Enhancing surveillance with the Surveillance-Santé-Sénégal (3S) platform

Overview

Zoonotic diseases — infections that spread between animals and humans pose a persistent and often underestimated threat to public health in Senegal. In border regions shaped by migration, urban centres dense with livestock markets, and communities where human, animal, and environmental health are deeply intertwined, the gaps in early warning systems can be costly. For the community health workers, livestock professionals, and local actors who are often first to notice something is wrong, those gaps translate directly into delayed responses and preventable outbreaks.

Led by the AI4PEP Senegal team, the project deployed the 3S (Surveillance-Santé-Sénégal) platform, an AI-powered tool for real-time detection of zoonotic disease across three strategically selected districts: Saraya in Kédougou, a cross-border mining region with high population movement; Podor in Saint-Louis, a high-traffic corridor bordering Mauritania; and Pikine in Dakar, an urban hub where stray animals, wastewater, and biodiversity pressures converge. Rather than positioning the platform as a top-down health authority tool, the project built it into community practice training actors across health, livestock, and environmental sectors to use the system collaboratively and contribute feedback to improve its functionality.

The results speak to what happens when AI tools are paired with genuine community buy-in. Participants across all three districts embraced the platform, with market vendors, fishermen, and livestock professionals engaging alongside formal health workers in cross-sectoral surveillance. Early warning is no longer the sole preserve of health authorities it is becoming a shared, community-wide responsibility. The project offers a replicable model for AI-driven epidemiological surveillance that is locally embedded, sectorally connected, and built for the realities of the communities it serves.