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

• Published in: Mathematical biosciences and engineering : MBE Vol. 17; no. 4; pp. 3040 - 3051
• Main Authors: Liu, Zhihua, Magal, Pierre, Seydi, Ousmane, Webb, Glenn
• Format: Journal Article
• Language: English
• Published: United States AIMS Press 08.04.2020
• Subjects: Asymptomatic Infections - epidemiology; Basic Reproduction Number - statistics & numerical data; Betacoronavirus; China - epidemiology; Computer Simulation; corona virus; Coronavirus Infections - epidemiology; Coronavirus Infections - prevention & control; Coronavirus Infections - transmission; COVID-19; epidemic mathematical model; Epidemics - prevention & control; Epidemics - statistics & numerical data; Humans; isolation; Mathematical Concepts; Models, Biological; Pandemics - prevention & control; Pandemics - statistics & numerical data; Pneumonia, Viral - epidemiology; Pneumonia, Viral - prevention & control; Pneumonia, Viral - transmission; public closings; quarantine; Quarantine - statistics & numerical data; reported and unreported cases; SARS-CoV-2; Time Factors; China; public closings; reported and unreported cases; isolation; quarantine; epidemic mathematical model; corona virus
• ISSN: 1551-0018; 1551-0018
• DOI: 10.3934/mbe.2020172

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.