2019年冠状病毒病(COVID-19)
入射(几何)
基本再生数
扩散
流行病模型
同质性(统计学)
数学
空间异质性
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
稳态(化学)
价值(数学)
应用数学
数学分析
统计
物理
人口学
生物
人口
几何学
医学
量子力学
化学
传染病(医学专业)
物理化学
疾病
社会学
病理
生态学
作者
Tao Zheng,Yantao Luo,Zhou Xinran,Long Zhang,Zhidong Teng
出处
期刊:Communications on Pure and Applied Analysis
[American Institute of Mathematical Sciences]
日期:2023-01-01
卷期号:22 (2): 365-396
被引量:5
摘要
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 $ \mathcal R_{0} $ 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 $ \mathcal R_{0}<1 $, then the infection-free steady state is globally asymptotically stable, while if $ \mathcal R_{0}>1 $, 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 $ \mathcal R_{0} $ 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI