College of Mathematics and Systems Science, Xinjiang University, Urumqi 830017, China.
Math Biosci Eng. 2023 Jul 28;20(9):15641-15671. doi: 10.3934/mbe.2023698.
In this paper, we propose a SVEIR-I epidemic model with media coverage in a spatially heterogeneous environment, and study the role of media coverage in the spread of diseases in a spatially heterogeneous environment. In a spatially heterogeneous environment, we first set up the well-posedness of the model. Then, we define the basic reproduction number $ R_0 $ of the model and establish the global dynamic threshold criteria: when $ R_0 < 1 $, disease-free steady state is globally asymptotically stable, while when $ R_0 > 1 $, the model is uniformly persistent. In addition, the existence and uniqueness of the equilibrium state of endemic diseases were obtained when $ R_0 > 1 $ in homogeneous space and heterogeneous diffusion environment. Further, by constructing appropriate Lyapunov functions, the global asymptotic stability of disease-free and positive steady states was established. Finally, through numerical simulations, it is shown that spatial heterogeneity can increase the risk of disease transmission, and can even change the threshold for disease transmission; media coverage can make people more widely understand disease information, and then reduce the effective contact rate to control the spread of disease.
本文提出了一个具有媒体报道的 SVEIR-I 传染病模型,在空间异质环境中研究媒体报道在疾病传播中的作用。在空间异质环境中,我们首先建立了模型的适定性。然后,我们定义了模型的基本再生数 $ R_0 $,并建立了全局动态阈值准则:当 $ R_0 < 1 $ 时,无病平衡点全局渐近稳定,而当 $ R_0 > 1 $ 时,模型一致持续存在。此外,在均匀扩散环境和空间同质环境中,当 $ R_0 > 1 $ 时,得到了地方病平衡点的存在唯一性。进一步地,通过构造适当的李雅普诺夫函数,建立了无病和正平衡点的全局渐近稳定性。最后,通过数值模拟表明,空间异质性会增加疾病传播的风险,甚至可以改变疾病传播的阈值;媒体报道可以使人们更广泛地了解疾病信息,从而降低有效接触率以控制疾病的传播。