Last Updated: 18/01/2023
Integrating intervention-targetable behaviours of malaria vectors to optimize intervention selection and impact in Tanzania
Objectives
This study will provide insights into which additional strategies are likely to be most effective on the basis of local vector ecology. This could be a game changer in the development of locally-tailored, highly effective mosquito control packages in Africa, which accelerate progress toward malaria elimination. It will also form the basis for improved policy and practice with respect to effective targeting of supplementary vector control measures.
The study will integrate surveys of intervention-targetable behaviours of mosquitoes and humans into the existing nationally- representative malaria vector surveillance platform in Tanzania and use this to identify what human and mosquito behaviours drive persisting malaria transmission. Specifically, will quantify intervention-targetable behaviours of malaria vectors and characterize both environmental and anthropological determinants of how those behaviours vary across 32 locations in diverse ecological settings in mainland Tanzania. These data will be used to model and predict which supplementary vector control tools are likely to be most effective in different ecological zones, and provide NMCP with a framework for rational selection of interventions to optimize vector control impact. The project will potentially strengthen malaria vector surveillance and control in Tanzania and beyond and accelerated toward malaria elimination. This award will also strengthen research competence for the African research Institution, Ifakara Health Institute in particular, and consolidation collaboration with UK- institutions (University of Glasgow and University of Liverpool) which are global leader in Public Health Research.
The Tanzanian part of the study comes from the prestigious and highly internationally competitive Award which was offered to Dr. Govella by MRC under African Research Leader Scheme.
Feb 2020 — Oct 2024
$1M