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_74
Snippet: where R t i is the reproduction number at location i at time t and p i→j is the probability of a case moving from location i to location j while they are infectious. R t i is affected by a number of factors e.g., the intrinsic transmissibility of a pathogen or the health care capacity at location i (which could influence for example the capacity to isolate cases). The model could be easily extended to explicitly incorporate the dependence of th.....
Document: where R t i is the reproduction number at location i at time t and p i→j is the probability of a case moving from location i to location j while they are infectious. R t i is affected by a number of factors e.g., the intrinsic transmissibility of a pathogen or the health care capacity at location i (which could influence for example the capacity to isolate cases). The model could be easily extended to explicitly incorporate the dependence of the reproduction number on such factors.
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