IDEAS home Printed from https://ideas.repec.org/a/wsi/fracta/v29y2021i06ns0218348x21501346.html
   My bibliography  Save this article

Fractal Propagation And Immunity On Network

Author

Listed:
  • FUZHONG NIAN

    (Lanzhou University of Technology, LanZhou 730050, P. R. China)

  • YANG YANG

    (Lanzhou University of Technology, LanZhou 730050, P. R. China)

  • YAYONG SHI

    (Lanzhou University of Technology, LanZhou 730050, P. R. China)

Abstract

In this paper, the epidemic spreading was investigated from the point of view of fractal. Firstly, the real network was abstracted as a fully connected fractal network. Based on the fractal network, the fractal spreading process was studied. The fractal spreading process was simulated to analyze the change of infection density during transmission. The results showed that the infection density presented an upward trend of the ladder-shaped, and a jumping change in infection density occurred during a certain time. As an illustration, the pandemic of COVID-19 was analyzed, the results indicated that the proposed method was valid. Experiments and analyses have shown that intervention at key jump points in virus propagation can effectively control the spread of the virus.

Suggested Citation

  • Fuzhong Nian & Yang Yang & Yayong Shi, 2021. "Fractal Propagation And Immunity On Network," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(06), pages 1-12, September.
    • Handle: RePEc:wsi:fracta:v:29:y:2021:i:06:n:s0218348x21501346
    DOI: 10.1142/S0218348X21501346
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0218348X21501346
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0218348X21501346?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. Jin, Ziyang & Duan, Dongli & Wang, Ning, 2022. "Cascading failure of complex networks based on load redistribution and epidemic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Nian, Fuzhong & Liu, Xinghao & Diao, Hongyuan, 2022. "Mechanism of investor behavior propagation in stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

    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:wsi:fracta:v:29:y:2021:i:06:n:s0218348x21501346. 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: Tai Tone Lim (email available below). General contact details of provider: https://www.worldscientific.com/worldscinet/fractals .

    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.