IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v332y2018icp437-448.html
   My bibliography  Save this article

Coupling dynamics of epidemic spreading and information diffusion on complex networks

Author

Listed:
  • Zhan, Xiu-Xiu
  • Liu, Chuang
  • Zhou, Ge
  • Zhang, Zi-Ke
  • Sun, Gui-Quan
  • Zhu, Jonathan J.H.
  • Jin, Zhen

Abstract

The interaction between disease and disease information on complex networks has facilitated an interdisciplinary research area. When a disease begins to spread in the population, the corresponding information would also be transmitted among individuals, which in turn influence the spreading pattern of the disease. In this paper, firstly, we analyze the propagation of two representative diseases (H7N9 and Dengue fever) in the real-world population and their corresponding information on Internet, suggesting the high correlation of the two-type dynamical processes. Secondly, inspired by empirical analyses, we propose a nonlinear model to further interpret the coupling effect based on the SIS (Susceptible-Infected-Susceptible) model. Both simulation results and theoretical analysis show that a high prevalence of epidemic will lead to a slow information decay, consequently resulting in a high infected level, which shall in turn prevent the epidemic spreading. Finally, further theoretical analysis demonstrates that a multi-outbreak phenomenon emerges via the effect of coupling dynamics, which finds good agreement with empirical results. This work may shed light on the in-depth understanding of the interplay between the dynamics of epidemic spreading and information diffusion.

Suggested Citation

  • Zhan, Xiu-Xiu & Liu, Chuang & Zhou, Ge & Zhang, Zi-Ke & Sun, Gui-Quan & Zhu, Jonathan J.H. & Jin, Zhen, 2018. "Coupling dynamics of epidemic spreading and information diffusion on complex networks," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 437-448.
    • Handle: RePEc:eee:apmaco:v:332:y:2018:i:c:p:437-448
    DOI: 10.1016/j.amc.2018.03.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300318302236
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2018.03.050?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhan, Xiu-Xiu & Liu, Chuang & Zhang, Zi-Ke & Sun, Gui-Quan, 2016. "Roles of edge weights on epidemic spreading dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 228-234.
    2. Zhan, Xiu-Xiu & Liu, Chuang & Sun, Gui-Quan & Zhang, Zi-Ke, 2018. "Epidemic dynamics on information-driven adaptive networks," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 196-204.
    3. Peter Horby, 2013. "H7N9 is a virus worth worrying about," Nature, Nature, vol. 496(7446), pages 399-399, April.
    Full references (including those not matched with items on IDEAS)

    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. Liu, Chuang & Zhou, Nan & Zhan, Xiu-Xiu & Sun, Gui-Quan & Zhang, Zi-Ke, 2020. "Markov-based solution for information diffusion on adaptive social networks," Applied Mathematics and Computation, Elsevier, vol. 380(C).
    2. 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.
    3. 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).
    4. Haiming Zhang & Cong Peng & Xiaodong Duan & Dan Shen & Guanghua Lan & Wutao Xiao & Hai Tan & Ling Wang & Jialei Hou & Jiancui Zhu & Riwen He & Haibing Zhang & Lilan Zheng & Jianyu Yang & Zhen Zhang & , 2014. "A Cross-Sectional Study of Avian Influenza in One District of Guangzhou, 2013," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-6, October.
    5. Li, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    6. Dun, Han & Shuting, Yan & She, Han & Lingfei, Qian & Chris, Ampimah Benjamin, 2019. "Research on how the difference of personal propagation ability influences the epidemic spreading in activity-driven network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 311-318.
    7. Kumar, Viney & Bhattacharyya, Samit, 2023. "Nonlinear effect of sentiments and opinion sharing on vaccination decision in face of an outbreak: A multiplex network approach," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    8. Wang, Jun & Cai, Shimin & Wang, Wei & Zhou, Tao, 2023. "Link cooperation effect of cooperative epidemics on complex networks," Applied Mathematics and Computation, Elsevier, vol. 437(C).
    9. Min Xu & Chunxiang Cao & Qun Li & Peng Jia & Jian Zhao, 2016. "Ecological Niche Modeling of Risk Factors for H7N9 Human Infection in China," IJERPH, MDPI, vol. 13(6), pages 1-12, June.

    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:eee:apmaco:v:332:y:2018:i:c:p:437-448. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.