Using human biomass and its spatial...

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IHI team engages with top brass at SERI

The IHI team (right) led by Dr. Honorati Masanja (not seen on the photo) meets with SERI officials (left row) during a stakeholder engagement meeting in Bern last week. PHOTO/COURTESY …

Health professionals learn “One Health” approach

Dr. Ally Olotu stresses a point when he addressed participants and invited guests during the opening ceremony. PHOTO/IHIcoms (Bagamoyo, Aprili 5 2019) Health professionals from Zoonotic disease risk areas of …

Recent Projects

Calcium supplementation on pregnant women

Project summary This is a trial-based study funded by the Bill and Melinda Gates Foundation. It intends to generate evidence for decision-making on the potential non-inferiority of a lower dose …

Sustainable, Healthy, Learning Cities and Neighbourhoods

The Sustainable, Healthy, Learning Cities and Neighbourhoods is an exciting project in which IHI works with a consortium of partners from Asia and Africa to 1) develop capacity for improved …

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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