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Traffic-driven SIR epidemic spreading in networks

Author

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  • Pu, Cunlai
  • Li, Siyuan
  • Yang, XianXia
  • Xu, Zhongqi
  • Ji, Zexuan
  • Yang, Jian

Abstract

We study SIR epidemic spreading in networks driven by traffic dynamics, which are further governed by static routing protocols. We obtain the maximum instantaneous population of infected nodes and the maximum population of ever infected nodes through simulation. We find that generally more balanced load distribution leads to more intense and wide spread of an epidemic in networks. Increasing either average node degree or homogeneity of degree distribution will facilitate epidemic spreading. When packet generation rate ρ is small, increasing ρ favors epidemic spreading. However, when ρ is large enough, traffic congestion appears which inhibits epidemic spreading.

Suggested Citation

  • Pu, Cunlai & Li, Siyuan & Yang, XianXia & Xu, Zhongqi & Ji, Zexuan & Yang, Jian, 2016. "Traffic-driven SIR epidemic spreading in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 129-137.
    • Handle: RePEc:eee:phsmap:v:446:y:2016:i:c:p:129-137
    DOI: 10.1016/j.physa.2015.11.028
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    Citations

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    Cited by:

    1. Meihui Jiang, 2022. "Locating the Principal Sectors for Carbon Emission Reduction on the Global Supply Chains by the Methods of Complex Network and Susceptible–Infective Model," Sustainability, MDPI, vol. 14(5), pages 1-13, February.
    2. Chen, Jie & Hu, Mao-Bin & Li, Ming, 2020. "Traffic-driven epidemic spreading dynamics with heterogeneous infection rates," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    3. Jia, Nan & Ding, Li & Liu, Yu-Jing & Hu, Ping, 2018. "Global stability and optimal control of epidemic spreading on multiplex networks with nonlinear mutual interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 93-105.
    4. Chen, Jun-Jie & Hu, Mao-Bin & Wu, Yong-Hong, 2022. "Traffic-driven epidemic spreading with non-uniform origin and destination selection," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    5. Su, Zhu & Liu, Sannyuya & Deng, Weibing & Li, Wei & Cai, Xu, 2019. "Transportation dynamics on networks of heterogeneous mobile agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1379-1386.
    6. Schaum, Alexander & Bernal Jaquez, Roberto, 2016. "Estimating the state probability distribution for epidemic spreading in complex networks," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 197-206.
    7. Chen, Jie & Tan, Xuegang & Cao, Jinde & Li, Ming, 2022. "Effect of coupling structure on traffic-driven epidemic spreading in interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    8. Deepti Muley & Md. Shahin & Charitha Dias & Muhammad Abdullah, 2020. "Role of Transport during Outbreak of Infectious Diseases: Evidence from the Past," Sustainability, MDPI, vol. 12(18), pages 1-22, September.

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