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

Zhihua Liu; Pierre Magal; Ousmane Seydi; Glenn Webb; Zhihua Liu; Pierre Magal; Ousmane Seydi; Glenn Webb

doi:10.3934/mbe.2020172

Mathematical Biosciences and Engineering

2020, Volume 17, Issue 4: 3040-3051. doi: 10.3934/mbe.2020172

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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

Received: 11 March 2020 Accepted: 26 March 2020 Published: 07 April 2020

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.
- 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[J]. Mathematical Biosciences and Engineering, 2020, 17(4): 3040-3051. doi: 10.3934/mbe.2020172

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Abstract

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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