Selected article for: "infection rate and transmission model"

Author: Qihui Yang; Chunlin Yi; Aram Vajdi; Lee W Cohnstaedt; Hongyu Wu; Xiaolong Guo; Caterina M Scoglio
Title: Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China
  • Document date: 2020_3_30
  • ID: kcb68hue_34
    Snippet: To fit the model, we consider the COVID-19 epidemic outbreak starting in Wuhan City from January 19 th , because all confirmed cases reported in Hubei Province were in Wuhan City before January 19 th , 2020. To reduce the computational cost, the population of each city and population flows among the cities are scaled by 198, which is the number of cumulative confirmed cases in Hubei Province up to January 19 th . After scaling, the total number o.....
    Document: To fit the model, we consider the COVID-19 epidemic outbreak starting in Wuhan City from January 19 th , because all confirmed cases reported in Hubei Province were in Wuhan City before January 19 th , 2020. To reduce the computational cost, the population of each city and population flows among the cities are scaled by 198, which is the number of cumulative confirmed cases in Hubei Province up to January 19 th . After scaling, the total number of nodes in the network equals 298,838. In addition, as the criteria for counting the confirmed cases are changed on February 12 th , 2020, there is a jump in the reported number of confirmed cases in Hubei Province on February 13 th , 2020. Accordingly, by keeping = 0.33 day -1 and = 0.25 day -1 (average) unchanged, we fitted the transmission model to the cumulative number of confirmed cases in Hubei Province (Health Commission of Hubei Province, 2020), from January 19 th to February 12 th by tuning the infection rate ′ ( ). We then examine the future course of the epidemic under different scenarios.

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