Plasmodium vivax. This indicates that RMOD could be useful in P. vivax dominated elimination settings. Parasite density correlates well with the quantitative magneto-optical signal. Importantly, residual hemozoin present in malaria-negative patients is also detectable by RMOD, indicating its ability to detect previous infections. This could be exploited to reveal transmission hotspots in low-transmission settings.Improved methods for malaria diagnosis are urgently needed. Here, we evaluate a novel method named rotating-crystal magneto-optical detection (RMOD) in 956 suspected malaria patients in Papua New Guinea. RMOD tests can be conducted within minutes and at low cost. We systematically evaluate the capability of RMOD to detect infections by directly comparing it with expert light microscopy, rapid diagnostic tests and polymerase chain reaction on capillary blood samples. We show that compared to light microscopy, RMOD exhibits 82% sensitivity and 84% specificity to detect any malaria infection and 87% sensitivity and 88% specificity to detect  Here Arndt et al. establish rotating-crystal magneto-optical detection (RMOD) as a near-point-of-care diagnostic tool for malaria detection and report a sensitivity and specificity of 82% and 84%, respectively, as validated by analyzing a clinical population in a high transmission setting in Papua New Guinea. Development of rapid, easy-to-use and low-cost malaria diagnostic methods, with high sensitivity and specificity, remains an urgent priority in tropical diseases research3. Currently available methods include the inspection of blood smears using light microscopy (LM), rapid diagnostic tests (RDTs), and molecular methods, such as polymerase chain reaction (PCR) or other molecular techniques. These techniques rely on different diagnostic targets, namely the direct observation of infected red blood cells (LM), detection of parasite antigens (RDT), or DNA/RNA (using PCR or other molecular techniques).Humans have suffered from malaria for thousands of years and still, hundreds of millions of people are infected each year. Nowadays, malaria also places a significant social and economic burden on many tropical developing countries, further undermining the potential for growthPlasmodium parasites is a striking and well-described biophysical phenomenon, arising from the metabolism of hemoglobin6. Normally, oxygen-bound hemoglobin is a diamagnetic substance with a magnetic susceptibility close to that of water7. During infection of RBCs, Plasmodium parasites break down hemoglobin in their digestive vacuoles and heme molecules liberated in the process are assembled into iron-containing organic crystallites called hemozoin11. These hemozoin crystals are one of the most distinguishing features of Plasmodium infection in peripheral blood and played a vital role in identifying Plasmodium parasites as the cause of malaria and the mosquito as the agent of transmission in the late 19th century13. During the process of hemozoin formation, hemoglobin iron is oxidized and concentrated to make up about 10% of the mass of the newly formed hemozoin crystals, resulting in an overall paramagnetic behavior of hemozoin4. As such, hemozoin is an intrinsic biomagnetic marker of infection with Plasmodium. While the hemozoin crystals are not excreted naturally by the infected cells until cell rupture, they can easily be made accessible for diagnostic purposes by lysing blood.Researchers have also been fascinated by the magnetic properties of malaria-infected red blood cells (RBCs) for a long time, since using an inherent and unique physical property such as malaria parasite-induced RBC magnetism, may enable rapid and easy diagnosis at low cost. The increased magnetic susceptibility of RBCs infected with 28 and some of these techniques showed promise under laboratory conditions. However, only a few magneto-optical (MO) methods have been tested in operational settings in malaria endemic countries or with samples collected from malaria-infected patients in endemic countries. A promising concept for hemozoin-based malaria diagnosis was described by Newman and colleagues in 200818. This applicability of the method was demonstrated using synthetic hemozoin (β-hematin) samples, but the ability to detect infections in a set of LM-confirmed patient samples under laboratory conditions, was considered requiring further development16. Building upon this concept, over recent years, we developed a novel diagnostic technique, named rotating-crystal magneto-optical detection (RMOD). As detailed in refs. 26, the main conceptual improvements were (i) synchronous magnetic rotation of the hemozoin crystals using an array of permanent magnets, (ii) application of a circularly polarized incoming laser beam to maximize the MO signal and to avoid contributions from components other than hemozoin, and (iii) highly efficient detection of the MO signal originating from hemozoin by a balanced photodetection scheme combined with lock-in filtering. With these improvements, we showed that RMOD can detect hemozoin in very small concentrations of a few ppm. Furthermore, we demonstrated that hemozoin can be detected in lysed blood with very high sensitivity in the low ng/µL range using RMOD26. Measurements on parasite cultures indicated that RMOD had a limit of detection (LOD) of ∼10 parasites per µL of blood in samples spiked with P. falciparum26. These promising results were further supported by studies on P. berghei and P. yoelii-infected mice24. On an operational level, RMOD is promising as it can be conducted after a short training and provide test results within minutes. From a funding perspective, since no expensive reagents are used, the per-sample measurement cost is very low.Several approaches to exploit these magnetic properties for diagnostic purposes have been proposed29. Many mechanisms and intricacies of parasite biology and human response to infection may collectively determine the actual quantity of hemozoin in peripheral blood. For example, infected RBCs are cleared mostly in the liver and spleen, and consequently these organs become loaded with hemozoin31. Leukocytes phagocytose infected RBCs and ingest hemozoin33. Late parasite stages of P. falciparum containing large quantities of hemozoin sequester in the capillaries34, whereas a higher proportion of late stages of P. vivax continues to circulate in peripheral blood. Gametocytes of P. falciparum contain large amounts of hemozoin and circulate for an extended period of time after an infection has been cleared or treated36. While many aspects of hemozoin clearance and redistribution in the human body are yet to be elucidated, there is evidence for long-term persistence of hemozoin in body tissues of people living in endemic areas37.The dynamics of hemozoin accumulation and clearance in natural malaria infections in the human body are more complex than what can be mimicked in model systems, and intermediate redistribution and final fate of hemozoin during and following malaria infections are not well-understoodP. falciparum and P. vivax38. Using a RMOD prototype device similar to that described in our previous studies26, we systematically compared RMOD performance to conventional diagnostic techniques, namely expert LM, RDT, and PCR.In order to account for these complexities, which are potentially relevant to hemozoin-based malaria diagnosis, we conducted a detailed evaluation of RMOD on almost 1000 suspected malaria cases in Madang, Papua New Guinea (PNG). PNG has a complex malaria epidemiology and the study area exhibits high transmission intensities for both, 42, and a schematic illustration of the RMOD measurement principle  is included as Supplementary Table P. falciparum R2 = 0.79; p < 0.0001; P. vivax: R2 = 0.71; p < 0.0001). A correlation plot is shown in Supplementary Fig. For the quantitative methods, LM and PCR, parasite density and gene copy number correlated well . A detailed summary of the RMOD results compared to the other methods  is shown in Fig. The median overall magneto-optical signals for LM positive and LM negative samples were 23.0 mV/V and 1.7 mV/V, respectively. For the RDT positive and negative samples the median MO signals were 15.1 mV/V and 1.7 mV/V, respectively. For PCR positive and negative samples the median MO signals were 16.4 mV/V and 1.7 mV/V, respectively. For all three methods, the differences in the median MO signals for positive and negative samples were highly statistically significant  is two orders of magnitude smaller than the dynamic range of the methodology defined as the difference between the median MO signal of the LM negative and LM positive population. The distribution of the standard deviations of the MO signals, as determined from measurements of triplicates, is presented for the whole sample set in Supplementary Fig. Since RMOD provides a quantitative measurement of hemozoin content in the blood sample and the detected MO signals are continuous, receiver operating characteristic (ROC) analyses were conducted to determine the cut-off MO signals corresponding to maximum sensitivity and specificity to detect infection per se, as well as infection with specific parasite species.Sensitivity and specificity were determined by selecting the minimum distance from the ROC curve to the  coordinate indicating 100% sensitivity and specificity. The cut-off values and resulting indicators of agreement between methods are presented in Table Plasmodium infection were 82% and 84%, respectively, and the optimal cut-off value to distinguish between infections and non-infections was 4.19 mV/V. The overall agreement between LM and MO was classified as substantial (κ = 0.64)43. Sensitivity and specificity increased for P. vivax infections (incl. mixed infections) to 87% and 88%, respectively. When based on PCR as a reference method, overall sensitivity was 78% and overall specificity was 78%. The overall agreement between PCR and MO was classified as moderate (κ = 0.54). When RDT was used as the reference method, sensitivity was 76% and specificity was 83% with an overall agreement classified as moderate-to-substantial (κ = 0.58).In summary, when based on expert LM as reference standard, ROC analysis indicated that maximum sensitivity and specificity of RMOD for the detection of any P. vivax infections than the CareStart® RDT (90% vs. 77%) but less P. falciparum infections (78% vs. 92%).Using expert LM as the main reference method, we found that RMOD detected a higher proportion of One has to keep in mind, that none of the methods used for comparison is a perfect standard, as they are all subject to systematic and stochastic errors. In fact, we will discuss the data obtained for a considerable set of patients later, where RMOD may have detected low-level infections that were not detected by the other methods.P. falciparum-infected samples resulted in lower MO values as compared to P. vivax-infected samples with similar parasite density. P. falciparum gametocyte-containing samples formed a characteristic sub-population that, on average, exhibited higher MO signals at a similar parasite density when compared with samples containing only P. falciparum asexual stages. The correlation of MO signals with parasite density was better for P. vivax  than for P. falciparum .Parasite density as determined by LM correlated well with the MO signals as shown in Fig. 44. However, we also observed considerable MO signal scatter within the sample population, which tested negative with all diagnostic methods used for comparison , and patients in this group exhibited, on average, higher MO signals than expected from our previous studies26.Despite the clear correlation of MO signal and parasite density as determined by LM, we observed a considerable scatter of the MO signal at a given parasite density. This is natural, as the MO signal depends not only on the density of the parasites but also on the hemozoin content of the parasites, determined by their developmental stage. This alone can explain a considerable variation of the MO signal at any parasite densityn = 32), as shown in Fig. In addition, the median MO signals in the malaria negative population were statistically significantly higher (more than double) than those measured in a smaller sample set of malaria naïve or long-term malaria-free