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_14
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03. 11.20034363 doi: medRxiv preprint where C(t) represents the cumulative number of cases at time t, r is the growth rate at the early stage, and K is the final epidemic size. ∈ [0,1] is a parameter that allows the model to capture different growth profiles including the constant incidence ( = 0), sub-exponential growth (0 < < 1 ) and exp.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03. 11.20034363 doi: medRxiv preprint where C(t) represents the cumulative number of cases at time t, r is the growth rate at the early stage, and K is the final epidemic size. ∈ [0,1] is a parameter that allows the model to capture different growth profiles including the constant incidence ( = 0), sub-exponential growth (0 < < 1 ) and exponential growth ( = 1 ). The exponent α measures the deviation from the symmetric s-shaped dynamics of the simple logistic curve. The model recovers the original Richards model for = 1, and reduces to the generalized logistic model [17] for α = 1 and =
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