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Epidemic spreading on networks with overlapping community structure

Author

Listed:
  • Chen, Jiancong
  • Zhang, Huiling
  • Guan, Zhi-Hong
  • Li, Tao

Abstract

Many real networks are characterized by overlapping community structures in which vertices may belong to more than one community. In this paper, we propose a network model with overlapping community structure. The analytical and numerical results show that the connectivity distribution of this network follows a power law. We employ this network to investigate the impact of overlapping community structure on susceptible–infected–susceptible (SIS) epidemic spreading process. The simulation results indicate that significant overlapping community structure results in a major infection prevalence and leads to a peak of the spread velocity in the early stages of the emerging infection.

Suggested Citation

  • Chen, Jiancong & Zhang, Huiling & Guan, Zhi-Hong & Li, Tao, 2012. "Epidemic spreading on networks with overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1848-1854.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:4:p:1848-1854
    DOI: 10.1016/j.physa.2011.10.011
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    Citations

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    Cited by:

    1. Zhang, Ruixia & Li, Deyu, 2017. "Rumor propagation on networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 375-385.
    2. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    3. Namtirtha, Amrita & Dutta, Animesh & Dutta, Biswanath, 2018. "Identifying influential spreaders in complex networks based on kshell hybrid method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 310-324.
    4. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2016. "Targeted revision: A learning-based approach for incremental community detection in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 70-85.
    5. Wang, Junyi & Hou, Xiaoni & Li, Kezan & Ding, Yong, 2017. "A novel weight neighborhood centrality algorithm for identifying influential spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 88-105.
    6. Namika Makhija & Shashank Mouli Satapathy, 2021. "Community detection in dynamic networks: a comprehensive and comparative review using external and internal criteria," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(2), pages 217-230, April.
    7. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    8. Wei, Xiaodan & Xu, Gaochao & Zhou, Wenshu, 2018. "Global stability of endemic equilibrium for a SIQRS epidemic model on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 203-214.
    9. Guan, Yuan-Pan & You, Zhi-Qiang & Han, Xiao-Pu, 2016. "Reconstruction of social group networks from friendship networks using a tag-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 485-492.
    10. Han, Dun & Sun, Mei & Li, Dandan, 2015. "The virus variation model by considering the degree-dependent spreading rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 42-50.
    11. Nian, Fuzhong & Yao, Shuanglong, 2018. "The epidemic spreading on the multi-relationships network," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 866-873.
    12. Yusheng Zhang & Liang Li & Yuewen Jiang & Biqing Huang, 2020. "Analysis of COVID-19 Prevention and Control Effects Based on the SEITRD Dynamic Model and Wuhan Epidemic Statistics," IJERPH, MDPI, vol. 17(24), pages 1-16, December.

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