volunteers . This implies that either (i) RMOD detects low-level infections that are not detected by the other methods or (ii) there is a higher residual hemozoin level in populations that are more frequently infected with Plasmodium.This hypothesis is further substantiated by the observation that MO signals in the malaria negative (by LM and RDT and PCR) sub-population were highly correlated with malaria positivity rate in the overall population (as determined by LM), when both populations were stratified by age .Evidence that the probability for hemozoin to be present in leukocytes in malaria negative patients is higher for samples with high MO signals is shown in Fig. 45. Malaria diagnosis is complicated by many factors, including the frequent occurrence of asymptomatic infections with low parasite density46.Improving malaria diagnosis in support of malaria control and elimination, especially through the development of methods applicable in resource-limited settings is important and timelyP. falciparum and P. vivax are common47. In order to evaluate the performance of RMOD, we conducted a comparison with various conventional diagnostic methods, namely expert LM, RDT, and PCR.In this study, we tested a magneto-optical method, namely RMOD, for automated and rapid measurement of magnetically induced linear dichroism of hemozoin in close to 1000 human blood samples from suspected malaria patients in a high-transmission area of Papua New Guinea (PNG) where both RMOD may offer advantages over existing methods in terms of rapidness and cost. While the measurement itself only takes a few seconds, sample preparation and handling are still in the order of minutes. As such, a time-to-result of around 10 min is within reach of the technique. RMOD also has the potential to be cost-competitive. The cost of a prototype as used in the present study is similar to that of a standard light microscope and the cost-per sample is very low as the method is almost reagent-free see Fig. .43. Hemozoin-containing trophozoite and schizont stages are known to sequester less frequently in P. vivax than in P. falciparum infections, resulting in a higher proportion of these stages present in peripheral blood during P. vivax infection49. Consequently, we observed approximately 10-fold higher average MO signals for P. vivax as compared to P. falciparum  at similar parasite densities  presence  of late P.f. stages in peripheral blood50; (ii) presence of P.f. gametocytes; (iii) the presence of ‘free hemozoin’ released by rupture of sequestered parasites and (iv) the fact that some hemozoin is produced at the ring stage. Our very recent RMOD study, quantifying the hemozoin production during the life cycle of P. falciparum parasites shows that ~20% of the hemozoin is produced during ring-stage development44.As such, our data hint towards RMOD working ‘better’ for 26. This led to a seemingly decreased diagnostic performance. The most plausible hypothesis to explain this observation is that a considerable proportion of the patients had hemozoin in their peripheral blood at levels still detectable by RMOD, yet in the absence of an infection detectable by any of the methods used for comparison.While MO signals were significantly correlated with parasite density, the scatter of MO signals in the malaria negative population  together with the distribution of MO signals from samples that were positive for P. vivax by expert LM in the present study (n = 124) in a ROC analysis. This resulted in an expected sensitivity of 97% and specificity of 97%, together with a near perfect agreement between LM and RMOD techniques, with κ = 0.91. Furthermore, an analogous calculation for the P. falciparum samples (n = 213) also resulted in 97% sensitivity and 97% specificity with κ = 0.87.It is likely that in low-transmission and/or elimination settings, which many countries are currently working towards, the residual hemozoin level in the population will be lower, and the background MO signal should approach that measured for long-term malaria-free and malaria-naïve volunteer samples. This would lead to an increase in the ability of RMOD to discriminate infections in these settings. In order to estimate the magnitude of improvement, to be expected when lowering the MO signal threshold to the level observed in long-term malaria-free and malaria naïve-individuals, we used the distribution of MO signals obtained from these samples  with 60% sensitivity and 97% specificity.In the current state of development, RMOD cannot distinguish between parasite species in 60 to detect ultra-low density infections and relate their presence to RMOD measurement outcomes.While the results of the present study illustrate the potential of RMOD and hemozoin-based malaria diagnosis, they also pose new questions. Future studies are required to further investigate how residual hemozoin levels in different transmission intensity settings, and longitudinal hemozoin dynamics in infected and treated individuals influence RMOD measurement outcomes. It is especially worthwhile considering and further exploring the usefulness of RMOD-based hemozoin detection for malaria diagnosis and in epidemiological studies in low-transmission and elimination settings. The PCR method employed in this study did not achieve an optimal LOD and should thus not be considered as a molecular gold standard. Future studies should include high-volume, ultrasensitive molecular techniquesThe current prototype device was deliberately kept flexible so that measurement parameters could be adjusted and optimized. This makes the operation more complex than what we would envision for a finalized diagnostic product, which would focus on ease of use, standardization, and high throughput. For such a final product, we would envision the operation to be very simple at the ‘push of a button’, without requiring any compromise on the present diagnostic performance, which is similar to that of LM.P. vivax infections and it can be expected that P. vivax will represent the vast majority of infections in the malaria end-game outside of Africa61. Given the rapid and low-cost measurement possible with RMOD and the promising results in particular for P. vivax, the method may play a beneficial role in such settings. Since hemozoin is an intrinsic biomarker of Plasmodium spp. infection that persists in peripheral blood  it may be worth investigating in how far RMOD can be used as a tool to detect transmission hotspots in elimination settings.Many countries in low-transmission or elimination settings experience an increase in the proportion of P. falciparum and P. vivax are highly endemic, and P. malaria and P. ovale are also present in the study area38. Capillary blood samples were collected by qualified nurses or community health workers at Yagaum Rural Hospital located outside of Madang and at Madang Town Clinic in 2017–2019.Madang is located on the north coast of Papua New Guinea Fig. . P. falc® Malaria, Accessbio Inc., USA) and two blood slides for LM were prepared at enrollment. All RDT positive patients received standard antimalarial treatment according to PNG malaria treatment guidelines. This study received ethical clearance by the PNG Institute of Medical Research (PNGIMR) Institutional Review Board and the PNG Medical Research Advisory Committee .Blood samples originated from suspected malaria cases presenting as outpatients at the respective clinics. An RDT  before being declared Plasmodium-negative. Parasite density was calculated from the number of parasites per 200–500 leukocytes (depending on parasite density) and an assumed leukocyte density of 8000 μL−1 63. Slides discrepant for positivity/negativity, species determination, or density (>2 log difference) were adjudicated by a WHO-certified level 1 (expert) microscopist. Slides were scored as LM positive for an individual Plasmodium species if the species was detected independently by at least two microscopists. Densities were calculated as the geometric mean densities of all positive reads47.LM was conducted by the PNGIMR microscopy unit consisting of experienced, WHO-certified microscopists. Slides were read, and parasite density determined according to standard WHO guidelines for malaria LM using thick blood smears for parasite density quantificationPlasmodium 18S rRNA genes. Briefly, a screening PCR to exclude negative samples was first run on all samples64. Samples that were positive by the screening PCR were then subjected to a species-specific quantitative real-time PCR (qPCR) as described elsewhere using a CFX96 Touch qPCR system 65. Therefore, it was possible to quantify parasite density based on gene copy number. For all reactions, 4 µL of the DNA eluate was used, corresponding to DNA material from roughly 26.7 µL of the original blood sample. Primer sequences and thermocycling conditions are provided in Supplementary Information Tables DNA extraction was performed on 200 µL of whole blood using DNA extraction kits for 96 well plates . DNA was eluted in 30 µL of RNAse/DNAse free water. The present study employed a two-step PCR protocol as described previously using molecular probes targeting 26. The working principle is depicted in Fig. 57. Here, we refer to this effect as the magneto-optical (MO) signal, which is the marker-signal for hemozoin detection and quantification25.The concept of the rotating-crystal magneto-optical setup and the underlying physical principles of hemozoin detection are described in detail in our former studiesFor the preparation of the blood lysates, 35 µL of whole blood was mixed with 315 µL of lysis solution (13.3 mM of NaOH and 0.03% v/v of Triton X-100 in distilled water) and allowed to stand for at least 10 min to ensure complete lysis. Thereafter, 280 µL of the lysate was transferred into the optical sample holders and measurements were performed without further delay. Samples for RMOD measurements were prepared in triplicate per blood sample.B ~ 1 T) at the sample position. This magnetic field induces the co-alignment of the hemozoin crystals, and when the magnetic ring is rotated, the co-aligned hemozoin crystals follow this rotation. During the measurement, polarized light from a laser diode is transmitted through the sample in the direction perpendicular to the plane of rotation of the magnetic field. The rotation of the co-aligned dichroic crystals gives rise to a periodic change in the detected intensity. The modulated intensity, divided by the average intensity, corresponds to the measured ‘MO signal’, which is displayed in the corresponding figures in mV/V units24.The hemolysed blood sample, transferred into a cylindrical sample holder, is inserted into the center of a ring-shaped assembly of permanent magnets, which creates a strong uniform magnetic field (n = 943), but n = 22 samples were frozen overnight before preparation and MO measurement due to logistical constraints. The measurement of a single sample took approximately 3–5 min  using standardized data collection forms and into Microsoft Excel 2016 (Microsoft Corporation) spreadsheets. Data analysis and graphing were conducted using Microsoft Excel 2016 (Microsoft Corporation), Graphpad Prism 8.0 (Graph Pad Software), and Stata 13 (StataCorp). No customized computer codes were used.66. Continuous data are presented as averages  for normally distributed data and medians with interquartile range or range for not normally distributed data.Proportions are presented alongside their exact 95% confidence intervals67. Receiver operating characteristic (ROC) analyses were used to determine the cut-offs for the continuous RMOD data to best predict presence or absence of infection, i.e., to determine sensitivity and specificity by calculating the minimum distance between the ROC curve and the  coordinate indicating 100% sensitivity and 100% specificity68.LM, PCR, and RDT results were used to compare against RMOD results. Following the recommendation of WHO, LM was used as the main reference method. Methods were compared by calculating the sensitivity and specificity, predictive values, and agreement (κ) with respect to the reference methodFurther information on research design is available in the Supplementary InformationReporting Summary


