AI and Mathematical Modelling for Mpox Response in Cameroon
Photo Credit: Feepik
Overview
Mpox remains a persistent public health threat in Cameroon, where fragmented surveillance systems and limited real-time data have historically slowed outbreak detection and response. For the health workers and communities in endemic regions, these gaps translate directly into preventable illness and death.
The AI4Mpox Cameroon project addresses this through Mpox-237CM, a digital dashboard that gives health officials live case maps, trend tracking, hotspot alerts, and outbreak forecasts. Built in partnership with the Centre de Recherche et de Prévention des Épidémies (CERPLE), the tool integrates existing data collection infrastructure, ensuring continuity and institutional ownership from the outset. Two master's students are embedded in the project, conducting targeted surveillance research that connects academic capacity with on-the-ground public health needs.
The dashboard is already operational in the Southwest Region, marking an early but significant shift toward evidence-based epidemic response. By combining AI and mathematical modelling, the project equips decision-makers with the foresight to act before outbreaks escalate.