Influence of Human Behavior on COVID-19 Dynamics Based on a Reaction–Diffusion Model

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作者
Shun Zhi
Hong-Tao Niu
You-Hui Su
Xiaoling Han
机构
[1] Shenyang University of Technology,School of Science
[2] Xuzhou University of Technology,School of Mathematics and Statistics
[3] Northwest Normal University,College of Mathematics and Statistics
关键词
Reaction–diffusion model; COVID-19; Human behavior change; Basic reproduction number; 35K57; 35B40; 37N25; 92D30;
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摘要
To investigate the influence of human behavior on the spread of COVID-19, we propose a reaction–diffusion model that incorporates contact rate functions related to human behavior. The basic reproduction number R0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {R}_{0}$$\end{document} is derived and a threshold-type result on its global dynamics in terms of R0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {R}_{0}$$\end{document} is established. More precisely, we show that the disease-free equilibrium is globally asymptotically stable if R0≤1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {R}_{0}\le 1$$\end{document}; while there exists a positive stationary solution and the disease is uniformly persistent if R0>1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {R}_{0}>1$$\end{document}. By the numerical simulations of the analytic results, we find that human behavior changes may lower infection levels and reduce the number of exposed and infected humans.
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