A mathematical model for the novel coronavirus epidemic in Wuhan, China

Chayu Yang; Jin Wang; Chayu Yang; Jin Wang

doi:10.3934/mbe.2020148

Mathematical Biosciences and Engineering

2020, Volume 17, Issue 3: 2708-2724. doi: 10.3934/mbe.2020148

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A mathematical model for the novel coronavirus epidemic in Wuhan, China

Chayu Yang ,
Jin Wang ^,

Department of Mathematics, University of Tennessee at Chattanooga, 615 McCallie Ave., Chattanooga, TN 37403, USA

Received: 15 February 2020 Accepted: 09 March 2020 Published: 11 March 2020

We propose a mathematical model to investigate the current outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Our model describes the multiple transmission pathways in the infection dynamics, and emphasizes the role of the environmental reservoir in the transmission and spread of this disease. Our model also employs non-constant transmission rates which change with the epidemiological status and environmental conditions and which reflect the impact of the on-going disease control measures. We conduct a detailed analysis of this model, and demonstrate its application using publicly reported data. Among other findings, our analytical and numerical results indicate that the coronavirus infection would remain endemic, which necessitates long-term disease prevention and intervention programs.
- COVID-19,
- compartmental modeling,
- basic reproduction number
Citation: Chayu Yang, Jin Wang. A mathematical model for the novel coronavirus epidemic in Wuhan, China[J]. Mathematical Biosciences and Engineering, 2020, 17(3): 2708-2724. doi: 10.3934/mbe.2020148

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Abstract

We propose a mathematical model to investigate the current outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Our model describes the multiple transmission pathways in the infection dynamics, and emphasizes the role of the environmental reservoir in the transmission and spread of this disease. Our model also employs non-constant transmission rates which change with the epidemiological status and environmental conditions and which reflect the impact of the on-going disease control measures. We conduct a detailed analysis of this model, and demonstrate its application using publicly reported data. Among other findings, our analytical and numerical results indicate that the coronavirus infection would remain endemic, which necessitates long-term disease prevention and intervention programs.

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