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Epidemic spreading in metapopulation networks with heterogeneous infection rates

Author

Listed:
  • Gong, Yong-Wang
  • Song, Yu-Rong
  • Jiang, Guo-Ping

Abstract

In this paper, we study epidemic spreading in metapopulation networks wherein each node represents a subpopulation symbolizing a city or an urban area and links connecting nodes correspond to the human traveling routes among cities. Differently from previous studies, we introduce a heterogeneous infection rate to characterize the effect of nodes’ local properties, such as population density, individual health habits, and social conditions, on epidemic infectivity. By means of a mean-field approach and Monte Carlo simulations, we explore how the heterogeneity of the infection rate affects the epidemic dynamics, and find that large fluctuations of the infection rate have a profound impact on the epidemic threshold as well as the temporal behavior of the prevalence above the epidemic threshold. This work can refine our understanding of epidemic spreading in metapopulation networks with the effect of nodes’ local properties.

Suggested Citation

  • Gong, Yong-Wang & Song, Yu-Rong & Jiang, Guo-Ping, 2014. "Epidemic spreading in metapopulation networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 208-218.
    • Handle: RePEc:eee:phsmap:v:416:y:2014:i:c:p:208-218
    DOI: 10.1016/j.physa.2014.08.056
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    Citations

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    Cited by:

    1. Wang, Jingbei & Yang, Naiding & Zhang, Yanlu & Song, Yue, 2018. "Development of the mitigation strategy against the schedule risks of the R&D project through controlling the cascading failure of the R&D network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 390-401.
    2. Huang, Yunhan & Ding, Li & Feng, Yun, 2016. "A novel epidemic spreading model with decreasing infection rate based on infection times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 1041-1048.
    3. Wang, Jingbei & Yang, Naiding & Zhang, Yanlu & Song, Yue, 2019. "Modeling and simulation of the cascading failure of R&D network considering the community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 43-53.
    4. Huang, Jinyu & Chen, Chao, 2022. "Metapopulation epidemic models with a universal mobility pattern on interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    5. Jia, Peng & Liu, Jiayong & Fang, Yong & Liu, Liang & Liu, Luping, 2018. "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 240-254.

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