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

The risk of spatial spread in our model relies on estimating movement patterns of infectious cases. Our method also provides estimates of the probability of a case staying within a country throughout their infectious period, and the extent to which distance between two locations affects the flow of infectious cases between them. The real-time estimates of these parameters over the course of the epidemic (Fig 34) , suggest that while the relative flow of cases between locations did not vary substantially over time, the probability of travel across national borders may have decreased after the initial phase of the epidemic. Finally, we quantify the relative risk of importation of a case into a country from any other currently affected country. The risk of importation is proportional to the population flow into a country from all other countries estimated using a mobility model (here, gravity model) weighted by the infectivity at each country (which depends on the number of cases and time at which they were infected, see Methods). Our estimates of the countries with higher risk of acting as source of importations are largely consistent with the reported source of cases (Fig 5) . In 4 out of the 5 reported cases of international spread of the epidemic in West Africa, the model correctly attributed the highest relative risk of acting as a source of importation (relative risk > 0.9 for importation into Liberia, Nigeria and Sierra Leone and 0.49 in case of Mali) to the actual source identified through retrospective epidemiological and genomic investigations [26] .