IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v533y2019ics0378437119311641.html
   My bibliography  Save this article

Influence of geometric correlations on epidemic spreading in multiplex networks

Author

Listed:
  • Fan, Dongmei
  • Jiang, Guo-Ping
  • Song, Yu-Rong
  • Zhang, Xu

Abstract

Real-world multiplex networks are not randomly connected by several single-layer networks. In fact, there exist significant geometric correlations among different layers. In this paper, the influence of the geometric correlations, including the radial correlation and the angular correlation, on epidemic spreading on multiplex networks is investigated. The results show that the radial correlation and/or the angular correlation can reduce the epidemic threshold and lead to smaller scale of outbreak on the artificial networks. Moreover, although geometric correlations and overlapped links are positively correlated, the influence of geometric correlations on epidemic spreading cannot be replaced by overlapped links. Simulations on a real-world multiplex network indicate that the geometric correlations can produce lower threshold and smaller scale of outbreak.

Suggested Citation

  • Fan, Dongmei & Jiang, Guo-Ping & Song, Yu-Rong & Zhang, Xu, 2019. "Influence of geometric correlations on epidemic spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311641
    DOI: 10.1016/j.physa.2019.122028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119311641
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122028?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.

    Citations

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


    Cited by:

    1. Doménech-Carbó, Antonio & Doménech-Casasús, Clara, 2021. "The evolution of COVID-19: A discontinuous approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    2. Meng, Xueyu & Cai, Zhiqiang & Si, Shubin & Duan, Dongli, 2021. "Analysis of epidemic vaccination strategies on heterogeneous networks: Based on SEIRV model and evolutionary game," Applied Mathematics and Computation, Elsevier, vol. 403(C).

    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:phsmap:v:533:y:2019:i:c:s0378437119311641. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.