Last Updated: 30/07/2025
Understanding temporal shifts in mosquito host-seeking as drivers of behavioral resistance to insecticide-treated bed nets (MosqBedTiming)
Objectives
This project aims to understand the origins of the behavioral shifts (biting before nightfall reducing ITN effectiveness) using innovative methodologies.
Mosquitoes transmit malaria parasites by feeding on humans, claiming approximately half a million lives each year. Insecticide-treated nets (ITNs) have been an effective method to reduce malaria mortality by protecting people from mosquito bites at night. However, mosquitoes are now changing their host-seeking behavior, biting before nightfall reducing ITN effectiveness. Two mechanisms are hypothesized to drive this shift: genetic evolution or phenotypic plasticity. ITNs may select for mosquitoes genetically hardwired to bite early, or mosquitoes might adapt behaviorally without genetic changes. These mechanisms have different implications for long-term ITN effectiveness and require different countermeasures. There is currently lack of tools to accurately test these hypotheses. A behavioral assay was recently developed to longitudinally monitor mosquito activity in the lab continuously over weeks. The aim is now to adapt this method for field deployment to investigate temporal shifts in mosquito behavior in malaria-endemic regions with varying levels of ITN use. Lab and field research will be merged through three objectives: (1) Develop an assay to monitor mosquito host-seeking rhythms and environmental variables in the field. (2) Deploy the assay in malaria-endemic areas with varying ITN exposure. (3) Dissect the genetic and environmental factors driving host-seeking shifts in lab experiments. The project combines the PI’s experience in biophysics and hardware development with Prof. Teun Bousema’s expertise in malaria fieldwork, and Dr. Felix Hol’s expertise in mosquito behavior to address the urgent issue of mosquito behavioral resistance to ITNs. This work will help design next-generation vector control strategies by understanding the factors driving behavioral shifts that diminish the effectiveness of ITNs.
Mar 2026 — Feb 2028
$230,376


