Using human biomass and its spatial distribution to predict mosquito-borne disease transmission patterns in rural Tanzania
Disease-transmitting mosquitoes are known to preferentially bite bigger people over small people, and households with high occupancy have also been shown to have high Anopheles densities. It is therefore likely that overall directional movement of mosquitoes within villages, and subsequent disease transmission risk, could be greatly influenced by spatial distribution of household biomass. These observations, though widely accepted have not been previously developed into practical actionable methodologies for disease prevention and control. Yet this close association between human aggregations and mosquito biting risk may significant influence on malaria parasite prevalence and infectiousness. In this study use controlled experimental hut studies and high resolution household-level sampling of indoor mosquito-biting densities, to demonstrate spatial correlations between human biomass, household occupancy and indoor malaria vector densities in three villages in south eastern Tanzania. We also assess whether regular household census data could be used to identify households with the greatest Anopheles mosquito biting risk in rural Tanzania. Based on the understanding of how disease-transmitting mosquitoes identify and follow cues from vertebrate hosts, we hypothesize that their dispersal within villages, as determined by distribution of host biomass, could relied upon as an indicator of areas with high biting risk occurs.