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_25
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint .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 with the data and GRM. The dispersion among these 500 scenarios provides a measure of stability of the fits and their range of values gives an estimation of the confidence intervals. The first conclusion is the non-surprising large range of scenarios obtained when using data before the maximum, which how.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint .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 with the data and GRM. The dispersion among these 500 scenarios provides a measure of stability of the fits and their range of values gives an estimation of the confidence intervals. The first conclusion is the non-surprising large range of scenarios obtained when using data before the maximum, which however encompass the realized data. We observe a tendency for early scenarios to predict a much faster and larger number of new cases than observed, which could be expected in the absence of strong containment control. With more data, the scenarios become more accurate, especially when using realized data after the peak, and probably account now well for the impact of the containment measures that modified the dynamics of the epidemic spreading.
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