Long-lasting insecticidal nets (LLINs) are the most widely deployed vector control intervention in sub-Saharan Africa to prevent malaria. Recent reports indicate selection of pyrethroid insecticide resistance is widespread in mosquito vectors. This paper explores risk factors associated with malaria infection prevalence and vector density between mass distribution campaigns, changes in net coverage, and loss of protection in an area of high pyrethroid resistance in Northwest Tanzania.Plasmodium falciparum circumsporozoite protein. Logistic regression was used to identify household and environmental factors associated with malaria infection and regression binomial negative for vector density.A cross sectional malaria survey of 3456 children was undertaken in 2014 in Muleba district, Kagera region west of Lake Victoria. Vector density was assessed using indoor light traps and outdoor tent traps. Anophelines were identified to species using PCR and tested for Anopheles funestus and 95.4% Anopheles gambiae of which 4.5% were Anopheles arabiensis and 93.5% were Anopheles gambiae sensu stricto.LLIN use was 27.7%. Only 16.9% of households had sufficient nets to cover all sleeping places. Malaria infection was independently associated with access to LLINs . LLINs less than 2 years old were slightly more protective than older LLINs ; however, there was no evidence that LLINs in good condition (hole index < 65) were more protective than LLINs, which were more holed. Other risk factors for malaria infection were age, group, altitude and house construction quality. Independent risk factors for vector density were consistent with malaria outcomes and included altitude, wind, livestock, house quality, open eaves and LLIN usage. Indoor collections comprised 4.6% Three years after the mass distribution campaign and despite top-ups, LLIN usage had declined considerably. While children living in households with access to LLINs were at lower risk of malaria, infection prevalence remained high even among users of LLINs in good condition. While effort should be made to maintain high coverage between campaigns, distribution of standard pyrethroid-only LLINs appears insufficient to prevent malaria transmission in this area of intense pyrethroid resistance. Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the main vector control interventions deployed in sub-Saharan Africa to control malaria . AccordiInsecticide-treated nets (ITNs) that required annual re-treatment were first distributed to pregnant women and infants through antenatal clinics in 2004. In 2008, LLINs that did not require re-treatment were distributed through mass campaigns targeting children under five years of age .ITNs are the most effective when usage is high to provide community protection . The chaThe gains arising from increased usage of LLINs might also be undermined by the development of insecticide resistance among malaria vectors . ResistaThis study explored LLIN coverage indicators three years after the universal coverage campaign of 2011 and whether standard pyrethroid-only LLINs still provide protection against malaria vectors and infection prevalence in an area of intense pyrethroid resistance in Northwest Tanzania. It also explored other household and individual risk factors for malaria infection and vector density.2, 29,000 households and an estimated population of 135,000 and is situated between 1100 and 1600 m above sea level [Cross sectional prevalence and entomological surveys were conducted during baseline of a cluster randomized controlled trial (RCT) assessing PBO LLINs and IRS with Actellic CS® (pirimiphos methyl) . The stuea level . There aea level .Anopheles gambiae sensu stricto (s.s.) resistant to pyrethroids and Anopheles arabiensis were the only vectors found in 2011 [Anopheles gambiae and 54.5% for Anopheles funestus and a resistance intensity of 38 fold for Anopheles gambiae sensu lato (s.l.) and 34 fold for Anopheles funestus compared to a susceptible mosquito strain [ in 2011 . Resistao strain .Permethrin-treated LLINs (Olyset Net) were distributed through universal coverage campaign in 2011. After the campaign in 2011, net ownership was 90.8% and net usage was 55.7% . BendiocThe prevalence survey was carried out from September to October 2014 . All houOn obtaining household consent, a questionnaire was administered and data entered into a personal digital assistant  on number of residents, socio economic status, house construction and quality, education, access to and use of LLINs and other malaria preventive measures, and presence of livestock.Plasmodium infection was assessed by a rapid diagnostic test (RDT) , Diasys, Wokingham, UK) and haemoglobin levels measured using HemoCue Hb 201 + . Results were initially recorded on paper forms and double entered into a digital database and checked for consistency.Selected children were given a coupon and asked to present the following day for parasitological testing. In the same households selected for cross sectional survey, 20% of LLINs were inspected for assessment of physical condition and hole index determined according to WHO guidelines .Anopheline mosquitoes per house were subsequently tested for Plasmodium falciparum circumsporozoite protein (Pf-CSP) using ELISA [An. gambiae s.l. was tested using real time PCR Taq Man assay to distinguish between the two sibling species An. gambiae s.s. and An. arabiensis [Anopheles funestus complex was determined using conventional PCR [From November 2014 to January 2015, indoor mosquito collections were conducted using CDC light traps in 14–21 randomly selected houses per cluster for one night only. The light traps were installed at the foot of a bed occupied by a family member sleeping under a LLIN. In addition, two or three furvela tent trap collections per cluster  were conng ELISA . A sub-sabiensis . Speciesonal PCR .Statistical analysis was performed using STATA . Random effects logistic regression models were used to determine possible risk factors for malaria infection determined by RDT in children 0.5–14 years old adjusting for correlation of malaria infection within clusters.Potential household and personal risk factors were explored: age, gender, individual net use, education of household head, social economic status (SES), quality of house construction and presence of open eaves, number of people per sleeping room (a proxy for crowding), LLIN ownership and access, indoor residual spraying (IRS) in 2013, presence and proximity of livestock.Variables were cleaned and coded and those which were nonlinearly related to the outcome were categorized. Variables were created for improved housing structure, individual net use, household net access, household crowding and social economic status, detail of all variables is indicated in Table All variables were analysed individually for an association with malaria infection (outcome) using a logistic regression that included village and household as random effects to account for correlation within individual village clusters and households. All potential risk factors showing evidence for a possible association with malaria infection (p < 0.1) were included in the preliminary main effect multivariate logistic regression model. A forward stepwise method was used, retaining any risk factors showing an association (LRT test p < 0.05). No a priori interaction terms were identified. Multi-collinearity was assessed for by removing parameters one by one from the model and examining the standard errors of the remaining parameters. If this caused the standard error of one of the remaining parameters to change by > 10% this was defined as multi-collinearity and one of the parameters removed.A similar approach was adopted to assess risk factors for indoor vector density. Because vector density count data was skewed and often over dispersed, a negative binomial regression analysis was used. The model estimated a density rate ratio (DRR) as the measure of effect. Univariate regression of each risk factor was performed initially and the forward step-wise method was used to build a multivariate model.The total number of households which were selected to participate in the baseline survey was 2880. Of these 2270 (78.8%) consented to participate, 276 (9.6%) failed to meet the inclusion criteria (no children < 15 years), 13 (0.5%) refused and 11.1% were excluded for other reasons . The proportion of individuals who reported using a net the night before was 27.1%. The proportion of nets declared to be less than 2 years old was 37.1%, those 2–3 years old was 31.3% and those over 3 years old were 31.4%. Many of the nets had been received via clinic-based distribution during the period since the last UCC. Only 26% of individuals slept under nets of good condition, 35% slept under nets of moderate condition and 38% under nets which were badly torn. Net access was very low; only 16.9% of individuals were residing in households with enough nets to cover all sleeping places. About 25.9% of the households reported to be sprayed with insecticide in the year before  was 64.8% (95% CI 61.8–67.8) in children aged 6 months to 14 years old. The prevalence of clinical malaria, defined as fever  and any Plasmodium infection by RDT was 6.8% (95% CI 5.5–8.1). Only 2.9% (114) of tested children had fever and among those who had fever 86% had a positive test result. The prevalence of moderate or severe anaemia .The odds of malaria infection increased with age, the oldest group being the most at risk . Children living in improved housing structure had lower odds of malaria infection compared to those who were living in unimproved housing . Individuals living in houses with an open eaves showed a strong association with malaria infection compared to those who were living in houses with closed eave gaps .Individuals who were living in households with adequate net access per sleeping place were better protected from malaria infection . Age of LLINs was also significant, with only LLINs less than two years of age showing evidence of protection . LLINs’ usage was not associated with malaria prevalence in the multivariate analysis. There was no association between malaria protection and the hole index of LLINs over the WHO LLIN categories of good condition  to ‘unserviceable’ condition .None of the other factors  were associated with malaria infection once adjusted for the other factors in the model.An. funestus s.l. and the remaining were An. gambiae s.l.. The 969 An. gambiae s.l. were identified to species by PCR, 93.5% were An. gambiae s.s., 4.5% were An. arabiensis, and 2.2% did not amplify. There was no evidence of difference in ratio of An. gambiae s.s. to An. arabiensis between indoor and outdoor collections . Of the 289 An. funestus identified by PCR 81.7% were An. funestus s.s., 15.6% Anopheles leesoni, 1.0% Anopheles parensis and 1.7% did not amplify. A subsample of 4311 specimens was tested for CSP. The sporozoite rate was 4.7%. Both An. funestus and An. gambiae s.s. were found positive for CSP. The entomological inoculation rate was 0.34 (95% CI 0.20–0.49) infectious bites per person-night during the period of collection, and this rate varied from 0 to 2.7 between village clusters.A total of 29,401 and 2668 mosquitoes were collected in 770 indoor light trap collections and in 120 outdoor tent trap collections respectively. Anophelines comprised 64% of the indoor collections and 57% of the outdoor collections. Mean vector density per collection night was 24.5 indoors and 12.7 outdoors. Of the Anophelines collected 4.6% were identified as Altitude of households selected during the entomology survey ranged from 1133 to 1651 m, with a mean of 1303 m. It rained during 43.4% of collections and the wind was moderate or strong during 43.6% of collections. 34.7% of households did not have animals. For those that owned animals, 39% kept them indoor. 50% of families had poorly constructed houses and 24% had improved houses. 