Using Digital Surveillance Tools for Near Real-Time Mapping of the Risk of International Infectious Disease Spread: Ebola as a Case Study

Sangeeta Bhatia; Britta Lassmann; Emily Cohn; Malwina Carrion; Moritz U.G. Kraemer; Mark Herringer; John Brownstein; Larry Madoff; Anne Cori; Pierre Nouvellet

In our increasingly interconnected world, it is crucial to understand the risk of an outbreak originating in one country or region and spreading to the rest of the world. Digital disease surveillance tools such as ProMED and HealthMap have the potential to serve as important early warning systems as well as complement the field surveillance during an ongoing outbreak. Here we present a flexible statistical model that uses data produced from digital surveillance tools (ProMED and HealthMap) to forecast short term incidence trends in a spatially explicit manner. The model was applied to data collected by ProMED and HealthMap during the 2013-2016 West African Ebola epidemic. The model was able to predict each instance of international spread 1 to 4 weeks in advance. Our study highlights the potential and limitations of using publicly available digital surveillance data for assessing outbreak dynamics in real-time.