Mathematical modeling of transmission dynamics of COVID-19

Shuqi Wang; Wen Tang; Liyan Xiong; Mengyu Fang; Bingsong Zhang; Chi-Yang Chiu; Ruzong Fan; Shuqi Wang; Wen Tang; Liyan Xiong; Mengyu Fang; Bingsong Zhang; Chi-Yang Chiu; Ruzong Fan

doi:10.3934/bdia.2021002

Big Data and Information Analytics

2021, Volume 6, 12-25. doi: 10.3934/bdia.2021002

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Research article

Mathematical modeling of transmission dynamics of COVID-19

1.
Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Reservoir Rd., N.W., Washington, DC 20057, USA
2.
Division of Biostatistics, Department of Preventive Medicine, University of Tennessee Health Science Center, 66 N. Pauline Street, Memphis, TN 38163, USA

Received: 21 October 2020 Accepted: 08 March 2021 Published: 15 March 2021

The emergence of coronavirus disease 2019 (COVID-19) demonstrates the importance of research on understanding and accurately modeling the transmission and spread of pandemic. In this paper, we consider a susceptible-exposed-infected-recovered-deceased (SEIRD) system of differential equations to describe relationship among the number of susceptible individuals, the number of exposed individuals who are transmitting the virus, the number of infected individuals among the exposed people, the number of recovered individuals from those infected, and the number of deaths from those infected in a town, state or country. Based on the empirical results of transmission process of COVID-19 in the United States from April 16th to June 30th, 2020, we consider a few cases of contact rate, incidence rate, recovery rate, and mortality rate to model the transmission and dynamics of the virus. Numerical analysis and analytical method are used to explore the dynamics and prediction of the pandemic.
- COVID-19,
- incidence rate,
- mortality rate,
- susceptible-infected-recovered models,
- susceptible-exposed-infected-recovered-deceased models
Citation: Shuqi Wang, Wen Tang, Liyan Xiong, Mengyu Fang, Bingsong Zhang, Chi-Yang Chiu, Ruzong Fan. Mathematical modeling of transmission dynamics of COVID-19[J]. Big Data and Information Analytics, 2021, 6: 12-25. doi: 10.3934/bdia.2021002

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Abstract

The emergence of coronavirus disease 2019 (COVID-19) demonstrates the importance of research on understanding and accurately modeling the transmission and spread of pandemic. In this paper, we consider a susceptible-exposed-infected-recovered-deceased (SEIRD) system of differential equations to describe relationship among the number of susceptible individuals, the number of exposed individuals who are transmitting the virus, the number of infected individuals among the exposed people, the number of recovered individuals from those infected, and the number of deaths from those infected in a town, state or country. Based on the empirical results of transmission process of COVID-19 in the United States from April 16th to June 30th, 2020, we consider a few cases of contact rate, incidence rate, recovery rate, and mortality rate to model the transmission and dynamics of the virus. Numerical analysis and analytical method are used to explore the dynamics and prediction of the pandemic.

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