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 the context of increasing potential for movement of diseases between various regions of the world due to increased global connectivity, innovative strategies for epidemic monitoring are urgently needed. In this study, we propose a statistical framework that relies on digital surveillance data from ProMED or HealthMap to 1) predict the short-term epidemic trajectory in currently affected countries, 2) quantify the short-term risk of spread to other countries and 3) for countries at risk of importation, quantify where the risk comes from. We apply our model to data collected during the West African Ebola epidemic of 2013-2016, curated by the outbreak analysts at ProMED/HealthMap, and we compare the model's outputs to those obtained when using the data collated by the WHO and made available at the end of the epidemic.