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<p>With the development of disease transmission dynamics, the role of an individual’s surrounding environment in the transmission process has garnered increasing attention. To address these dynamics, this paper establishes a three-layered coupled network model incorporating mass media, and examines the impact of multiple local influences on co-evolution processes of information, behavior, and disease transmission. These multiple local influences include pairwise local influences and higher-order local influences. The model innovatively introduces the mass media as a special node, to form a special 2-simplex structure, and analyzes its impact on the process of information dynamic, thereby deepening the understanding of the multiple local influences. The information layer model portrays the dynamics of negative and positive information, and evaluates how multiple local influences shape individuals’ willingness to receive information. The behavioral layer depicts the individuals’ behavioral decision-making process to vaccinate, and consider the combined effects of information dissemination and multiple local influences on willingness to vaccinate. The disease layer model illustrates the dynamics of disease, and consider the effect of vaccination on individual susceptibility. The model is investigated through Microscopic Markov Chain Approach (MMCA) and each state transition equation is constructed, and deduce the threshold of disease transmission. Comprehensive Monte Carlo (MC) simulations were conducted to validate our theoretical findings. The simulation findings illustrate that the mass media can not only reduce the proportion of disease transmission by regularly disseminating positive information, but more importantly, the special 2-simplex local environment it constructs can effectively suppress the epidemic. Compared with the purely pairwise local effects, the combined effect of multiple local environments can suppress disease more significantly. This study focuses on the inhibitory effect of multiple local environments on disease transmission, and finds that the special local environment shaped by mass media has unique advantages in disease prevention and control. This finding highlights the importance of regulating multiple local environmental factors toward more efficient disease control and prevention strategies, and provides new ideas for future epidemic prevention and control efforts.</p>

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Co-evolution of information, behavior and epidemic transmission under multiple local influences in multiplex networks

  • 期刊论文

  • 发表日期：

    2025年6月12日

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  • Bingjie Wu,
  • Liang’an Huo,
  • Laijun Zhao

摘要

With the development of disease transmission dynamics, the role of an individual’s surrounding environment in the transmission process has garnered increasing attention. To address these dynamics, this paper establishes a three-layered coupled network model incorporating mass media, and examines the impact of multiple local influences on co-evolution processes of information, behavior, and disease transmission. These multiple local influences include pairwise local influences and higher-order local influences. The model innovatively introduces the mass media as a special node, to form a special 2-simplex structure, and analyzes its impact on the process of information dynamic, thereby deepening the understanding of the multiple local influences. The information layer model portrays the dynamics of negative and positive information, and evaluates how multiple local influences shape individuals’ willingness to receive information. The behavioral layer depicts the individuals’ behavioral decision-making process to vaccinate, and consider the combined effects of information dissemination and multiple local influences on willingness to vaccinate. The disease layer model illustrates the dynamics of disease, and consider the effect of vaccination on individual susceptibility. The model is investigated through Microscopic Markov Chain Approach (MMCA) and each state transition equation is constructed, and deduce the threshold of disease transmission. Comprehensive Monte Carlo (MC) simulations were conducted to validate our theoretical findings. The simulation findings illustrate that the mass media can not only reduce the proportion of disease transmission by regularly disseminating positive information, but more importantly, the special 2-simplex local environment it constructs can effectively suppress the epidemic. Compared with the purely pairwise local effects, the combined effect of multiple local environments can suppress disease more significantly. This study focuses on the inhibitory effect of multiple local environments on disease transmission, and finds that the special local environment shaped by mass media has unique advantages in disease prevention and control. This finding highlights the importance of regulating multiple local environmental factors toward more efficient disease control and prevention strategies, and provides new ideas for future epidemic prevention and control efforts.