Dimension-reduction method for analysis of vaccination evolution with dynamic risk perception during epidemics

IF 4.4 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Applied Mathematical Modelling Pub Date : 2025-08-25 DOI:10.1016/j.apm.2025.116380

Yanyi Nie , Tao Lin , Wei Wang

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引用次数: 0

Abstract

We propose an epidemic-game coevolution model on higher-order networks to simulate the evolutionary dynamics of vaccination behavior in individuals with dynamic risk perception. In the model, the strategy updating of N individuals depends on their dynamic perception and response to both vaccination risk and higher-order infection risk. By introducing a dimension-reduction method, the N-dimensional vaccination dynamics described by the microscopic Markov chain approach are simplified into a one-dimensional equation, revealing that under weak selection intensity, the vaccination equilibrium tends to approach the optimal choice of fully rational individuals. Numerical simulations reveal that dynamic risk perception motivates individuals to consistently choose vaccination regardless of cost. Enhancing risk perception among a subset of individuals can trigger widespread vaccination behaviors in the population. Our analysis systematically explains how dynamic risk perception regulates behavioral evolution in an infectious environment.

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流行病期间具有动态风险感知的疫苗接种演变分析的降维方法

我们提出了一个高阶网络上的流行病-博弈协同进化模型来模拟具有动态风险感知的个体接种疫苗行为的进化动力学。在模型中，N个个体的策略更新取决于他们对疫苗接种风险和高阶感染风险的动态感知和反应。通过引入降维方法，将微观马尔可夫链方法描述的n维疫苗接种动力学简化为一维方程，揭示了弱选择强度下，疫苗接种均衡趋向于完全理性个体的最优选择。数值模拟表明，动态风险感知激励个体始终如一地选择疫苗接种而不考虑成本。增强一小部分人的风险认知可引发人群中广泛的疫苗接种行为。我们的分析系统地解释了动态风险感知如何在感染环境中调节行为进化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Mathematical Modelling 数学-工程：综合

CiteScore

9.80

自引率

8.00%

发文量

508

审稿时长

43 days

期刊介绍： Applied Mathematical Modelling focuses on research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. A significant emerging area of research activity involves multiphysics processes, and contributions in this area are particularly encouraged. This influential publication covers a wide spectrum of subjects including heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimization; finite volume, finite element, and boundary element procedures; modelling of inventory, industrial, manufacturing and logistics systems for viable decision making; civil engineering systems and structures; mineral and energy resources; relevant software engineering issues associated with CAD and CAE; and materials and metallurgical engineering. Applied Mathematical Modelling is primarily interested in papers developing increased insights into real-world problems through novel mathematical modelling, novel applications or a combination of these. Papers employing existing numerical techniques must demonstrate sufficient novelty in the solution of practical problems. Papers on fuzzy logic in decision-making or purely financial mathematics are normally not considered. Research on fractional differential equations, bifurcation, and numerical methods needs to include practical examples. Population dynamics must solve realistic scenarios. Papers in the area of logistics and business modelling should demonstrate meaningful managerial insight. Submissions with no real-world application will not be considered.