Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Predicting the Cumulative Number of Cases for the COVID-19 Epidemic in China From Early Data

Version 1 : Received: 24 February 2020 / Approved: 25 February 2020 / Online: 25 February 2020 (07:38:24 CET)

How to cite: Liu, Z.; Magal, P.; Seydi, O.; Webb, G. Predicting the Cumulative Number of Cases for the COVID-19 Epidemic in China From Early Data. Preprints 2020, 2020020365 (doi: 10.20944/preprints202002.0365.v1). Liu, Z.; Magal, P.; Seydi, O.; Webb, G. Predicting the Cumulative Number of Cases for the COVID-19 Epidemic in China From Early Data. Preprints 2020, 2020020365 (doi: 10.20944/preprints202002.0365.v1).

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.

Subject Areas

corona virus; reported and unreported cases; isolation; quarantine; public closings; epidemic mathematical model

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