57.9% of houses had open eaves. The median number of rooms was 5 per house and median household size was 5 persons. Only 19.4% of families cooked inside the house. Houses had been sprayed 3 times since the first IRS campaign in 2007. An average of 65.7% of households were using at least one LLINs.The univariate analyses showed evidence for negative associations between vector density and improved housing, number of rooms, households using at least one LLINs and number of times the house had been sprayed. Cooking inside the house was associated with higher vector densities. Altitude above 1242 m was associated with a decreased risk of indoor vectors, whereas light wind or no wind during collection was associated with increased risk.House structure had an IRR of 0.75 (95% CI 0.60–0.90), indicating a 25% decreased risk of vector exposure in improved housing. Using at least one LLIN in the household and several times sprayed was associated with reduced vector density. There was no evidence of association with rain during collection night, open eaves or animals present inside the house.The multivariate model retained five risk factors as significant: altitude, wind during collection, presence of livestock, house construction and LLINs’ usage. Number of rooms, showed co-linearity with house construction and, was therefore removed from the model. There was strong association with vector density, altitude and wind. Vector density was negatively associated with increasing altitude, being 65% less at the higher altitudes (above 1353 m) and with nights with moderate or strong winds. Improved housing structure was associated with reduced vector density whereas presence of livestock was associated with higher vector density. Net usage was associated with density after adjusting for other factors. The variables that showed no association with vector density in the multivariate model were: history of IRS, cooking indoors and presence of open eaves.This study investigated the effects of LLINs three years after the last universal coverage campaign of 2011 in an area of intense pyrethroid resistance in Northwest Tanzania. The aim of the study was to explore the effects of net coverage and deterioration as well as other household and individual risk factors associated to malaria infection and vector density. At the time of the study many of the original LLINs had developed holes or been replaced by newer ones. Malaria prevalence was over 60% in the study area in 2014, while the estimated number of infective bites per day was 0.34. These rates were much higher than the rates observed in the same area in 2011 shortly after the campaign . An incrLLIN ownership had decreased from 90.8% after the universal coverage campaign of 2011 to 69% in 2014  and usagIn the present study, access to LLINs was associated with malaria protection in the multivariate analysis whereas usage was not. This is not the first community study showing that net use is not associated with malaria. Net use last night is based on self-reporting by household members while access and ownership is observed and may be more reliable net coverage indicators , 29.About 53% of the nets which were still in use had holes and around 35% of the nets were badly torn (pHI > 643). Previous studies have indicated that personal and community effectiveness of LLINs declines over time due to factors such as net coverage, ageing of nets, net damage and insecticide resistance , 14. ProOther main risk factors for malaria infection prevalence in children 6 months to 14 years included living in area of lower altitude, in poorly constructed houses and with open eaves, being 5–14 years old, and coming from a lower socio-economic category. The same risk factors are also associated with higher vector density. These findings are consistent with other studies . Some stThe observed increased risk of malaria infection in people living in poor housing is consistent with previous studies , 34. LivIncreased risk of malaria infection in older children (the 5–14 year age group) compared to younger children seen in this study is a trend which has been observed in other studies conducted elsewhere in Tanzania . Older cAnopheles, but did not lead to an increase in human biting rate. The impact that livestock have on malaria and vector density is complex. Some studies indicate that livestock provides zooprophylatic protection [Households that own livestock had higher vector density, but this did not translate in increased malaria infection prevalence when adjusted for other co-variates. This suggests that livestock may attract otection , while ootection . It depeThe study has some limitations. The prevalence cross sectional survey was carried out before the entomological collections potentially affecting level of net coverage in the households and therefore comparability. However similar risk factors were associated with both outcomes showing that this one-month time lag may not have affected the findings of the study. Net usage assessment was based on self-reporting by household members and might not be reliable which could explain the lack of association between usage and malaria infection prevalence.Three years after the universal coverage campaign LLIN usage had decreased considerably despite distribution of new LLINs in the interim. Children living in households with full access to LLINs per sleeping place were at lower risk of malaria; however, malaria prevalence in this group remained high. Standard pyrethroid-only LLINs were no longer sufficiently protective even when in good condition and relatively new. More efforts should be made to maintain high coverage of more effective types of LLIN between campaigns.


This study investigated the prevalence and distribution patterns of malaria in Kilosa district as part of non-malaria causes of febrile illnesses in children study. We enrolled febrile patients aged 2–13 years presenting at the outpatient department during the rainy and dry seasons, in 2013. For each participant, we tested for malaria parasites and identified parasite species using microscopy. We then calculated parasite density and estimated geometric mean parasite density.Plasmodium falciparum accounted for 98.6% of malaria positives. There was a heterogeneous distribution of malaria cases among the 17 wards constituting the catchment area. A high proportion  of malaria positive individuals had high parasite densities. Individuals who were enrolled in the rainy season had higher geometric mean parasite density  compared to the dry season . The relatively high malaria prevalence recorded in Kilosa, an area considered low endemicity, calls for concerted effort in documenting malaria burden at fine geographical scales and tailor preventive and control strategies that target hotspots of high malaria transmission.The overall malaria prevalence in febrile children was 23.7% (n = 609).  Despite the continued efforts geared to reduce malaria case incidence and death rates, malaria remains a major disease, especially in children. The 2018 World malaria report estimates about 219 million malaria cases occurred in 2017 which is an increase of about 3.5 million cases compared to 2016 [Diverse malaria control efforts have been implemented for several years in malaria-endemic areas. However, we have been observing rises and falls in malaria cases and deaths globally and Tanzania. The 2015 World malaria report shows a global decrease from about 262 million cases in 2000 to 213 million in 2015 and the decline in malaria deaths by 48% [There are variations in the malaria burden between regions and districts of Tanzania. This includes differences in entomological inoculation rates, vector composition, and transmission intensities at districts level or even within villages –9. MalarThis study was conducted at Kilosa district hospital in the Morogoro region, Tanzania for 6 months covering both the rainy and dry seasons in 2013, as part of a large study on non-malaria causes of febrile illnesses in children , 12. KilThe study participants were patients presenting at the outpatient department (OPD), aged 2–13 years and with axillary body temperature ≥ 37.5 °C. For 6 months each working day (excluding weekends) the study team enrolled 5 participants who met inclusion criteria, agreed to participate and the parent/guardian provided written informed consent. For each participating child, a standardized questionnaire was administered to the parent/guardian to capture demographic and clinical information. The management of patients was performed according to the local standard of care based on world health organization (WHO) and Ministry of Health guidelines , 17, andA thick and thin blood smears were prepared from a finger prick blood sample and stained with 3% Giemsa solution, and examined under a light microscope with oil immersion. These were used for the identification and quantification of the malaria parasite respectively. A smear was considered negative if no parasites were seen after viewing at 100× high-power fields. For quality assurance, each slide was read independently by a second microscopist and any discrepancies were resolved by a third microscopist. The parasite density was determined according to the number of parasites per 200 white blood cells (WBC) counts, assuming a total WBC count of 8000/μL .Parasitaemia was categorized as low (< 1000 parasites/µl blood), moderate (1000–4999 parasites/µl blood), high , and hyperparasitaemia  –21. FeveData were entered into an Access database, verified and cleaned to ensure that clinical data and laboratory findings are matched. The statistical analyses were performed using STATA software . The geometrical mean of parasite density (GMPD) was calculated as the antilogarithm of the arithmetic mean of the base 10 logarithms of 10 plus the parasite density. Pearson’s Chi Square test was used to determine the association between categorical variables. An alpha level of 0.05 was used for all tests of statistical significance.A total of 609 participants were enrolled, of these 51.2% (n = 312) were males and 48.8% (n = 297) females. Among the 609 participants, 354 (58.1%) were children ˂ 5 years and 255 (41.9%) had ≥ 5 years. About 50% (310) of patients were enrolled during the dry season while 299 (49.1%) were enrolled in the rainy season. During the time of enrollment, the majority of the participants (78%) had a mild fever. Overall 177  had prior treatment and 154  of those with prior treatment were treated with antimalaria drugs. Only 29  of those treated with antimalaria drugs were later diagnosed with malaria.Plasmodium falciparum accounted for 98.6%. Two patients (1.4%) had a mixed infection with P. falciparum and P. malariae. There was no difference in malaria prevalence by season, sex and age groups, Table The overall malaria prevalence was 23.7% (n = 609) and patients .4% had apatients .4% had aA high proportion  of malaria positive individuals had high parasite densities whereas only 2.1% had hyperparasitaemia, Table We report here high malaria parasitaemia which might imply our study population is sitting at a transmission hotspot in a low prevalence designated Morogoro region. There are relatively few studies in Tanzania reporting parasite density, a report in Muheza  had compP. falciparum accounted for 99% of cases. It is however comparable to data from Kigoma (26%) and Lindi (26%) regions in the Western and South-eastern zones respectively, the areas considered having the highest prevalence in Tanzania [The overall malaria prevalence reported here was higher compared to the data from the 2011–2012 malaria indicator survey (13%) for the Morogoro region , and P. Tanzania . In the Tanzania . These oTanzania –32.The prevalence was not different between age groups, sex and seasons. Similar observations were reported in the same district where malaria infection was associated with the age groups of 1–10 years and 11–20 years . Our finWards with rice fields and other anthropogenic activities like bricks making had high prevalence , 38 and Despite the general decline of malaria cases in endemic areas including Tanzania, pockets of hotspots remain. Such hotspots are likely maintained by the high parasite density in a section of the population like what we observed in this study. Our findings call for a focused intensification of the preventive and control measures targeting high transmission areas to sustain the gains on malaria infections reductions.The prevalence of malaria in this study could be under- or over-estimated because this study is a hospital-based survey and might not reflect the situation in the primary healthcare facilities and the population at large, however, these findings still provide important information on malaria at fine geographical scale.


