Malaria control may be enhanced by targeting reservoirs of Plasmodium falciparum transmission. One putative reservoir is asymptomatic malaria infections and the scale of their contribution to transmission in natural settings is not known. We assess the contribution of asymptomatic malaria to onward transmission using a 14-month longitudinal cohort of 239 participants in a high transmission site in Western Kenya. We identify P. falciparum in asymptomatically- and symptomatically-infected participants and naturally-fed mosquitoes from their households, genotype all parasites using deep sequencing of the parasite genes pfama1 and pfcsp, and use haplotypes to infer participant-to-mosquito transmission through a probabilistic model. In 1,242 infections (1,039 in people and 203 in mosquitoes), we observe 229 (pfcsp) and 348 (pfama1) unique parasite haplotypes. Using these to link human and mosquito infections, compared with symptomatic infections, asymptomatic infections more than double the odds of transmission to a mosquito among people with both infection types (Odds Ratio: 2.56; 95% Confidence Interval (CI): 1.36–4.81) and among all participants (OR 2.66; 95% CI: 2.05–3.47). Overall, 94.6% (95% CI: 93.1–95.8%) of mosquito infections likely resulted from asymptomatic infections. In high transmission areas, asymptomatic infections are the major contributor to mosquito infections and may be targeted as a component of transmission reduction.

Surveillance and diagnosis of Plasmodium falciparum malaria relies predominantly on rapid diagnostic tests (RDT). However, false-negative (FN) RDT results are known to occur for a variety of reasons, including operator error, poor storage conditions, pfhrp2/3 gene deletions, poor performance of specific RDT brands and lots, and low-parasite density infections. We used RDT and microscopy results from 85 000 children enrolled in Demographic Health Surveys and Malaria Indicator Surveys from 2009 to 2015 across 19 countries to explore the distribution of and risk factors for FN-RDTs in sub-Saharan Africa, where malaria’s impact is greatest. We sought to (1) identify spatial and demographic patterns of FN-RDT results, defined as a negative RDT but positive gold standard microscopy test, and (2) estimate the percentage of infections missed within community-based malaria surveys due to FN-RDT results. Across all studies, 19.9% (95% CI 19.0% to 20.9%) of microscopy-positive subjects were negative by RDT. The distribution of FN-RDT results was spatially heterogeneous. The variance in FN-RDT results was best explained by the prevalence of malaria, with an increase in FN-RDT results observed at lower transmission intensities, among younger subjects, and in urban areas. The observed proportion of FN-RDT results was not predicted by differences in RDT brand or lot performance alone. These findings characterise how the probability of detection by RDTs varies in different transmission settings and emphasise the need for careful interpretation of prevalence estimates based on surveys employing RDTs alone. Further studies are needed to characterise the cost-effectiveness of improved malaria diagnostics (eg, PCR or highly sensitive RDTs) in community-based surveys, especially in regions of low transmission intensity or high urbanicity.

Novel interventions that leverage the heterogeneity of parasite transmission are needed to achieve malaria elimination. To better understand spatial and temporal dynamics of transmission, we applied amplicon next-generation sequencing of two polymorphic gene regions (csp and ama1) to a cohort identified via reactive case detection in a high-transmission setting in western Kenya. From April 2013 to July 2014, we enrolled 442 symptomatic children with malaria, 442 matched controls, and all household members of both groups. Here, we evaluate genetic similarity between infected individuals using three indices: sharing of parasite haplotypes on binary and proportional scales and the L1 norm. Symptomatic children more commonly share haplotypes with their own household members. Furthermore, we observe robust temporal structuring of parasite genetic similarity and identify the unique molecular signature of an outbreak. These findings of both micro- and macro-scale organization of parasite populations might be harnessed to inform next-generation malaria control measures.