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

Plasmodium falciparum importation does not sustain malaria transmission in a semi-arid region of Kenya

Human movement impacts the spread and transmission of infectious diseases. Recently, a large reservoir of Plasmodium falciparum malaria was identified in a semi-arid region of northwestern Kenya historically considered unsuitable for malaria transmission. Understanding the sources and patterns of transmission attributable to human movement would aid in designing and targeting interventions to decrease the unexpectedly high malaria burden in the region. Toward this goal, polymorphic parasite genes (ama1, csp) in residents and passengers traveling to Central Turkana were genotyped by amplicon deep sequencing. Genotyping and epidemiological data were combined to assess parasite importation. The contribution of travel to malaria transmission was estimated by modelling case reproductive numbers inclusive and exclusive of travelers. P. falciparum was detected in 6.7% (127/1891) of inbound passengers, including new haplotypes which were later detected in locally-transmitted infections. Case reproductive numbers approximated 1 and did not change when travelers were removed from transmission networks, suggesting that transmission is not fueled by travel to the region but locally endemic. Thus, malaria is not only prevalent in Central Turkana but also sustained by local transmission. As such, interrupting importation is unlikely to be an effective malaria control strategy on its own, but targeting interventions locally has the potential to drive down transmission

What Is Threatening the Effectiveness of Insecticide-Treated Bednets? A Case-Control Study of Environmental, Behavioral, and Physical Factors Associated with Prevention Failure.

Insecticide-treated nets are the cornerstone of global malaria control and have been shown to reduce malaria morbidity by 50-60%. However, some areas are experiencing a resurgence in malaria following successful control. We describe an efficacy decay framework to understand why high malaria burden persists even under high ITN coverage in a community in western Kenya.We enrolled 442 children hospitalized with malaria and paired them with age, time, village and gender-matched controls. We completed comprehensive household and neighborhood assessments including entomological surveillance. The indicators are grouped into five domains in an efficacy decay framework: ITN ownership, compliance, physical integrity, vector susceptibility and facilitating factors. After variable selection, case-control data were analyzed using conditional logistic regression models and mosquito data were analyzed using negative binomial regression. Predictive margins were calculated from logistic regression models.Measures of ITN coverage and physical integrity were not correlated with hospitalized malaria in our study. However, consistent ITN use (Adjusted Odds Ratio (AOR) = 0.23, 95%CI: 0.12-0.43), presence of nearby larval sites (AOR = 1.137, 95%CI: 1.02-1.27), and specific types of crops (AOR (grains) = 0.446, 95%CI: 0.24-0.82) were significantly correlated with malaria amongst children who owned an ITN. The odds of hospitalization for febrile malaria nearly tripled when one other household member had symptomatic malaria infection (AOR-2.76, 95%CI:1.83-4.18). Overall, perfect household adherence could reduce the probability of hospitalization for malaria to less than 30% (95%CI:0.12-0.46) and adjusting environmental factors such as elimination of larval sites and growing grains nearby could reduce the probability of hospitalization for malaria to less than 20% (95%CI:0.04-0.31).Availability of ITNs is not the bottleneck for malaria prevention in this community. Behavior change interventions to improve compliance and environmental management of mosquito breeding habitats may greatly enhance ITN efficacy. A better understanding of the relationship between agriculture and mosquito survival and feeding success is needed

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

What Is Threatening the Effectiveness of Insecticide-Treated Bednets? A Case-Control Study of Environmental, Behavioral, and Physical Factors Associated with Prevention Failure

<div><p>Background</p><p>Insecticide-treated nets are the cornerstone of global malaria control and have been shown to reduce malaria morbidity by 50–60%. However, some areas are experiencing a resurgence in malaria following successful control. We describe an efficacy decay framework to understand why high malaria burden persists even under high ITN coverage in a community in western Kenya.</p><p>Methods</p><p>We enrolled 442 children hospitalized with malaria and paired them with age, time, village and gender-matched controls. We completed comprehensive household and neighborhood assessments including entomological surveillance. The indicators are grouped into five domains in an efficacy decay framework: ITN ownership, compliance, physical integrity, vector susceptibility and facilitating factors. After variable selection, case-control data were analyzed using conditional logistic regression models and mosquito data were analyzed using negative binomial regression. Predictive margins were calculated from logistic regression models.</p><p>Results</p><p>Measures of ITN coverage and physical integrity were not correlated with hospitalized malaria in our study. However, consistent ITN use (Adjusted Odds Ratio (AOR) = 0.23, 95%CI: 0.12–0.43), presence of nearby larval sites (AOR = 1.137, 95%CI: 1.02–1.27), and specific types of crops (AOR (grains) = 0.446, 95%CI: 0.24–0.82) were significantly correlated with malaria amongst children who owned an ITN. The odds of hospitalization for febrile malaria nearly tripled when one other household member had symptomatic malaria infection (AOR–2.76, 95%CI:1.83–4.18). Overall, perfect household adherence could reduce the probability of hospitalization for malaria to less than 30% (95%CI:0.12–0.46) and adjusting environmental factors such as elimination of larval sites and growing grains nearby could reduce the probability of hospitalization for malaria to less than 20% (95%CI:0.04–0.31).</p><p>Conclusion</p><p>Availability of ITNs is not the bottleneck for malaria prevention in this community. Behavior change interventions to improve compliance and environmental management of mosquito breeding habitats may greatly enhance ITN efficacy. A better understanding of the relationship between agriculture and mosquito survival and feeding success is needed.</p></div

Diagram of the efficacy decay of prevention.

<p>Effectiveness of ITNs is threatened by five domains: inadequate coverage, poor compliance, poor physical condition and reduced vector susceptibility. In addition, facilitating factors can further reduce the apparent effectiveness measured under real-world conditions.</p

Multivariable negative binomial regressions of anopheles mosquito counts.

<p>Multivariable negative binomial regressions of anopheles mosquito counts.</p

Predictive margins.

<p>Probability of malaria for different values of specific covariates by domain. Each scenario holds all other model covariates at their mean value.</p

Characteristics of case/control children and their households.

<p>Characteristics of case/control children and their households.</p