Use of digital epidemic surveillance data for AI-guided epidemic forecasting

The grant will reshape current forecasting methods and will allow the team to develop an open-source, modular, and flexible tool that uses epidemic case incidence data to inform short-term case and epidemic risk projections. It builds on the "Mapping the Risk of International Infectious Disease Spread (MRIIDS)" prototype that the team developed with funding from the U.S. Agency for International Development. Project partners will apply natural language processing and machine learning algorithms to automate the extraction of epidemic case data and will further refine and improve forecasting algorithms through use of artificial intelligence. Integration of other innovative data streams will strengthen the accuracy and validity of these predictive models for impending outbreaks.