The introduction of population migration to SEIAR for COVID-19 epidemic modeling with an efficient intervention strategy

Min Chen; Miao Li; Yixue Hao; Zhongchun Liu; Long Hu; Lin Wang

doi:10.1016/j.inffus.2020.08.002

The introduction of population migration to SEIAR for COVID-19 epidemic modeling with an efficient intervention strategy

Inf Fusion. 2020 Dec:64:252-258. doi: 10.1016/j.inffus.2020.08.002. Epub 2020 Aug 6.

Authors

Min Chen¹, Miao Li¹, Yixue Hao¹, Zhongchun Liu², Long Hu¹, Lin Wang^{3

4}

Affiliations

¹ School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
² Department of Psychiatry, Renmin Hospital of Wuhan University, China.
³ Research Center for Tissue Engineering and Regenerative Medicine, China.
⁴ Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.

Abstract

In this paper, we present a mathematical model of an infectious disease according to the characteristics of the COVID-19 pandemic. The proposed enhanced model, which will be referred to as the SEIR (Susceptible-Exposed-Infectious-Recovered) model with population migration, is inspired by the role that asymptomatic infected individuals, as well as population movements can play a crucial role in spreading the virus. In the model, the infected and the basic reproduction numbers are compared under the influence of intervention policies. The experimental simulation results show the impact of social distancing and migration-in rates on reducing the total number of infections and the basic reproductions. And then, the importance of controlling the number of migration-in people and the policy of restricting residents' movements in preventing the spread of COVID-19 pandemic are verified.

Keywords: Basic reproduction number; COVID-19; Contact rate; Migration-in rate; SEIAR.