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Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data

1 School of Mathematical Sciences, Beijing Normal University. Beijing 100875, China
2 Université de Bordeaux, IMB, UMR 5251, F-33400 Talence, France
3 CNRS, IMB, UMR 5251, F-33400 Talence, France
4 Département Tronc Commun, École Polytechnique de Thiès, Sénégal
5 Mathematics Department, Vanderbilt University, Nashville, TN, USA

Special Issues: Modeling the Biological, Epidemiological, Immunological, Molecular, Virological Aspects of COVID-19

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.
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Keywords corona virus; reported and unreported cases; isolation; quarantine; public closings; epidemic mathematical model

Citation: Zhihua Liu, Pierre Magal, Ousmane Seydi, Glenn Webb. Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data. Mathematical Biosciences and Engineering, 2020, 17(4): 3040-3051. doi: 10.3934/mbe.2020172


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