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Traffic-driven SI epidemic spreading on scale-free networks

Author

Listed:
  • Yongqiang Zhang

    (School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, P. R. China)

  • Shuang Li

    (School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, P. R. China)

  • Junfeng Zhang

    (School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, P. R. China)

  • Jinlong Ma

    (School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, P. R. China)

  • Haigang An

    (School of Management, Hebei GEO University, Shijiazhuang 050031, P. R. China)

Abstract

As COVID-19 spread globally in 2020, the interaction between the traffic dynamics and the spread of the epidemic has attracted much attention. However, controlling the spread of the epidemic remains a challenging issue. In this paper, we have investigated the relationships between link-closure strategies and the traffic-driven epidemic spreading. It is found that the epidemic spreading can be suppressed by the targeted closing of links between small-degree nodes. In contrast, closing links between large-degree nodes can accelerate the outbreak of the epidemic. These findings have significance for controlling the spread of the epidemic.

Suggested Citation

  • Yongqiang Zhang & Shuang Li & Junfeng Zhang & Jinlong Ma & Haigang An, 2022. "Traffic-driven SI epidemic spreading on scale-free networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 33(08), pages 1-12, August.
    • Handle: RePEc:wsi:ijmpcx:v:33:y:2022:i:08:n:s012918312250111x
    DOI: 10.1142/S012918312250111X
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