Epidemic spread dynamics in multilayer networks: Probing the impact of information outbreaks and reception games

The co-evolution of epidemic and information spread within multilayer networks is a current hot topic in network science. During epidemic outbreaks, the accompanying information exhibits both outbreak and reception game behaviors; yet, these complex phenomena have been scarcely addressed in existing research. In this paper, we model information outbreaks using activated individuals who transmit messages to their neighbors, while also considering the game behaviors of information receivers. By focusing on these two factors, we establish a multilayer network model featuring both information outbreaks and reception games. Employing the microscopic Markov chain method, we analyze the propagation dynamics within this network and derive epidemic thresholds, corroborating these results with Monte Carlo simulations. Our findings indicate that information outbreaks suppress epidemic outbreaks, whereas increased costs of information reception promote epidemic spread. Smooth information dissemination further inhibits the transmission of the epidemic. Additionally, we observe that heterogeneity in the network structure between the virtual and physical layers reduces the ultimate scale of epidemic infection, with the virtual layer exerting a more substantial influence. These insights are crucial for elucidating the co-evolutionary mechanisms of spread within multilayer networks and for developing effective epidemic prevention and control strategies.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0236359
Citations
6
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
6.62

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article

Epidemic spread dynamics in multilayer networks: Probing the impact of information outbreaks and reception games

Huang He, Jianbo Wang, Zhanwei Du, Ping Li et al.
6 citations
Chaos An Interdisciplinary Journal of Nonlinear Science
Complex Network Analysis Techniques
6.62
article

Epidemic spread dynamics in multilayer networks: Probing the impact of information outbreaks and reception games

Huang He, Jianbo Wang, Zhanwei Du, Ping Li, Xiaoke Xu
article en
6 citations

Abstract

The co-evolution of epidemic and information spread within multilayer networks is a current hot topic in network science. During epidemic outbreaks, the accompanying information exhibits both outbreak and reception game behaviors; yet, these complex phenomena have been scarcely addressed in existing research. In this paper, we model information outbreaks using activated individuals who transmit messages to their neighbors, while also considering the game behaviors of information receivers. By focusing on these two factors, we establish a multilayer network model featuring both information outbreaks and reception games. Employing the microscopic Markov chain method, we analyze the propagation dynamics within this network and derive epidemic thresholds, corroborating these results with Monte Carlo simulations. Our findings indicate that information outbreaks suppress epidemic outbreaks, whereas increased costs of information reception promote epidemic spread. Smooth information dissemination further inhibits the transmission of the epidemic. Additionally, we observe that heterogeneity in the network structure between the virtual and physical layers reduces the ultimate scale of epidemic infection, with the virtual layer exerting a more substantial influence. These insights are crucial for elucidating the co-evolutionary mechanisms of spread within multilayer networks and for developing effective epidemic prevention and control strategies.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 35(3)
Southwest Petroleum University (CN), Beijing Normal University (CN), University of Hong Kong (HK)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province, Beijing Municipal Natural Science Foundation
Good health and well-being
Openalex Percentile: Top 4%
Complex Network Analysis Techniques
6.62
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