IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i11p1895-d438057.html
   My bibliography  Save this article

Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/11/1895/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/8/11/1895/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Jiang & Zuo, Renxian & He, Chaocheng & Xiong, Hang & Zhao, Kang & Hu, Zhongyi, 2022. "The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    2. Liu, Hui & Yang, Naiding & Yang, Zhao & Lin, Jianhong & Zhang, Yanlu, 2020. "The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Zhu, Xuzhen & Wang, Ruijie & Wang, Zexun & Chen, Xiaolong & Wang, Wei & Cai, Shimin, 2019. "Double-edged sword effect of edge overlap on asymmetrically interacting spreading dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 617-624.
    4. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2019. "Interacting model of rumor propagation and behavior spreading in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 168-177.
    5. Yang, Yixin & Pan, Qiuhui & He, Mingfeng, 2023. "The influence of environment-based autonomous mobility on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Li, Ling & Dong, Gaogao & Zhu, Huaiping & Tian, Lixin, 2024. "Impact of multiple doses of vaccination on epidemiological spread in multiple networks," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    7. Fang, Fanshu & Ma, Jing & Li, Yanli, 2023. "The coevolution of the spread of a disease and competing opinions in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    8. Alqaralleh, Huthaifa & Canepa, Alessandra & Chini, Zanetti, 2021. "Financial Contagion During the Covid-19 Pandemic: A Wavelet-Copula-GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202110, University of Turin.
    9. Xu, Yuan-Hao & Wang, Hao-Jie & Lu, Zhong-Wen & Hu, Mao-Bin, 2023. "Impact of awareness dissemination on epidemic reaction–diffusion in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    10. Huo, Liang’an & Yu, Yue, 2023. "The impact of the self-recognition ability and physical quality on coupled negative information-behavior-epidemic dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    11. Zhehao Huang & Zhenghui Li & Zhenzhen Wang, 2020. "Utility Indifference Valuation for Defaultable Corporate Bond with Credit Rating Migration," Mathematics, MDPI, vol. 8(11), pages 1-26, November.
    12. Long, Linbo & Zhong, Kan & Wang, Wei, 2018. "Malicious viruses spreading on complex networks with heterogeneous recovery rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 746-753.
    13. Pan, Cheng & Yang, Lu-Xing & Yang, Xiaofan & Wu, Yingbo & Tang, Yuan Yan, 2018. "An effective rumor-containing strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 80-91.
    14. Feng, Meiling & Liu, Lijin & Chen, Jiaxing & Xia, Chengyi, 2024. "Heterogeneous propagation processes between awareness and epidemic on signed multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    15. Li, Chao & Wang, Li & Sun, Shiwen & Xia, Chengyi, 2018. "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 512-523.
    16. Jun, Seung-Pyo & Yoo, Hyoung Sun & Lee, Jae-Seong, 2021. "The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    17. 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.
    18. Chen, Xiaolong & Gong, Kai & Wang, Ruijie & Cai, Shimin & Wang, Wei, 2020. "Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    19. Chen, Ren-Raw & Zhang, Xiaohu, 2024. "From liquidity risk to systemic risk: A use of knowledge graph," Journal of Financial Stability, Elsevier, vol. 70(C).
    20. Yu Chen & Wei Wang & Jinping Feng & Ying Lu & Xinqi Gong, 2020. "Maximizing multiple influences and fair seed allocation on multilayer social networks," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:1895-:d:438057. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.