Author: Ke Wu; Didier Darcet; Qian Wang; Didier Sornette
Title: Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world Document date: 2020_3_16
ID: 9607dy2o_72
Snippet: The generalized growth model (6) allows for a sub-exponential growth of the outbreak in the early stage (for p < 1), but cannot describe the decay of the incidence rate. It thus serves as a rough upper limit, obtained by assuming that the outbreak continues to grow following the same process as in the past. The generalized Logistic model (5) and Logistic growth model (4) both assume a logistic decay of the growth rate as the total number of confi.....
Document: The generalized growth model (6) allows for a sub-exponential growth of the outbreak in the early stage (for p < 1), but cannot describe the decay of the incidence rate. It thus serves as a rough upper limit, obtained by assuming that the outbreak continues to grow following the same process as in the past. The generalized Logistic model (5) and Logistic growth model (4) both assume a logistic decay of the growth rate as the total number of confirmed cases increases. Note that they are nested in the generalized Richards model (1), by fixing respectively = 1 and = 1; p = 1 .
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