This community innovation has been accepted at the 2026 DHIS2 Annual Conference as a physical poster.
EPIDEMIA: Next-Generation Epidemic Intelligence
Despite substantial global progress in shrinking the malaria map, momentum has slowed because of drug and insecticide resistance, conflict and population displacement, declining international financing for malaria interventions, and increasing climate variability and change. One way to address these challenges is by leveraging routine surveillance and other relevant data to support proactive public health response. Although there has been considerable interest in malaria forecasting, operational uptake has been limited by data fragmentation, model complexity, and challenges in integration with public health action. The EPIDEMIA malaria early warning system was developed to generate district-level malaria risk forecasts for Ethiopia using satellite-derived environmental data and epidemiological time series. Over the past decade, EPIDEMIA has evolved through close collaboration with national and regional public health stakeholders, transitioning from a research prototype to an operational platform supporting malaria surveillance and preparedness. We are developing the next-generation version of EPIDEMIA under a NASA-funded project aimed at improving forecast skill, scalability, and usability. This effort leverages advances in software design, Earth observation data streams, and machine-learning–based spatiotemporal modeling to enhance forecasting of risk and early detection of malaria outbreaks across heterogeneous settings. A central focus of the current implementation is strengthening interoperability with national health information systems, including DHIS2. This talk will present the history of the development of EPIDEMIA, outlining accomplishments and lessons learned and highlighting prospects for increasing the level of automation through integration with DHIS2. Topics will include design considerations for data exchange, alignment with DHIS2 data models, and approaches for embedding climate-informed risk products within existing surveillance and decision-making workflows.
Primary Author: Michael Wimberly
Keywords:
malaria; early warning; outbreak detection; surveillance; emergency response; forecasting; climate variation; extreme weather
Very interesting!