Dynamic analysis of a SEAIRS model on co-evolution of human behavior changes in COVID-19 epidemic

Xiaoyu Li; Nan Wang; Zhiming Li; Xiaoyu Li; Nan Wang; Zhiming Li

doi:10.3934/mbe.2026072

Mathematical Biosciences and Engineering

2026, Volume 23, Issue 7: 1971-1994. doi: 10.3934/mbe.2026072

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Research article

Dynamic analysis of a SEAIRS model on co-evolution of human behavior changes in COVID-19 epidemic

1.
Basic Teaching Department, Xinjiang University of Political Science and Law, Tumushuke 843900, China
2.
College of Mathematics and System Science, Xinjiang University, Urumqi 830017, China

Received: 15 February 2026 Revised: 30 April 2026 Accepted: 01 June 2026 Published: 02 July 2026

Considering that people usually take non-drug protective measures (making behavior changes), this paper proposes a new SEAIRS model by combining behavior changes during the spread of the COVID-19 epidemic. First, we prove the positivity and boundedness of the solution of the model. Furthermore, the existence and stability of the equilibrium points are discussed in three behavior scenarios $ (B_c = 0, \ B_c = 1, \ 0 < B_c < 1, $ where $ B_c $ represents the proportion of susceptible individuals ($ S $), exposed individuals ($ E $), and asymptomatic infected individuals ($ A $) who adopt preventive behavior changes). Finally, we illustrate the model's behaviour using COVID-19 data from Romania, and summarize some valuable results: (i) the spread of diseases can be effectively controlled by reducing the contact between susceptible, exposed, and infected individuals; (ii) increasing the proportion of behavioral changes can significantly reduce the number of infected individuals. The model suggests two main theoretical measures to promote behavior changes within the framework: one is to increase the return difference between the two behaviors by adjusting relevant parameters, and the other is to increase the value of the information function.
- COVID-19 epidemic,
- SEAIRS model,
- behavior change,
- globally asymptotically stable
Citation: Xiaoyu Li, Nan Wang, Zhiming Li. Dynamic analysis of a SEAIRS model on co-evolution of human behavior changes in COVID-19 epidemic[J]. Mathematical Biosciences and Engineering, 2026, 23(7): 1971-1994. doi: 10.3934/mbe.2026072

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Abstract

Considering that people usually take non-drug protective measures (making behavior changes), this paper proposes a new SEAIRS model by combining behavior changes during the spread of the COVID-19 epidemic. First, we prove the positivity and boundedness of the solution of the model. Furthermore, the existence and stability of the equilibrium points are discussed in three behavior scenarios $ (B_c = 0, \ B_c = 1, \ 0 < B_c < 1, $ where $ B_c $ represents the proportion of susceptible individuals ($ S $), exposed individuals ($ E $), and asymptomatic infected individuals ($ A $) who adopt preventive behavior changes). Finally, we illustrate the model's behaviour using COVID-19 data from Romania, and summarize some valuable results: (i) the spread of diseases can be effectively controlled by reducing the contact between susceptible, exposed, and infected individuals; (ii) increasing the proportion of behavioral changes can significantly reduce the number of infected individuals. The model suggests two main theoretical measures to promote behavior changes within the framework: one is to increase the return difference between the two behaviors by adjusting relevant parameters, and the other is to increase the value of the information function.

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