Selected article for: "forward predict and previous work"
Author: pierre magal; Glenn Webb
Title: Predicting the number of reported and unreported cases for the COVID-19 epidemic in South Korea, Italy, France and Germany
  • Document date: 2020_3_24
    • ID: 9zeqigqa_1
    Snippet: In a previous work [2] , we developed a model of the COVID-19 epidemic in China. The purpose of the model was to predict forward in time the future number of cases in a time-line of the epidemic from early reported case data. The model in [2] focused on the Chinese government imposed public policies designed to contain the epidemic. Our goal here is to apply this analysis to the COVID-19 epidemics in South Korea, Italy, France, and Germany. In an.....
    Document: In a previous work [2] , we developed a model of the COVID-19 epidemic in China. The purpose of the model was to predict forward in time the future number of cases in a time-line of the epidemic from early reported case data. The model in [2] focused on the Chinese government imposed public policies designed to contain the epidemic. Our goal here is to apply this analysis to the COVID-19 epidemics in South Korea, Italy, France, and Germany. In an early phase of the epidemic, the reported case data grows exponentially, which corresponds to a constant transmission rate. We assume that government measures and public awareness cause this early constant transmission rate to change to a time dependent exponentially decreasing rate. We identify the early constant transmission rate using a method developed in [1] . We then identify the time dependent exponentially decreasing transmission rate from reported case data, and project forward the time-line of the epidemic course. We refer to [3, 4] for more results about this topic.

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