IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v377y2007i1p125-130.html
   My bibliography  Save this article

Epidemic spreading in lattice-embedded scale-free networks

Author

Listed:
  • Xu, Xin-Jian
  • Wu, Zhi-Xi
  • Chen, Guanrong

Abstract

We study geographical effects on the spread of diseases in lattice-embedded scale-free networks. The geographical structure is represented by the connecting probability of two nodes that is related to the Euclidean distance between them in the lattice. By studying the standard susceptible-infected model, we found that the geographical structure has great influences on the temporal behavior of epidemic outbreaks and the propagation in the underlying network: the more geographically constrained the network is, the more smoothly the epidemic spreads, which is different from the clearly hierarchical dynamics that the infection pervades the networks in a progressive cascade across smaller-degree classes in Barabási–Albert scale-free networks.

Suggested Citation

  • Xu, Xin-Jian & Wu, Zhi-Xi & Chen, Guanrong, 2007. "Epidemic spreading in lattice-embedded scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 125-130.
    • Handle: RePEc:eee:phsmap:v:377:y:2007:i:1:p:125-130
    DOI: 10.1016/j.physa.2006.11.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437106012398
    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.2006.11.023?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. 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).
    2. Yang, Han-Xin & Sun, Lei, 2020. "Heterogeneous donation game in geographical small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. Zhao, Laijun & Wang, Jiajia & Huang, Rongbing & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli, 2014. "Sentiment contagion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 17-23.

    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:377:y:2007:i:1:p:125-130. 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.