis, which formed a monolayer and were sparsely distributed, was significantly higher on the hydrophilic-treated COC plates than on conventional glass slides. Interestingly, Le et al. [Giemsa microscopy has been the gold standard for malaria diagnosis for more than 100 years. Since the area of the blood smear on the glass slide wherein the RBCs are in a monolayer is quite small, the sensitivity of e et al.  reportedFurthermore, a method for automated counting of parasite-infected cells without Giemsa staining using hydrophilic-treated COC plates are developed. Calculation of the infection rate is essential to cultivate or investigate the parasite, but this is laborious and time-consuming work. Further, operators have to practice the conventional method extensively for accurate infection rate calculation. The running cost of the automated counting method is very low (about 0.3 USD per COC plate). When large plastic frame(s) for applying RBCs are employed, huge numbers of RBCs on a plate can be analysed. In contrast, because some smaller frames can be placed on a plate, certain significant conditions (drug concentration or reaction time) can be analysed on the plate, which might be useful for screening of new drug candidates. Leucocytes containing nuclei could interfere with the determination of parasitaemia in patients with malaria. However, because the size of the leucocyte nuclei is greater than that of the parasite nuclei, these can be distinguished using the MetaMorph Offline software after detection of SYTO21 signals. Furthermore, over 99.9% of leucocytes can be removed with a push column in fieldwork situations . TherefoConducting automated infection rate counting with SYTO21 may not be practical. Fluorescence microscopy is costly, a freezing system is required to maintain SYTO21 stability, and a purchase route for reagents is required. Researchers in laboratories with access to this equipment can quickly calculate parasitic infection rates at a low cost. In contrast, Giemsa microscopy can be performed on hydrophilic-treated plates and requires a power supply for a hair dryer, making this method suitable for field settings. Because approximately 20 min are required to prepare a plate with a Giemsa-stained RBC monolayer, the method can be performed at the point-of-care. Previously, hydrophilic-treated plates were transported to an endemic country  in high temperature and humidity environments. The samples remained stable for more than 2 weeks. Further, because this method uses quick drying with a hair dryer, the risk of contamination with patient blood is reduced and diagnosis can be safely conducted.Taken together, hydrophilic-treated COC plate surfaces can be used not only for wide-range analysis by Giemsa microscopy, but also for automated and accurate infection rate counting without Giemsa staining.