Plasmodium infections.Malaria is a major public health problem in India. Data from surveys totaling 3031 participants at three sites revealed a high proportion of asymptomatic infections, complicating diagnosis. The aim of this study was to identify differences in complaints and symptoms between sites, and factors associated with asymptomatic Plasmodium infections confirmed using microscopy, rapid diagnostic tests (RDTs), and polymerase chain reaction (PCR). Multivariate analyses were conducted to determine the association between general symptoms and age, season, or gender, and factors associated with asymptomatic Plasmodium infections were assessed.Published data from community-based cross-sectional studies conducted between 2012 and 2015 in Nadiad (Gujarat), Chennai (Tamil Nadu), and Rourkela (Odisha) as part of the Center for the Study of Complex Malaria in India were analysed. Complaints and symptoms were systematically recorded, and Plasmodium falciparum); 78.6% had a history of fever or documented fever, 14.3% had other symptoms, and 7.1% were “truly asymptomatic”. For Chennai this was 29.2%, 4.2% and 66.7% respectively, with a malaria prevalence of 2.6% by PCR of 928 participants . In Rourkela, with 7.7% of 1307 participants positive for malaria by PCR , the percentages were 35.6%, 24.8% and 39.6%, respectively. In Rourkela, asymptomatic infections were associated with young age and male gender (microscopy or RDT), and with rainy season (PCR). In the same site, participants with Plasmodium vivax were more likely to be asymptomatic (11/18 or 61.1%) than persons with P. falciparum mono-infections (27/78 or 34.6%); gametocytes for P. falciparum were evenly distributed between symptomatic and asymptomatic infections . The addition of the symptoms “headache”, “aches” and “chills” to fever improved the case-definition of symptomatic malaria.Complaints of any illness were lowest in Chennai (17.7%), 30.6% in Rourkela and 42.7% in Nadiad. Complaints were more often reported for children; gender differences were noted in Rourkela only. In Nadiad, 7.0% of 796 participants were positive for malaria by PCR (32% There were considerable differences in complaints at the three sites in India. Malaria and asymptomatic infections differ by region, indicating that malaria elimination will require localized approaches. Plasmodium falciparum), and less than 100 persons died [Plasmodium species and Anopheles vectors, and a wide variety of endemic settings [Plasmodium vivax can be detected throughout the country, whereas P. falciparum is more common in the Eastern and North-Eastern states. The major malaria vector is Anopheles culicifacies, estimated to be associated with 60–65% of the malaria disease burden in India [Anopheles stephensi is present in urban and peri-urban areas, and has been associated with serious malaria outbreaks in South India [Anopheles fluviatilis is present in the forests and foothills, and Anopheles minimus mainly in the North-Eastern states [Malaria is still a major cause of morbidity and mortality in India, although the numbers are decreasing. In 2018, the National Vector Borne Disease Control Programme (NVBDCP) estimated that approximately 500,000 people suffered from malaria  [P. vivax and P. falciparum prevalence rates oscillating throughout the year based on the rainfall. Participants were enrolled from the peri-urban and rural areas adjacent to Nadiad town. Rourkela city in the Sundargarh district of the eastern state of Odisha receives rains during the southwest monsoon season (June–September) and some rainfall during the retreating northeast monsoon (December–January) [P. falciparum as the major infecting species. Insecticide treated nets are distributed for free in malarious areas by the Government of Odisha. Subjects were enrolled from peri-urban and rural areas around Rourkela. An. culicifacies is the major vector in Nadiad, An. stephensi in Chennai, and An. fluviatilis in Rourkela [The three study sites have been described previously , 19. Briptember) . MalariaJanuary) . MalariaRourkela .P. vivax: chloroquine 25 mg/kg over 3 days and primaquine 0.25 mg/kg for 14 days; P. falciparum artesunate 4 mg/kg for 3 days in combination with sulfadoxine 25 mg/kg and pyrimethamine 1.25 mg/kg on the first day and primaquine 0.75 mg/kg [A census was conducted before the start of the surveys as described previously . Cross-s75 mg/kg . TreatmePlasmodium parasites [Several diagnostic tests were used . Haemoglarasites , 23. RDThttps://clinepidb.org), under “Study: India ICEMR Cross-Sectional”. Data were exported into Stata  for analysis. At all three study sites, the distribution of any symptoms by age, gender and season was examined first, followed by an evaluation of symptomatic and asymptomatic malaria. Malaria was defined in three groups: ‘Symptomatic and fever’ defined as Plasmodium-positive by PCR plus fever ; ‘Symptomatic and other’ defined as Plasmodium-positive by PCR and other symptoms (not fever), and ‘Truly asymptomatic infection’. Parasite infections detected by PCR but not by microscopy were classified as ‘submicroscopic’ and infections detected by PCR but not by RDT as ‘subpatent’. For anaemia, an age- and gender-appropriate definition was used  [Data for the cross-sectional studies are available in the Clinical Epidemiology Database, ClinEpiD  . Charactnd male) ; variablRourkela participants were younger and less educated than participants in the other sites and were more likely to have a history of malaria in the past year Table . A recenThere were considerable regional differences in general symptoms . A total of 67% of infections detected by PCR and 82.3% of submicroscopic infections were truly asymptomatic. The proportion of truly asymptomatic infections among Plasmodium positive persons was higher when detected by PCR  than by microscopy (37.5%) or RDT , with most malaria infections presenting with fever (range 75.4% for microscopy and 79% for PCR). Depending on the test, 14–17% presented with symptoms other than fever, with as most common symptoms headache, chills, and aches; 7–9% were truly asymptomatic  was close to the prevalence in Nadiad, only a minority presented with fever (range 39.5% by RDT and 35.6% by PCR) or other symptoms (range 24.8% detected by PCR and 13.7% by microscopy); asymptomatic infections ranged from 39.6% detected by PCR to 51% among subpatent infections  compared to persons with asymptomatic malaria  and persons with symptoms other than fever . Few gametocytes of P. falciparum were detected (7 or 0.5%); among persons with infections they were evenly distributed between symptomatic and asymptomatic infections , but gametocytes were more common among people with asexual parasitaemia compared to people without parasitaemia . Persons with P. vivax were more likely to be asymptomatic than persons with P. falciparum . In the same site, associations were noted between asymptomatic infections and young age and male gender as detected by microscopy or RDT, and with rainy season as detected by PCR , but not as detected by any other malaria test.Compared to the absence of malaria, asymptomatic infection was not associated with personal repellent use, travel, or anti-malarial treatment in the past 2 weeks at any site, or with ITN use in Rourkela, or with haemoglobin, anaemia, or When considering any of the symptoms headache, aches, chills, or fever as a definition of symptomatic malaria, the number of malaria cases with symptoms other than these was reduced in Rourkela and Nadiad, and disappeared in Chennai, indicating that all patients in Chennai presented with one of these symptoms Fig. . HoweverIndia aims to eliminate malaria . To do sDifferent patterns of general symptoms were observed, with the lowest number of any symptoms in Chennai, and the highest number of any symptoms in Nadiad. Patterns of symptoms were higher in the younger age groups and were more common in the dry season in Nadiad, whereas in Rourkela they were more common in the rainy season. Only in Rourkela were gender differences observed for some symptoms . These patterns in symptoms by region indicates that the burden of disease in each region is different. It has been reported that cultural factors can contribute to differences in symptom experiences and health-seeking behavior . Since sP. falciparum infection of 2 months, with variable parasite densities; for P. vivax this was 6 months [P. falciparum were higher than among non-febrile participants [It is not always apparent whether asymptomatic infections will develop into symptomatic malaria cases and be cleared by treatment with anti-malarial drugs or will be cleared by the person’s immune system without intervention. Submicroscopic asymptomatic parasite levels can persist after treatment, if parasites are drug resistant or if inadequate doses of anti-malarials have been used. An association with recent treatment was not detected in this analysis, but in Chennai, asymptomatic infections (as detected by RDT) were associated with an infection in the past year. A recent study in a low endemicity area in Vietnam followed 356 persons with asymptomatic subpatent infections; 61% remained afebrile during the 24-month follow up period. They noted a median duration of asymptomatic submicroscopic 6 months . Like thicipants . In a sticipants . A relatP. falciparum was the main species; it was the only site with considerable bed net use. Malaria is decreasing in Rourkela [Plasmodium vivax infections were more likely to be asymptomatic compared to P. falciparum infections; results in the literature concerning this have been conflicting [Anopheles mosquitoes [Although malaria prevalence was similar in Nadiad and Rourkela, the proportion of asymptomatic infections was very low in Nadiad compared to Rourkela, and almost all malaria in Nadiad was accompanied by symptoms. It has been suggested that the asymptomatic reservoir could be minimal when transmission has decreased over many years and people have lost immunity  and thisRourkela , but theRourkela , 32. ImmRourkela , 30, 33.Rourkela . AlternaRourkela . It has Rourkela ; in Rourflicting . Use of flicting , 16. Asysquitoes .Plasmodium parasites, and the definition of symptomatic/asymptomatic infections is mainly useful in the surveillance context for the evaluation of malaria burden. In Rourkela, there remained a group of persons who had symptoms such as cough or backache and a positive Plasmodium test. It is possible that these symptoms were unrelated to malaria but due to other diseases, given the higher prevalence of asymptomatic Plasmodium infections in this area.Asymptomatic malaria is often defined as a positive malaria test in the absence of documented fever or a history of fever . This stIn Chennai, the number of malaria cases was low (n = 24) and in Nadiad, the number of asymptomatic malaria cases was low (n = 12); this limited the type of analyses that could be conducted. The participants with asymptomatic infections were not followed over time and so it was not possible to assess their subsequent clinical status. The study systematically asked questions concerning a series of symptoms at enrolment, not just fever, and used the same design, questionnaires, and malaria tests in all three sites, strengthening the comparability of the results.P. vivax where dormant hypnozoites in the liver can continue transmission. Mass drug treatment has been an alternative but may result in ineffective exposure of persons to adverse events of medication when the malaria prevalence is very low, and may select resistant parasites, especially when conducted in the dry season [‘malaria control in inaccessible areas’ programme.This current study reports on regional differences in general complaints at the three sites in India and on difference of malaria and asymptomatic infections by region. Asymptomatic infections are important because it can continue transmission, hinder elimination, and chronically affect people’s health. Strategies to reduce asymptomatic infections include “mass screen and treat” campaigns, mass drug administration, and reactive case management, and all these options can be combined with indoor residual spraying or ITN. Reactive case detection (RCD), the screening of persons in the households and neighborhoods of positive index cases, has been studied in Chennai and Nadiad but results were not encouraging . RCD is y season . Mass scAdditional file 1. Additional tables.


