{"title":"Dynamical behaviors of a stochastic SIR epidemic model with reaction–diffusion and spatially heterogeneous transmission rate","authors":"Tan Su, Yonggui Kao, Daqing Jiang","doi":"10.1016/j.chaos.2025.116283","DOIUrl":null,"url":null,"abstract":"<div><div>Much effort has been paid to epidemic models built by ordinary differential equations (ODEs), partial differential equations (PDEs), or stochastic differential equations (SDEs) and received remarkable achievement. Different from these models, we establish and analyze a SIR epidemic model by using stochastic partial differential equations (SPDEs) in this paper, which incorporates the influence of inevitable population diffusion, spatial heterogeneity, and environmental perturbation. For this model, the existence and uniqueness of the global positive solution is first proved through an innovative variable transformation approach. Then, we establish the sufficient condition for the existence of the Infected class by constructing suitable Lyapunov functions. The exponential extinction of disease is also investigated. More importantly, the exact expression of the probability density function near the equilibrium is obtained by theoretical analysis and matrix calculation. Further, we perform several numerical simulations to illustrate theoretical results. Finally, the corresponding conclusions and prospects are discussed.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"195 ","pages":"Article 116283"},"PeriodicalIF":5.3000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960077925002966","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Much effort has been paid to epidemic models built by ordinary differential equations (ODEs), partial differential equations (PDEs), or stochastic differential equations (SDEs) and received remarkable achievement. Different from these models, we establish and analyze a SIR epidemic model by using stochastic partial differential equations (SPDEs) in this paper, which incorporates the influence of inevitable population diffusion, spatial heterogeneity, and environmental perturbation. For this model, the existence and uniqueness of the global positive solution is first proved through an innovative variable transformation approach. Then, we establish the sufficient condition for the existence of the Infected class by constructing suitable Lyapunov functions. The exponential extinction of disease is also investigated. More importantly, the exact expression of the probability density function near the equilibrium is obtained by theoretical analysis and matrix calculation. Further, we perform several numerical simulations to illustrate theoretical results. Finally, the corresponding conclusions and prospects are discussed.
人们在利用常微分方程(ODE)、偏微分方程(PDE)或随机微分方程(SDE)建立流行病模型方面做了大量工作,并取得了显著成果。与这些模型不同,本文利用随机偏微分方程(SPDEs)建立并分析了一个 SIR 流行病模型,该模型纳入了不可避免的种群扩散、空间异质性和环境扰动的影响。对于该模型,首先通过创新的变量变换方法证明了全局正解的存在性和唯一性。然后,我们通过构建合适的 Lyapunov 函数,建立了感染类存在的充分条件。我们还研究了疾病的指数消亡。更重要的是,我们通过理论分析和矩阵计算得到了平衡附近概率密度函数的精确表达式。此外,我们还进行了多次数值模拟,以说明理论结果。最后,讨论了相应的结论和展望。
期刊介绍:
Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.