In Uganda, a country with huge dependence on natural resources, the increased frequency and intensity of severe weather conditions such as floods and droughts pose high risks as the occurrences of water-borne and vector-borne diseases and malnutrition-related illnesses are heightened.
Despite the successful introduction of policy measures, to-date, Uganda has not yet implemented a system capable of predicting the anticipated occurrence of climate-sensitive diseases based on changes in weather conditions. Funded by the World Bank’s Climate Investment Funds (CIF), the “Climate Change and Health in Sub-Saharan Africa Project: The Case of Uganda (CHASA)” addressed this gap by developing a digital solution that predicts the occurrence of climate-sensitive diseases based on historical and current weather and health data.
The project developed a digital predictive model using Artificial Intelligence for estimating the occurrence of climate-sensitive diseases based on historical weather and health data. The model uses monthly average weather data obtained from UNMA for predicting the occurrence of monthly climate-sensitive diseases. CHAI and Uganda Ministry of Health-Division of Health Information are working to institutionalize the predictive model with the health system.
Country: Uganda
Funder: Climate Investment Funds (CIF), World Bank