Data from: Topographic mapping of the interfaces between human and aquatic mosquito habitats to enable barrier-targeting of interventions against malaria vectors

Mwakalinga, VM, Sartorius, BKDORCID logo, Limwagu, AJ, Mlacha, YP, Msellemu, DF, Chaki, PP, Govella, NJ, Coetzee, M, Dongus, S and Killeen, GF (2018). Data from: Topographic mapping of the interfaces between human and aquatic mosquito habitats to enable barrier-targeting of interventions against malaria vectors. [Dataset]. Dryad. https://doi.org/10.5061/dryad.77vq6gs
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Geophysical topographic metrics of local water-accumulation potential are freely available and have long been known as high resolution predictors of where aquatic habitats for immature Anopheles mosquitoes are most abundant, resulting in elevated densities of adult malaria vectors and human infection burden. Using existing entomological and epidemiological survey data, here we illustrate how topography can also be used to map out the interfaces between wet, unoccupied valleys and dry, densely populated uplands, where malaria vector densities and infection risk are focally exacerbated. These topographically identifiable geophysical boundaries experience disproportionately high vector densities and malaria transmission risk because this is where Anopheles mosquitoes first encounter humans when they search for blood after emerging or ovipositing in the valleys. Geophysical topographic indicators accounted for 67% of variance for vector density but only 43% for infection prevalence, so they could enable very selective targeting of interventions against the former but not the latter (targeting ratios of 9.0 versus 1.5 to 1, respectively). So in addition to being useful for targeting larval source management to wet valleys, geophysical topographic indicators may also be used to selectively target adult Anopheles mosquitoes with insecticidal residual sprays, fencing, vapour emanators or space sprays to barrier areas along their fringes.

Keywords

Plasmodium falciparum, Geophysical topography, Spatial modelling, Anopheles gambiae, Malaria, Barrier - targeted interventions

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