Author: Sangeeta Bhatia; Britta Lassmann; Emily Cohn; Malwina Carrion; Moritz U.G. Kraemer; Mark Herringer; John Brownstein; Larry Madoff; Anne Cori; Pierre Nouvellet
Title: Using Digital Surveillance Tools for Near Real-Time Mapping of the Risk of International Infectious Disease Spread: Ebola as a Case Study Document date: 2019_11_15
ID: jwesa12u_96
Snippet: For each model (i.e., for each choice of the time window), we made forward projections every 7 th day, over a 2 week, 4 week and 6 week horizon. To forecast incidence from day t onwards, we fitted the model to the daily incidence series up to day t − 1. We then sampled 1000 parameter sets (reproduction numbers for each location in each time window and parameters of the gravity model) from the joint posterior distribution, and for each parameter.....
Document: For each model (i.e., for each choice of the time window), we made forward projections every 7 th day, over a 2 week, 4 week and 6 week horizon. To forecast incidence from day t onwards, we fitted the model to the daily incidence series up to day t − 1. We then sampled 1000 parameter sets (reproduction numbers for each location in each time window and parameters of the gravity model) from the joint posterior distribution, and for each parameter set, simulated one future epidemic trajectory according to equation (1) , assuming that future R t is equal to the last estimated R t value in each location.
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