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

Importantly, many other open data sources could be included in our framework to improve model performance. For example, data on human mobility could be used to further inform the parametric form and parameter values of our mobility model. We have incorporated a simple and wellcharacterised model of population movement in the current work. In addition to utilising other possible data sources, future work could consider other models of human population movement [33] . When relevant, spatially-explicit data on population-level immunity to the circulating pathogen (e.g. following previous epidemics and/or due to vaccination) could also be used to refine our transmission model. Finally, the impact of the health capacity of a region to respond to a public health emergency could also be accounted for in future iterations of the model. Ongoing efforts to collate quantitative information on the performance of health systems and the ability of regions or countries to respond to an epidemic [34], [35] can potentially provide valuable data for future work. Here using a relatively simple modelling approach we provide one of the first pieces of evidence of the potential value of digital surveillance for real-time quantitative analysis of epidemic data, with important operational and actionable outputs.