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

Here, we have assumed a single p stay for all countries on African mainland. For estimating the time-varying reproduction number for each country, we split the duration of the total outbreak into intervals of equal width. We assume that transmissibility in each location stays constant within each time window and thus, within a time window, we estimated a single reproduction number for each location. We varied the length of the time window to obtain different models, with short time windows increasing the number of parameters in the model. To reduce the number of parameters in the model, we divided the 55 countries on African continent into 5 groups and forced each country in a group to have the same reproduction number in each time window. The first three groups correspond of the three mainly affected countries -Sierra Leone, Guinea and Liberia. The countries that shared a border with these three countries were grouped together. These were Mali, Côte d'Ivoire, Guinea-Bissau and Gambia. The rest of the countries were assigned to the fifth group. A comparison of the performance of different models is presented in the Supplementary Material (Fig 32) .