Using human biomass and its spatial...

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Scientists: Target TB interventions on these transmission hotspots

(Dar es Salaam, September 14, 2017). Scientists at Ifakara Health Institute (IHI) have recently adapted a method for identifying tuberculosis (TB) transmission hotpots using a new technique that could revolutionize …

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IHI is looking for suitably qualified Research Officer and Laboratory Technicians to fill vacant positions in the Laboratory Unit in Bagamoyo. To apply or share, get more details about these …

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Understanding and enhancing approaches to quality improvement in small and medium sized private facilities in sub-Saharan Africa

This is an evaluation study that IHI is conducting in collaboration with London school of hygiene and tropical medicine. The research takes place in the context of an innovative intervention …

Vaccine Delivery Costing Study

As countries drive towards achieving high and equitable coverage of life-saving vaccines, the availability of sustainable, equitable, and predictable financing for vaccine delivery is essential. Over the last two decades, …

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.


Lead Scientists:

Emmanuel Kaindoa

Fredros Okumu

Gerry Killeen



Liverpool School of Tropical Medicine


Wellcome Trust

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