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Coupled epidemic dynamics with awareness heterogeneity in multiplex networks

Author

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  • Xu, Jiwei
  • Li, Jincheng
  • Han, Zhen
  • Zhu, Peican

Abstract

The diffusion of individual awareness has a significant impact on the dynamic spread of epidemics. In previous studies, the individual’s state of awareness is mainly divided into two states: awareness and unawareness. However, in the real world, the factors that change the awareness state of individuals with different health states are often different, and there are differences when they are aware of the epidemic. In order to study the influence of the strength of awareness on epidemic transmission, this article proposes a two-layer network epidemic transmission model based on the individual health state. The upper-layer network constructs an APA (Asthenic awareness - Powerful awareness - Asthenic awareness) propagation model, which is used to represent the diffusion process of information about epidemic awareness. Meanwhile, the epidemic pain level is introduced to describe the awareness changes in infected persons. The lower-layer network adopts the SIS (Susceptible–Infected–Susceptible) virus model to describe the epidemic transmission process influenced by awareness information. Then we validate the efficiency of the proposed two-layer network propagation model through Monte Carlo numerical simulation. The epidemic threshold is determined using the microscopic Markov chain approach (MMCA), while analyzing key factors such as the epidemic pain level, the attenuation factor and network topology. The results demonstrate that individuals with powerful awareness exhibit a more pronounced inhibitory effect on the spread of the epidemic. Furthermore, individuals who are more sensitive to the pain of the epidemic are better at sustaining powerful awareness, thereby facilitating more effective containment of the epidemic. The systematic findings of this study provide valuable insights for exploring the interplay between individual awareness and epidemic transmission in real-world scenarios.

Suggested Citation

  • Xu, Jiwei & Li, Jincheng & Han, Zhen & Zhu, Peican, 2024. "Coupled epidemic dynamics with awareness heterogeneity in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:chsofr:v:187:y:2024:i:c:s0960077924008877
    DOI: 10.1016/j.chaos.2024.115335
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    References listed on IDEAS

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