Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study.

This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.

Reactive case detection of Plasmodium falciparum in western Kenya highlands: effective in identifying additional cases, yet limited effect on transmission.

BACKGROUND: Identifying asymptomatic reservoirs of malaria parasites using index cases as entry points into the community is potentially a cost-effective way towards achieving malaria elimination. METHODS: Within 1 year, 1430 confirmed malaria cases were identified in Marani hospital, western Kenya. Fifty cases were followed up, and 108 index case household members and 612 neighbours within a 100 m radius were screened. As controls, samples were collected from 510 individuals matched with index cases and located at a distance of ≥ 500 m from them. Infections were diagnosed by microscopy and PCR while simultaneously collecting malaria vectors indoor using pyrethrum spray catches. RESULTS: In the index case and neighbour households, the prevalence of infection was approximately twice as high as in control households (by PCR: index cases households: 28.9%, neighbours: 25.3%, matched controls: 12.9%). In index case households, the indoor vector density (Anopheles gambiae and Anopheles funestus) was higher (0.46 female/house/night) than in neighbouring (0.31 f/h/n) and control houses (0.29 f/h/n). CONCLUSIONS: Screening index case households and neighbours approximately doubles the chance to detect asymptomatic infections compared to randomly selected households. However, even if all cases were followed up, only a small proportion (˂ 10%) of the asymptomatic reservoir in the population would have been identified. Control programmes need to weigh the increased chance to find cases around index cases vs. the logistical challenges to target this subgroup within the population.