Dynamical behaviors of a stochastic SIR epidemic model with reaction–diffusion and spatially heterogeneous transmission rate

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2025-03-21 DOI:10.1016/j.chaos.2025.116283
Tan Su, Yonggui Kao, Daqing Jiang
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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.
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Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
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.
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