Malaria during pregnancy has been associated with hindered transplacental transfer of antibodies to several pathogens but whether it affects transplacental transfer of KSHV antibodies is unknown. We aimed to determine if Plasmodium falciparum (Pf) DNA at any ANC visit or delivery. Among women with malaria during pregnancy, we examined time of last malaria infection prior to delivery (< 27 vs. 27+ weeks gestation) and malaria incidence rate (MIR) (episodes/100 person-weeks).A cohort study in Kisumu, Kenya enrolled pregnant women at their first antenatal clinic (ANC) visit and followed them through delivery. We included 70 KSHV-positive, HIV-negative mothers and their children. KSHV antibody levels were measured by ELISA  and multiplex assay . Transplacental transfer of antibodies was measured by the cord to maternal blood ratio (CMR) of KSHV antibodies. Malaria during pregnancy was defined as detection of KSHV seroprevalence (positive for K8.1 or ORF73 by ELISA) among pregnant women was 88%. Neither malaria during pregnancy, malaria infection timing, nor MIR were associated with maternal delivery KSHV antibody blood levels. Maternal delivery and cord blood KSHV antibody levels were highly correlated but these correlations did not differ by malaria during pregnancy. KSHV transplacental antibody transfer was not associated with malaria during pregnancy, malaria infection timing, nor MIR.Malaria during pregnancy does not appear to affect transfer of KSHV antibodies across the placenta.The online version contains supplementary material available at 10.1186/s13027-020-00336-1. Kaposi sarcoma-associated herpesvirus (KSHV) is the etiological agent for Kaposi sarcoma (KS), one of the ten most common cancers in Kenya . In sub-S. pneumonia and measles [Maternally derived immunoglobulin G (IgG) antibodies transported across the placenta provide passive humoral immunity that protects infants for the first few months of their lives. The levels of antibodies transferred from mother to fetus determine the duration and strength of protection against infection. Placental malaria has been associated with reduced transfer of total IgG antibodies , 5 and a measles , 8 and m measles . AlteredAlthough malaria has been associated with reduced transplacental transfer of antibodies to other pathogens, the effect of malaria infection during pregnancy on maternal transfer of KSHV antibodies is relatively unknown. We used samples from the Chulaimbo Antenatal Postnatal (CHAP) cohort of pregnant women and their newborns enrolled from Kisumu District in Kenya, a region with a high KSHV seroprevalence that is also malaria holoendemic, to determine if malaria infection during pregnancy reduces the transplacental transfer of KSHV antibodies from mother to child.The CHAP study was a longitudinal cohort of pregnant women and their children initiated in 2011. The original study was designed to explore factors that determine early age of infection with EBV. The study population is described elsewhere in more detail , 11. In Informed consent was obtained from each study participant. Research was performed in accordance with the Declaration of Helsinki and all protocol and consent forms were approved by the Scientific and Ethical Review Unit (SERU) at the Kenya Medical Research Institute (KEMRI), the Colorado Multiple Institutional Review Board (COMIRB), and the State University of New York (SUNY) Upstate Medical University (where study was initiated).At enrollment, information on demographics and pregnancy history was collected including data on the woman’s tribe, education, marital status, age, gravidity, and bed net use at time of enrollment.Pregnant women provided finger stick blood samples at each ANC visit and 2-4 mL of venous blood at enrollment and within 12 h of delivery. An incision on the maternal side of the placenta was made to collect an intervillous blood (IVB) sample . For venPlasmodium falciparum (Pf) DNA as described previously [Pf DNA was detected by quantitative polymerase chain reaction (qPCR) and/or blood smear [Maternal, placental, and cord malaria status were determined by detection of eviously . A womanod smear . SubsequTrichuris trichura, Ascaris lumbricodes, E. histolytica, Giardia lamblia, stronglyoides, or Schistosoma hematobium.Presence of antibodies to either KSHV open reading frame (ORF)73 or K8.1 in plasma taken at enrollment and tested by enzyme-linked immunosorbent assays (ELISA) was used to indicate whether pregnant women were KSHV seropositive . All pren = 2). Children were considered preterm if born < 38 weeks gestational age and low birth weight if weighing ≤2500 g at birth.Child sex, birthweight (grams), and gestational age were collected at birth. Gestational age was calculated as the number of weeks from the last reported menstrual period to delivery. Gestational ages over 45 weeks were truncated to 45 weeks as that was the longest reasonable gestational age in the sample  following the manufacturer’s instructions. Hypergammaglobulinemia in pregnant women was defined as having levels of total IgG > 30 mg/ml as per kit instructions.IgG antibodies to K8.1 and ORF73 were tested using KSHV ELISA as previously described . Plasma The same samples were tested for antibodies to KSHV proteins K8.1, ORF73, K10.5, ORF38, and ORF50 using the bead-based multiplex assay as described . HealthyOf the 200 women enrolled in the original study we included 70 KSHV-positive, HIV-negative women who delivered at the study hospital and had complete maternal and cord blood sample pairs. Because we wanted to look at transplacental transfer of KSHV antibodies, we only included KSHV-positive women . MIR was calculated as the number of malaria episodes divided by the total weeks a pregnant woman was in the study before delivery multiplied by 100. Number of malaria episodes was determined by the number of times a pregnant woman was considered positive for Pf by qPCR. Consecutive positive detections by qPCR were considered a single malaria episode unless there was a two-month gap between malaria positive ANC visits. Pregnant women should have received Sulfadoxine-pyrimethamine (SP) at each ANC visit as a malaria prophylaxis and so we expected that any infection after two months would be a new exposure. Finally, we examined whether timing of the most recent malaria episode prior to delivery had any effect on maternal transplacental transfer of KSHV antibodies. Timing of malaria was defined as early most recent malaria exposure  vs. late most recent malaria exposure .Malaria during pregnancy was defined as ever occurring if KSHV antibody responses were measured by ELISA (K8.1 and ORF73) and multiplex . We examined maternal venous blood KSHV antibody levels at delivery. Transplacental transfer of antibodies was measured as the cord to maternal blood ratio (CMR) for each protein.p-value < 0.2 were selected as potential candidates and included in the final model if they changed the association estimate by ≥10%. For each exposure, p-values were adjusted for multiple comparisons using a false discovery rate (FDR) adjustment. All analyses were completed using SAS 9.4.Univariate descriptive statistics were calculated using Chi-squared or Fisher’s exact tests for categorical variables, and student's t-tests for continuous normally distributed variables. Mann Whitney U tests were used to model the relationship between malaria during pregnancy, or among women with malaria during pregnancy, timing of last malaria infection and maternal venous blood KSHV antibody levels at delivery. Spearman’s correlation coefficient was used for the analysis of MIR with maternal venous blood KSHV antibody levels at delivery, among women with a malaria infection during pregnancy. Pearson’s correlation coefficient was used to determine the correlations between KSHV antibody levels in maternal venous blood taken at delivery and neonatal cord blood. KSHV antibody levels measured by multiplex were log-transformed. Linear regression was used to model the associations between malaria during pregnancy, and among those with malaria during pregnancy, timing of last malaria infection and MIR with log-transformed KSHV antibody CMR. For adjusted analysis, maternal and child characteristics identified a priori to be associated with both malaria and transplacental transfer of KSHV antibodies were assessed as potential confounders. These included: maternal tribe, education, marital status, parity, bed net use during pregnancy, worm infection during pregnancy, and hypergammaglobulinemia, and child’s gestational age and birthweight. Associations between potential confounders and either exposure or KSHV antibody CMR were modeled using Mann Whitney U, Kruskal Wallis, Chi-squared, Fisher’s exact test, or Spearman correlation coefficient, as appropriate. Variables associated with both the exposure of interest and KSHV antibody CMR by To determine if our sample contained selection bias, we compared demographic and clinical characteristics of pregnant women enrolled in the study by whether they were included in the final analysis, excluded because they were HIV-positive, and excluded for any other reason. Chi-squared, Fisher’s exact test, and ANOVA were used, as appropriate, to compare univariate statistics across the three groups.n = 199), 175 (88%) were KSHV seropositive. Pregnant women tested positive for KSHV by detection of ORF73 alone , K8.1 alone  or either K8.1 or ORF73 . Our final analysis included 70 (35%) KSHV-positive, HIV-negative women who delivered at the study hospital with complete maternal venous blood and cord blood sample pairs , married (67%), and with upper primary schooling or higher (79%). Helminths were detected during pregnancy in 23% of women and hypergammaglobulinemia in 27% of women. Almost all the newborns were of normal birthweight 91%) and most were full term (71%)   had placental malaria and the average MIR was 8.8 per 100 person-weeks. The overall MIR of our study participants  was 4.7 malaria episodes per 100 person-weeks. The most recent malaria infection prior to delivery was during the last trimester (27+ weeks) for more than half of pregnant women who had any malaria infection during pregnancy  and mothers with malaria infection were more likely to come for all four ANC visits.  . Excluded mothers were also less likely to come to all four ANC visits   to examine this relationship. We did look at the gestational age of the most recent infection prior to delivery and still reported no effect on transplacental KSHV antibody transfer.Previous studies have found that malaria impedes the transfer of antibodies against  measles , 8, teta measles , 6, HSV- measles , though  measles , 8. We fKSHV antibodies may be resistant to barriers of transplacental transfer caused by malaria, such as placental inflammation, reduced Fc receptor binding avidity, or induced hypergammaglobulinemia which is known to reduce transplacental IgG transfer , 16. AntEBV is a gammaherpesvirus that is also endemic to sub-Saharan Africa. Up to 50% of children are infected with KSHV by two years of age  but almoin utero malaria reduces KSHV antibody transplacental transfer, then our estimates may be driven towards the null due to differential misclassification, though we believe this misclassification occurred minimally, if at all. Symptomatic women would have received appropriate diagnosis and care for malaria infection at the study clinic. In addition, our use of qPCR, which allowed us to detect both asymptomatic and symptomatic malaria infections, minimized any potential misclassification. We found a high MIR among women in our study of 4.7 per 100 person-weeks. Chulaimbo District, where our study took place, has one of the highest MIRs in Kenya [Women with malaria infection during pregnancy were significantly more likely to come for all four ANC visits versus their uninfected counterparts. Women who came for fewer ANC visits may have been miscategorized into the never malaria group due to less opportunities to detect the parasite. If in Kenya . In addiin utero malaria infection and not just at malaria during delivery. By using both the multiplex and ELISA assays to measure antibody