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Analysis and Research on the Progress of Epidemiological Dynamics based on SEIRS Predictive Model

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DOI: 10.23977/phpm.2021.010106 | Downloads: 6 | Views: 687


Zhenyuan Hu 1, Luping Wang 2, Changwei Li 1, Defeng Wen 1


1 School of Aeronautical Engine, Shenyang University of Aeronautics and Astronautics, Shenyang, Liaoning, 110000
2 Shenyang University of Aerospace Engineering Training Center, Shenyang, Liaoning, 110000

Corresponding Author

Luping Wang


In this paper, based on the nonlinear mathematical model SEIRS model, we describe the random transition between susceptibility, latent, morbidity and cure of the dynamic behavior of people under the action of infectious diseases. We select the infection rate, the number of contacts, the cure rate, mortality, immune cycle and other factors to solve the problem of the change of the number of patients in the system when the average number of people exposed to the initial latent person is different. By using dynamic simulation, it is concluded that the average number of contacts increases and the number of patients increases in the same cycle.


dynamic transmission model, SEIRS model, dynamic simulation, COVID-19 epidemic situation


Zhenyuan Hu, Luping Wang, Changwei Li, Defeng Wen. Analysis and Research on the Progress of Epidemiological Dynamics based on SEIRS Predictive Model. MEDS Public Health and Preventive Medicine (2021) 1: 36-40. DOI:


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