Real-time disease risk monitoring and forecasting for early action

Rift Valley fever (RVF) is a vector-borne disease that significantly impacts livelihoods, trade, tourism, and human health. Currently endemic in Africa and parts of the Near East, RVF primarily affects sheep, goats, cattle, buffaloes, and camels. Outbreaks are closely linked to climate anomalies like heavy rains and flooding, which create favorable conditions for mosquito populations, increasing disease risk. Early warning systems are essential to prevent RVF outbreaks. The Food and Agriculture Organization of the United Nations (FAO) developed a web-based RVF Early Warning Decision Support Tool (RVF DST), integrating near real-time risk maps, historical disease data, and expert eco-epidemiological knowledge. Launched in 2019 and integrated into FAO’s geospatial platform in 2020, the RVF DST was piloted in Kenya, Uganda, and United Republic of Tanzania. It provides near real-time risk maps updated weekly, covering the entire African continent. The tool uses a Multi-Criteria Decision Analysis approach to create real-time risk maps for RVF introduction, spread, and occurrence. It has improved FAO’s ability to identify high-risk areas, issue early warnings, incite members to step up preparedness and prevent RVF outbreaks, with alerts sent 2-3 months before the first signs of infection. These alerts, combined with surveillance activities and expert knowledge, help validate potential hotspots and support early response efforts. The RVF DST has enhanced vigilance and preparedness in Eastern Africa and fostered collaboration between FAO, national veterinary services, and partners like the World Health Organization (WHO), Intergovernmental Authority on Development (IGAD), and World Organisation for Animal Health (WOAH). It demonstrates the value of near real-time risk modelling and digital innovation in improving disease preparedness and response, setting a standard for global health security.