levels, we were able to examine a wider breadth of antibodies to KSHV antigens. The fact that we found similar results using both types of assays strengthens our conclusion that malaria does not appear to affect KSHV transplacental antibody transfer.The longitudinal design of this study allowed us to look throughout pregnancy for We had a limited sample size to adjust for multiple comparisons. Even so, our estimates were quite insignificant, and it is likely that if our sample size was larger, we would only have detected small associations, if any, between malaria infection during pregnancy and KSHV antibody transfer. We were unable to differentiate the exact number of malaria infections detected using qPCR and so created an algorithm to calculate a malaria incidence rate. Our sample only included women who delivered at the study hospital, who may be different from those lost to follow-up and were not generalizable to the rest of the population. Nonetheless, our sensitivity analysis comparing women included in our analysis to those excluded showed no differences in demographics or health characteristics.in utero malaria exposure that altered transplacental transfer of maternal IgG; the neonates first line of defense against infection. However, the data from this study suggests that malaria infection during pregnancy does not affect maternal KSHV antibody transfer to infants. Further studies should explore other potential biological mechanisms between malaria and KSHV including malaria’s potential role to increase susceptibility to and/or reactivation of KSHV during infancy and its potential role in the etiology of KS disease.Malaria has been previously associated with KSHV infection and non-bed net use with KS disease in sub-Saharan Africa , 21–26. Additional file 1. Inclusion criteria for analysis of malaria during pregnancy and transplacental KSHV antibody transfer.Additional file 2. Relationship between maternal Kaposi sarcoma-associated herpesvirus (KSHV) antibody levels at delivery and malaria infection during pregnancy.Additional file 3. Linear regression estimates of mean difference in KSHV antibody log(CMR) by malaria exposure.Additional file 4. Maternal demographics, clinical characteristics, and pregnancy history by inclusion and exclusion status.


Plasmodium falciparum malaria is classified as either uncomplicated or severe, determining clinical management and providing a framework for understanding pathogenesis. Severe malaria in children is defined by the presence of one or more features associated with adverse outcome, but there is wide variation in the predictive value of these features. Here we review the evidence for the usefulness of these features, alone and in combination, to predict death and other adverse outcomes, and we consider the role that molecular biomarkers may play in augmenting this prediction. We also examine whether a more personalized approach to predicting outcome for specific presenting syndromes of severe malaria, particularly cerebral malaria, has the potential to be more accurate. We note a general need for better external validation in studies of outcome predictors and for the demonstration that predictors can be used to guide clinical management in a way that improves survival and long-term health. Plasmodium. Over 150 Plasmodium species have been identified ), coma (OR 4.83 [95% CI 3.11–7.5]), hypoglycemia (OR 4.59 [95% CI 2.68–7.89]), shock (OR 4.31 [95% CI 2.15–8.64]), and deep breathing (OR 3.8 [95% CI 3.29–4.39]) . LeopoldScore systems have been developed to simplify the application of prediction models for rapid implementation in clinical settings. For instance, Helbok et al. developed the Lambaréné Organ Dysfunction Score (LODS) 0–3, which denote the presence of coma, prostration, and deep breathing – the three variables which were most significantly associated with fatal outcomes in six sites across Africa from the SMAC network . The LODIn addition to clinical features, many studies have also identified molecular biomarkers associated with adverse outcome in children with malaria. Whilst SM is a heterogeneous condition defined by the variety of clinical manifestations outlined above, biomarkers that predict progression from UM to SM and outcome across all SM phenotypes would be extremely attractive in clinical practice. Potential prognostic biomarkers originating from both host and parasite have been described.P. falciparum Histidine Rich Protein-2 (PfHRP2) have been demonstrated in multiple studies to be associated with the severity of malaria in children  and 82.6 [95% CI 61.2–95.0], respectively, for predicting mortality in SM patients, but specificity was low  .In contrast, the cytokine interferon gamma-induced protein-10 (IP-10), which is involved in the chemoattraction of T cells, natural killer cells, and monocytes, achieved high values for both sensitivity of 82.6% [95% CI 61.2–95.0] and specificity of 85% [95% CI 75.3–92.0] for mortality prediction in this cohort  when theIt is likely that the combination of multiple host biomarkers will be needed to produce widely applicable predictive tests for the outcome of malaria. The selection of optimal panels of biomarkers remains to be achieved, although modern variable selection and machine learning approaches should make this easier ,116. TheIn addition to prognostic features and biomarkers for SM in general, there are predictors of outcome specific to each of the major phenotypes of SM which occur in children: CM, SMA, and respiratory distress. Since there are clear clinical and biological differences between these syndromes , a more P. falciparum malaria the sequestration of parasites in the microvasculature of the brain appears to be a necessary feature, and cerebral edema (brain swelling) appears to be the final common pathway leading to death. Mortality rate is variable depending on the setting and presence of other SM features, however, even when these are accounted for it can still be as high as 15-25% in tertiary care centers ) with no evidence for a beneficial effect of transfusion (OR for death in the transfused group of 0.99 [95% CI 0.97–1.02]) . This prTreatment with blood transfusion is recommended when hemoglobin levels fall below 5g/dl . While lMany biomarkers associated with the presence of/or susceptibility to SMA have been identified. Interesting findings include a dysregulated immune response, primarily Th1 cytokines, and chemokines, and their association with dyserythropoiesis –197. GenIn childhood malaria, respiratory distress is largely attributed to metabolic acidosis  and is lOver 80% of children with SM complicated by respiratory distress are found to be profoundly acidotic . MoreoveThe principle cause of acidosis is thought to be tissue hypoxia and resultant anaerobic glycolysis generating lactic acid, and additional accumulation and impairment of the metabolism of lactic acid  and ketoMalaria, young age, malnutrition, and HIV infection were identified as the strongest risk factors for bacteremia amongst children admitted to hospital in a large study in Kenya . ChildreThe geographical overlap between high malaria incidence and HIV prevalence presents a substantial burden caused by coinfection. Whilst literature on the pediatric population is limited, due to the lower prevalence of HIV in children, studies have shown that HIV-infected individuals of all ages are more susceptible to SM –224 – esP. falciparum malaria. Due to the low prevalence of malaria and low associated mortality in Europe, no study has been performed to identify risk factors for death or poor long-term prognosis specifically in children in the context of best available supportive care. Therefore, definitions of SM and risk factors have been extrapolated from endemic settings. In the UK, surveillance data showed that children, pregnant women, and older people were particularly at risk of SM, but mortality was highest in those over 65 y of age with very few deaths in children [P. falciparum blood schizonts, pigment deposits in leucocytes, metabolic acidosis, male sex, delay in seeking treatment, diagnosis, or receiving care, nonuse, or inappropriate use of chemoprophylaxis, coma, and renal impairment [Travelers to malaria endemic areas may be malaria naïve with no naturally acquired immunity or may have waning immunity even if they were previously resident in the endemic country. Most life-threatening malaria complications occur in nonimmune travelers returning from malaria endemic areas, with 5% of those affected suffering SM . The morchildren ,233. Facpairment ,233.Severe childhood malaria is a multi-system disease that encompasses a range of clinical complications including CM, SMA, and respiratory distress. The defining features of SM differ considerably in their frequency, the strength of evidence for their association with adverse outcomes, and their predictive value. Many studies have combined multiple features into prediction models and scoring systems, which has improved the accuracy of prediction and increased ease of use. The most consistent and important predictors of death appear to be coma, markers of metabolic derangement (acidosis and hypoglycemia), and renal failure.var gene expression profiles, sTREM-1, sFlt-1, and angiopoietins 1 and 2. However, their potential may be compromised by technical challenges to implementation in clinical tests (var genes), difficulty in identifying universal thresholds across different transmission settings (PfHRP2), and incomplete understanding of complex interactions with other host response proteins (cytokines). To overcome the latter, feature selection techniques could be implemented to identify the best panels of non-redundant biomarkers and clinical features that together give more accurate outcome predictions. Few studies have included validation of prediction in external cohorts, but this is essential in order to provide evidence that they may be generalizable.Numerous molecular biomarkers have been proposed to predict outcome in SM, including PfHRP2 concentrations, It is clear that prognostic factors and biomarkers specific for distinct SM syndromes also hold promise, and may result in better prediction of adverse outcomes than general prognostic markers in SM. This parallels ongoing debate about whether syndrome-specific adjunctive treatments for SM are needed, essentially applying the principles of personalized medicine to malaria. This approach to prognosis appears most promising in CM, and additional work is needed to identify and validate syndrome-specific biomarkers in SMA and respiratory distress. Perhaps more importantly, there is a large gap between the identification of prognostic features and biomarkers and providing evidence that their measurement contributes to improved short or long-term outcomes for patients. Identification of predictors of neurological sequelae for CM now needs to be combined with intervention studies to prevent or mitigate the effects of these sequelae.In the ongoing search for predictors of outcome in malaria, we believe that it is essential to consider how biomarkers and other predictors could be used in malaria endemic settings. A successful predictive test is likely to be cheap, rapid, and easy to measure with minimal requirement for infrastructure or specialized training. It should be applicable across different settings, not confounded by the age or immune status of the patient, and it should be highly accurate. Ideally, the results of the prognostic test would guide realistic treatment choices for each individual patient, benefitting those at most risk of death or long-term morbidity.In this literature review, we have critically evaluated the usefulness and potential of the clinical and molecular features associated with SM mortality and long-term sequelae. However, there is still a need for a systematic meta-analysis of the impact of all these features on prognosis prediction accounting for the heterogeneity between the associated studies. This heterogeneity includes the differences in the sample sizes, study settings, and age range of the patients studied, making a systematic meta-analysis extremely challenging.


