Selected article for: "ahead forecasting and epidemic phase"

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_155
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . Table 1 : Percentage of weeks with observed incidence in 95% forecast interval. In forecasting ahead, we assumed transmissibility to be constant over the forecast horizon. If the 97.5th percentile of the R estimate used for forecasting was less than 1, we defined the epidemic to be in the declining phase during this period. Similarly, if the 2.5th percentile of R was gr.....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . Table 1 : Percentage of weeks with observed incidence in 95% forecast interval. In forecasting ahead, we assumed transmissibility to be constant over the forecast horizon. If the 97.5th percentile of the R estimate used for forecasting was less than 1, we defined the epidemic to be in the declining phase during this period. Similarly, if the 2.5th percentile of R was greater than 1, we defined the epidemic to be in a growing phase. The phase was set to stable where the 95% Credible Interval of the R estimates contained 1.

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