Project Description:

Each year, 400,000 people, primarily pregnant women and children under 5, die from malaria. Efforts to eliminate malaria rely on high-quality vector surveillance data. Vector surveillance is the process of analyzing the population characteristics of mosquitos, such as species, sex, and abdominal status, in a given location in order to make informed decisions toward elimination of vector-borne diseases. It is crucial to understand these characteristics because they provide insight into the behavior of vectors in a given area. This data is vital to inform intervention decisions, such as the distribution of bed nets or indoor residual sprays. Our device, the VectorCam tool, automatically performs analysis of individual mosquito specimens using computer vision. By automating the process, we can deskill vector surveillance by task shifting data collection from trained entomologists at a centralized lab to village health workers in their communities. This will ultimately result in greater temporal and spatial resolution of surveillance data, allowing for better targeted malaria interventions decisions.

Project Photo:

Vector Control Officer in Zambia using the VectorCam tool to identify mosquito characteristics from specimen collected earlier that day

Student Team Members

• Summer Duffy
• Christina Hummel
• Janis Iourovitski
• Rebecca Rosenberg
• Spencer Shumway
• Joshua Blair

Course Faculty

Project Mentors, Sponsors, and Partners

• Dr. Soumyadipta Acharya
• Dr. Youseph Yazdi