The prevalence and density of asymptomatic Plasmodium falciparum infections among children and adults in three communities of western Kenya

Background: Further reductions in malaria incidence as more countries approach malaria elimination require the identification and treatment of asymptomatic individuals who carry mosquito-infective Plasmodium gametocytes that are responsible for furthering malaria transmission. Assessing the relationship between total parasitaemia and gametocytaemia in field surveys can provide insight as to whether detection of low-density, asymptomatic Plasmodium falciparum infections with sensitive molecular methods can adequately detect the majority of infected individuals who are potentially capable of onward transmission. Methods: In a cross-sectional survey of 1354 healthy children and adults in three communities in western Kenya across a gradient of malaria transmission (Ajigo, Webuye, and Kapsisywa-Kipsamoite), asymptomatic P. falciparum infections were screened by rapid diagnostic tests, blood smear, and quantitative PCR of dried blood spots targeting the varATS gene in genomic DNA. A multiplex quantitative reverse-transcriptase PCR assay targeting female and male gametocyte genes (pfs25, pfs230p), a gene with a transcriptional pattern restricted to asexual blood stages (piesp2), and human GAPDH was also developed to determine total parasite and gametocyte densities among parasitaemic individuals. Results: The prevalence of varATS-detectable asymptomatic infections was greatest in Ajigo (42%), followed by Webuye (10%). Only two infections were detected in Kapsisywa. No infections were detected in Kipsamoite. Across all communities, children aged 11-15 years account for the greatest proportion total and sub-microscopic asymptomatic infections. In younger age groups, the majority of infections were detectable by microscopy, while 68% of asymptomatically infected adults (> 21 years old) had sub-microscopic parasitaemia. Piesp2-derived parasite densities correlated poorly with microscopy-determined parasite densities in patent infections relative to varATS-based detection. In general, both male and female gametocytaemia increased with increasing varATS-derived total parasitaemia. A substantial proportion (41.7%) of individuals with potential for onward transmission had qPCR-estimated parasite densities below the limit of microscopic detection, but above the detectable limit of varATS qPCR. Conclusions: This assessment of parasitaemia and gametocytaemia in three communities with different transmission intensities revealed evidence of a substantial sub-patent infectious reservoir among asymptomatic carriers of P. falciparum. Experimental studies are needed to definitively determine whether the low-density infections in communities such as Ajigo and Webuye contribute significantly to malaria transmission

Symptomatic malaria enhances protection from reinfection with homologous Plasmodium falciparum parasites

A signature remains elusive of naturally-acquired immunity against Plasmodium falciparum. We identified P. falciparum in a 14-month cohort of 239 people in Kenya, genotyped at immunogenic parasite targets expressed in the pre-erythrocytic (circumsporozoite protein, CSP) and blood (apical membrane antigen 1, AMA-1) stages, and classified into epitope type based on variants in the DV10, Th2R, and Th3R epitopes in CSP and the c1L region of AMA-1. Compared to asymptomatic index infections, symptomatic malaria was associated with reduced reinfection by parasites bearing homologous CSP-Th2R (adjusted hazard ratio [aHR]:0.63; 95% CI:0.45–0.89; p = 0.008) CSP-Th3R (aHR:0.71; 95% CI:0.52–0.97; p = 0.033), and AMA-1 c1L (aHR:0.63; 95% CI:0.43–0.94; p = 0.022) epitope types. The association of symptomatic malaria with reduced hazard of homologous reinfection was strongest for rare epitope types. Symptomatic malaria provides more durable protection against reinfection with parasites bearing homologous epitope types. The phenotype represents a legible molecular epidemiologic signature of naturally-acquired immunity by which to identify new antigen targets

Open Access

Spatial autocorrelation in uptake of antenatal care and relationship to individual, household and village-level factors: results from a community-based survey of pregnant women in six districts in western Keny

Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations

A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities

Spatial autocorrelation in uptake of antenatal care and relationship to individual, household and village-level factors: results from a community-based survey of pregnant women in six districts in western Kenya

Abstract Background The majority of maternal deaths, stillbirths, and neonatal deaths are concentrated in a few countries, many of which have weak health systems, poor access to health services, and low coverage of key health interventions. Early and consistent antenatal care (ANC) attendance could significantly reduce maternal and neonatal morbidity and mortality. Despite this, most Kenyan mothers initiate ANC care late in pregnancy and attend fewer than the recommended visits. Methods We used survey data from 6,200 pregnant women across six districts in western Kenya to understand demand-side factors related to use of ANC. Bayesian multi-level models were developed to explore the relative importance of individual, household and village-level factors in relation to ANC use. Results There is significant spatial autocorrelation of ANC attendance in three of the six districts and considerable heterogeneity in factors related to ANC use between districts. Working outside the home limited ANC attendance. Maternal age, the number of small children in the household, and ownership of livestock were important in some districts, but not all. Village proportions of pregnancy in women of child-bearing age was significantly correlated to ANC use in three of the six districts. Geographic distance to health facilities and the type of nearest facility was not correlated with ANC use. After incorporating individual, household and village-level covariates, no residual spatial autocorrelation remained in the outcome. Conclusions ANC attendance was consistently low across all the districts, but factors related to poor attendance varied. This heterogeneity is expected for an outcome that is highly influenced by socio-cultural values and local context. Interventions to improve use of ANC must be tailored to local context and should include explicit approaches to reach women who work outside the home

Can individuals- beliefs help us understand nonadherence to malaria test results? Evidence from rural Kenya

In malaria- endemic countries about a quarter of test- negative individuals take antimalarials (artemisinin- based combination therapies [ACTs]). ACT overuse depletes scarce resources for subsidies and contributes to parasite resistance. As part of an experiment in Kenya that provided subsidies for rapid diagnostic test and/or for ACTs conditionally on being positive, we studied the association between beliefs on malaria status (prior and posterior the intervention) and decisions to get tested and to purchase ACTs. We find that prior beliefs do not explain the decision of getting tested (conditional on the price) and nonadherence to a negative test. However, test- negative individuals who purchase ACTs report higher posterior beliefs than those who do not, consistent with a framework in which the formers revise beliefs upward, while the latters do not change or revise downward. We also do not find evidence that prior beliefs on ACT effectiveness and trust in test results play any major role in explaining testing or treatment behavior. Further research is needed to improve adherence to malaria- negative test results.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166413/1/rode12708.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/166413/2/rode12708_am.pd

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations