IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v678y2025ics037843712500620x.html
   My bibliography  Save this article

Unveiling epidemic spreading and control on networks with self-recovery and social support

Author

Listed:
  • Wu, Qingchu
  • Wang, Lin

Abstract

Given the inherent complexities of individual recovery, self-recovery stems from the individual themselves, whereas social support originates from their susceptible surroundings. Utilizing the quenched mean-field method, two distinct analytical models are developed. The condition for an epidemic outbreak is established through a comprehensive analysis of stability and bifurcation. Continuous-time simulations confirm the predictive capability of these models in terms of spreading behavior. Our findings indicate that both self-recovery and social support can decrease the likelihood of an epidemic outbreak. Further simulations imply that self-recovery can eradicate the explosive transition in scale-free networks, but only dampen its magnitude in random regular networks. These insights could have profound implications for governmental strategies in increasing its publicity efforts for epidemic control.

Suggested Citation

  • Wu, Qingchu & Wang, Lin, 2025. "Unveiling epidemic spreading and control on networks with self-recovery and social support," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 678(C).
    • Handle: RePEc:eee:phsmap:v:678:y:2025:i:c:s037843712500620x
    DOI: 10.1016/j.physa.2025.130968
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712500620X
    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.2025.130968?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:678:y:2025:i:c:s037843712500620x. 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.