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VectorPAL: an Integrated Entomological Decision Support System for Malaria Control

Project Description:

With VectorCam, frontline health workers can now identify mosquito species in the field without lab support, significantly improving the timeliness and quality of vector data. Our team is investigating the next step: how to turn that data into action. VectorPAL is a decision-support concept that synthesizes entomological, environmental, and behavioral inputs to recommend feasible, community-level interventions. Through stakeholder interviews, fieldwork in Uganda, and expert consultation, we are evaluating how such a tool could support district officers and village health teams in selecting strategies—like larval source management or ITN behavior reinforcement—based on real-time conditions. This work focuses on closing the loop between surveillance and response, answering the “so what?” question that arises once high-quality data is available.

Project Photo:

Photo of symbols representing malaria vector control including a spray bottle, a target on a waterbody, a crossed out mosquito, and a mosquito net.

Using AI-enabled tools to support community-driven malaria control through real-time mosquito surveillance and locally informed decision-making.