1. Spatial dynamic analysis for COVID-19 epidemic model with diffusion and Beddington-DeAngelis type incidence
- Author
-
Yantao Luo, Long Zhang, Zhidong Teng, Tao Zheng, and Xinran Zhou
- Subjects
Discrete mathematics ,Coronavirus disease 2019 (COVID-19) ,Applied Mathematics ,Homogeneity (statistics) ,Stability theory ,Reaction–diffusion system ,General Medicine ,Type (model theory) ,Diffusion (business) ,Epidemic model ,Analysis ,Mathematics ,Incidence (geometry) - Abstract
A diffusion SEIAR model with Beddington-DeAngelis type incidence is proposed to characterize the spread of COVID-19 with spatial transmission. First, the well-posedness of solution is studied. Second, the basic reproduction number \begin{document}$ \mathcal R_{0} $\end{document} is derived and served as a threshold value to determine whether COVID-19 will spread. Meanwhile, we consider the effect of diffusion on the spread of COVID-19 in spatial homogenous environment, by which we can obtain that if \begin{document}$ \mathcal R_{0} , then the infection-free steady state is globally asymptotically stable, while if \begin{document}$ \mathcal R_{0}>1 $\end{document} , then the endemic steady state is globally asymptotically stable. Furthermore, according to the official reporting data about COVID-19 in Wuhan, China, the actual value of \begin{document}$ \mathcal R_{0} $\end{document} is estimated, and comparing with other types of incidence, we find that the estimated peak with Beddington-DeAngelis type incidence is more close to the cases in reality. Finally, by numerical simulations, we can see that the diffusion behavior has evident impact on the spread of COVID-19 in spatial heterogeneity than homogeneity of environment.
- Published
- 2023