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  4. Vol 3, Issue 4, 2023

Improvement of SEIR Epidemic Dynamics Model and Its Matlab Implementation

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DOI: 10.23977/phpm.2023.030408 | Downloads: 12 | Views: 362

Author(s)

Yue Yan 1, Hao Zhu 1, Xiangkui Li 2, Xiaopan Li 1, Xuan Zhang 1, Dingguo Li 1

Affiliation(s)

1 College of Physics and Information Engineering, Zhaotong University, Zhaotong, 657000, China
2 College of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China

Corresponding Author

Xiangkui Li

ABSTRACT

In the context of resuming education, the application of infectious disease dynamics models can describe the transmission mechanism of infectious disease viruses. This article is based on the SEIR infectious disease dynamics model, and based on the description of the entire process of susceptible individuals from infection to isolation and transformation, establishes an infectious disease dynamics model suitable for analyzing the evaluation of rehabilitation and death populations. At the same time, this article introduces two major influencing factors, namely intervention and control by schools or governments, and virus mutation, to discover changes in the population in various states in the model. This change provides favorable strategies for guiding infectious disease prevention and control. The algorithm simulation shows the feasibility of the proposed method in the risk assessment of infectious diseases, which can provide theoretical decision-making basis for controlling the spread of diseases and also provide theoretical basis for the decision to resume work, production, and study. This risk assessment is not only applicable to COVID-19, but also can play the role of risk assessment in various epidemics.

KEYWORDS

Infectious disease dynamics model, SEIDR model, virus mutation, intervention and control, exposed

CITE THIS PAPER

Yue Yan, Hao Zhu, Xiangkui Li, Xiaopan Li, Xuan Zhang, Dingguo Li, Improvement of SEIR Epidemic Dynamics Model and Its Matlab Implementation. MEDS Public Health and Preventive Medicine (2023) Vol. 3: 49-58. DOI: http://dx.doi.org/10.23977/phpm.2023.030408.

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