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Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks

Author

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  • Dong Wang

    (School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Yi Zhao

    (School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

  • Hui Leng

    (School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

Abstract

The co-evolution between information and epidemic in multilayer networks has attracted wide attention. However, previous studies usually assume that two networks with the same individuals are coupled into a multiplex network, ignoring the context that the individuals of each layer in the multilayer network are often different, especially in group structures with rich collective phenomena. In this paper, based on the scenario of group-based multilayer networks, we investigate the coupled UAU-SIS (Unaware-Aware-Unaware-Susceptible-Infected-Susceptible) model via microscopic Markov chain approach (MMCA). Importantly, the evolution of such transmission process with respective to various impact factors, especially for the group features, is captured by simulations. We further obtain the theoretical threshold for the onset of epidemic outbreaks and analyze its characteristics through numerical simulations. It is concluded that the growth of the group size of information (physical) layer effectively suppresses (enhances) epidemic spreading. Moreover, taking the context of epidemic immunization into account, we find that the propagation capacity and robustness of this type of network are greater than the conventional multiplex network.

Suggested Citation

  • Dong Wang & Yi Zhao & Hui Leng, 2020. "Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks," Mathematics, MDPI, vol. 8(11), pages 1-15, October.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:1895-:d:438057
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    References listed on IDEAS

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    1. Nie, Xiaoyu & Tang, Ming & Zou, Yong & Guan, Shuguang & Zhou, Jie, 2017. "The impact of heterogeneous response on coupled spreading dynamics in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 225-232.
    2. Gao, Chao & Tang, Shaoting & Li, Weihua & Yang, Yaqian & Zheng, Zhiming, 2018. "Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 330-338.
    3. Yang, Han-Xin & Tang, Ming & Wang, Zhen, 2018. "Suppressing epidemic spreading by risk-averse migration in dynamical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 347-352.
    4. Marina Dolfin & Damian Knopoff & Michele Limosani & Maria Gabriella Xibilia, 2019. "Credit Risk Contagion and Systemic Risk on Networks," Mathematics, MDPI, vol. 7(8), pages 1-16, August.
    5. Zang, Haijuan, 2018. "The effects of global awareness on the spreading of epidemics in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1495-1506.
    6. Quantong Guo & Yanjun Lei & Chengyi Xia & Lu Guo & Xin Jiang & Zhiming Zheng, 2016. "The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-19, August.
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    Cited by:

    1. Ma, Weicai & Zhang, Peng & Zhao, Xin & Xue, Leyang, 2022. "The coupled dynamics of information dissemination and SEIR-based epidemic spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

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