Author: White, Laura F; Moser, Carlee B; Thompson, Robin N; Pagano, Marcello
Title: Statistical Estimation of the Reproductive Number From Case Notification Data. Cord-id: nqh5y1a5 Document date: 2020_10_9
ID: nqh5y1a5
Snippet: The reproductive number, or reproduction number, is a valuable metric in understanding infectious disease dynamics. There is a large body of literature related to its use and estimation. In the last 15 years, there has been tremendous progress in statistically estimating this number using case notification data. These approaches are appealing because they are relevant in an ongoing outbreak (e.g., for assessing the effectiveness of interventions) and do not require substantial modelling expertis
Document: The reproductive number, or reproduction number, is a valuable metric in understanding infectious disease dynamics. There is a large body of literature related to its use and estimation. In the last 15 years, there has been tremendous progress in statistically estimating this number using case notification data. These approaches are appealing because they are relevant in an ongoing outbreak (e.g., for assessing the effectiveness of interventions) and do not require substantial modelling expertise to be implemented. In this review, we describe these methods and the extensions that have been developed. We provide insight into the distinct interpretations of the estimators proposed and provide real data examples to illustrate how they are implemented. Finally we conclude with a discussion of available software and opportunities for future development.
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