Plasmodium falciparum malaria. Whether eBL risk is related to malaria parasite density is unknown. To address this issue, children with eBL, asymptomatic and clinical malaria, as a surrogate of malaria parasite density, were assessed.Endemic Burkitt lymphoma (eBL) is an aggressive B cell non-Hodgkin lymphoma associated with antigenic stimulation from Malaria-related laboratory results  count) were compiled for 4019 eBL cases and 80,532 subjects evaluated for asymptomatic malaria or clinical malaria  in 21 representative studies published in Africa (mostly East Africa) and 850 eBL cases and 2878 controls with primary data from the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) case–control study in Uganda, Tanzania, and Kenya. The average values of malaria-related laboratory results were computed by condition and trends across single-year age groups were assessed using regression and spline models.Overall, malaria infection or malaria was diagnosed in 37,089 of children compiled from the literature. Children with eBL and asymptomatic parasitaemia/antigenaemia, but not those with clinical malaria, were closest in their mean age (age 7.1–7.2 vs. 7.4–9.8 years), haemoglobin level (10.0–10.4 vs. 11.7–12.3 g/dL), malaria parasite density (2800 vs. 1827–7780 parasites/µL), platelet count , and WBC count (8180–8890 vs. 7100–7410 cells/µL). Parasite density in these two groups peaked between four to five years, then decreased steadily thereafter; conversely, haemoglobin showed a corresponding increase with age. Children with clinical malaria were markedly different: all had an average age below 5 years, had dramatically elevated parasite density  and dramatically decreased platelet count  and haemoglobin (< 7 g/dL).eBL and asymptomatic parasitaemia/antigenaemia, but not clinical malaria, were the most similar conditions with respect to mean age and malaria-related laboratory results. These results suggest that children with asymptomatic parasitaemia/antigenaemia may be the population at risk of eBL. Plasmodium falciparum malaria [P. falciparum malaria [P. falciparum infection [P. falciparum infection [Endemic Burkitt Lymphoma (eBL) is an aggressive B-cell non-Hodgkin lymphoma that is associated with endemic  malaria . Thus, t malaria –3 and eB malaria , where e malaria . The rolnfection –8 and innfection , 9. In anfection –12, espenfection . Howevernfection , 15 and nfection . The conWhether the relationship between malaria and eBL is related to malaria morbidity and circulating malaria parasite burden and inflammation , for whiThis paper reports an investigation to assess the patterns of age and selected malaria-related laboratory measures  count) in children with eBL, asymptomatic parasitaemia/antigenaemia, and clinical malaria in Uganda, Tanzania, and Kenya using primary data from a case–control study or secondary data extracted from papers published in malaria endemic areas.The analysis utilized primary data compiled from children enrolled in the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) Study conducted in Uganda, Tanzania, and Kenya during 2010–2016 . The EMBSecondary data on children with eBL or clinical malaria were compiled from published papers by searching PubMed and Google Scholar to identify representative papers about eBL and malaria conditions. Malaria conditions in these papers were classified according to the World Health Organization algorithm into asymptomatic parasitaemia/antigenaemia or clinical malaria with six conditions , symptoms , signs , and malaria-related laboratory measures , were extracted into a spreadsheet. Malaria parasite density > 250,000 parasites/µL of blood was used to define hyperparasitaemia; haemoglobin < 5 g/dL of blood was used to define severe malaria anaemia ; thromboP < 0.05 with Bonferroni adjustment for the number of comparisons performed were considered statistically significant.Results expressed on a continuous scale were extracted as means and standard deviations or as medians and inter-quartile ranges (IQR). Medians were statistically converted into means using standard statistical methods  to enablResults were available for 850 eBL cases and 2878 healthy controls with primary data in the EMBLEM study and 4019 eBL cases and 37,089 of 80,532 children with secondary data in 21 published articles selected from 685 articles had asymptomatic malaria infection or clinical malaria and their data were extracted (Fig. Malaria-related laboratory results showed distinct clusters in children below or above 5 years and by malaria condition Fig. a–d. The Trends in parasite density, haemoglobin, platelet count, and WBC count across single year age groups in children with eBL or asymptomatic parasitaemia/antigenaemia in the EMBLEM study are shown in Fig. Figure The current study was done to evaluate whether eBL risk might be connected with high parasite density using acute malaria conditions as surrogates of moderate or high parasite density. The results show clustering of eBL and asymptomatic parasitaemia/antigenaemia in children aged > 5 years who have normal or near normal values of parasite density, haemoglobin, platelet, and WBC counts. These results suggest that eBL could be a complication of asymptomatic parasitaemia/antigenaemia and cast doubt on the idea that it is a complication of high parasite density or the associated high inflammation, as was originally hypothesized. High parasite density was a feature of three sub-clusters of clinical malaria, all found in children below 5 years. These early age-onset malaria syndromes were characterized by markedly abnormal values of parasite density, haemoglobin, platelet counts and WBC counts. These syndromes included children with severe malaria anaemia and hyperparasitaemia, those with cerebral malaria and moderate malaria, and those with malaria prostration and mild malaria and markedly abnormal values of some or all of parasite density, haemoglobin, platelet counts and WBC counts. The findings in this study are likely valid because ~ 9.5% of eBL cases and 6.7% of the controls in the EMBLEM study were 0–3 years, but even in this age range the children with eBL and asymptomatic parasitaemia/antigenaemia still showed malaria-related laboratory measures that were different from those in children with acute malaria conditions. Moreover, children with eBL had significantly lower parasite density than those with asymptomatic parasitaemia/antigenaemia suggesting that the similarity of eBL with asymptomatic parasitaemia/antigenaemia observed in overall results is established at a very early age. These results are consistent with a recent review by Quintana et al.  where thc-MYC into the vicinity of immunoglobulin enhancer elements and progression to eBL [Antigenic stimulation from malaria is widely accepted as an insult that leads to B cell proliferation in the germinal center and increases the chance of translocation of n to eBL . Howevern to eBL , therebyn to eBL , the oven to eBL –12, suchP. falciparum genetic diversity score than controls [Asymptomatic malaria is typically associated with low-, rather than high-parasite density malaria parasitaemia. Thus, these results also suggest that eBL risk may be associated with low density malaria infection. Furthermore, because an asymptomatic infection, particularly in children above 5 years, is also likely to be a clonally diverse infection , these rcontrols . This hycontrols  because controls . The hypcontrols , 29.This study has some limitations, notably, reliance on cross-sectional data. Thus, the correlations should not be interpreted as evidence for causality. Second, the reliance on published literature to increase complement assessment in EMBLEM is a strength, but the literature may be biased or incomplete. For example, studies of asymptomatic parasitaemia/antigenaemia may under-sample children below 5 years, or studies of severe malaria may oversample children below 5 years, which would lead to erroneous mean age patterns. However, the results from the EMBLEM study, which enrolled representative, population-based eBL cases and controls and uniformly tested subjects for malaria-related laboratory measures, support the overall patterns. This study lacks direct measures of immunity to malaria, including anti-malaria antibodies, which limits the ability to compare the immune status of eBL cases with that of children with asymptomatic parasitaemia/antigenaemia or clinical malaria. The strengths of this study include the large sample size and detailed data from the EMBLEM study and published data about children with malaria from malaria endemic areas.The findings suggest that children with eBL and asymptomatic parasitaemia/antigenaemia were most similar with respect to age and malaria-related laboratory results and that both groups were markedly different from children with clinical malaria. These results raise a testable hypothesis that asymptomatic parasitaemia/antigenaemia, and by extension its associated low malaria parasite density, may be the antigenic stimulation from malaria related to eBL onset.Additional file 1: Table S1. A list of articles with used as sources for relevant data about malaria conditions in East Africa.