VectorCam — Uganda's AI smartphone tool for malaria vector surveillance

VectorCam is a smartphone-based AI application developed through a collaboration between Makerere University School of Public Health, the Johns Hopkins Bloomberg School of Public Health Center for Global Digital Health Innovation, and Uganda's Ministry of Health. The Bill & Melinda Gates Foundation endorsed it as a notable health innovation.

The application uses computer vision and deep learning to automatically identify mosquito species, sex, and blood-meal status from photographs taken via a smartphone-attached microscope adapter. In field validation, VectorCam achieved 90% accuracy for species identification in resource-constrained settings where trained entomologists are scarce. Correct species identification is essential for targeted malaria vector control: different Anopheles species have different insecticide-resistance profiles and transmission dynamics, making generic spraying programmes both costly and ineffective.

As of 2024, VectorCam has been deployed in 12 districts with embedded operational research monitoring, with a rollout target of 22 districts across Uganda. The system enables district health teams to generate real-time entomological data without requiring centralised laboratory infrastructure.

The system does not yet have published independent outcome evaluations (e.g., randomised controlled data on malaria incidence attributable to the improved surveillance). Evidence remains at the technical-performance and deployment level; causal claims about population-level health outcomes should be treated with caution pending formal evaluation. Future impact studies are planned as part of the Ministry of Health rollout.

Read the full analysis: https://publichealth.jhu.edu/center-for-global-digital-health-innovation/vectorcam-innovation-for-mosquito-surveillance-lauded-by-bill-gates