This community innovation has been accepted at the 2026 DHIS2 Annual Conference as a physical poster.
Operational climate-sensitive disease forecasting
Climate change is increasingly altering the transmission dynamics of climate-sensitive diseases, particularly vector-borne and water-borne diseases, underscoring the need for predictive systems that support timely public health action. In Lao PDR, we integrated climate data into the national Health Management Information System (HMIS) based on DHIS2 to operationalize disease forecasting within routine surveillance. Temperature and rainfall data were linked with weekly indicator-based disease surveillance data to assess associations with priority climate-sensitive diseases, including dengue and diarrhoeal diseases. Building on this integration, we implemented a predictive engine based on the Early Warning, Alert, and Response System (EWARS), using statistical models developed in R. Forecast outputs were automatically pushed into DHIS2 for visualization through dashboards, enabling program managers and decision makers to act proactively. The system was retrospectively tested using historical data through 2022 to generate dengue forecasts, which were validated against observed data from 2023. Model performance improved compared to earlier iterations, with forecasts closely aligning with observed epidemic trends. To support sustainability and national ownership, the forecasting workflow was embedded within the DHIS2 Climate and Health Action Platform (CHAP), strengthening interoperability and governance. A national workshop built capacity among central and provincial staff to interpret forecasts and translate early warnings into preparedness and response actions. This work demonstrates the feasibility of embedding climate-informed disease forecasting into the HMIS rather than relying on parallel tools. Remaining challenges include data sharing across sectors, limitations in climate data granularity, and the need for continuous model refinement. Addressing these issues through intersectoral coordination and ongoing capacity building is critical to strengthening climate-resilient surveillance and response systems in Lao PDR and similar settings.
Primary Author: Achala Upendra Jayatilleke
Keywords:
Climate change, climate sensitive disease, disease forecasting, surveillance, preparedness, response, DHIS2, HMIS, Lao PDR
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