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A modified SIS model with an infective medium on complex networks and its global stability

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  • Yang, Meng
  • Chen, Guanrong
  • Fu, Xinchu

Abstract

In this paper, we propose a modified susceptible–infected–susceptible model with an infective medium, which describes epidemics transmitted through an infective medium on complex networks. We examine epidemic thresholds for disease spreading by using this new model and compare it with the standard SIS model and another SIS model having an infective medium. We also study and compare the effects of the uniform immunization scheme on different models. We finally give some necessary and sufficient conditions for the global stability of the new model.

Suggested Citation

  • Yang, Meng & Chen, Guanrong & Fu, Xinchu, 2011. "A modified SIS model with an infective medium on complex networks and its global stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2408-2413.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:12:p:2408-2413
    DOI: 10.1016/j.physa.2011.02.007
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    References listed on IDEAS

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    1. Shi, Hongjing & Duan, Zhisheng & Chen, Guanrong, 2008. "An SIS model with infective medium on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2133-2144.
    2. James Holland Jones & Mark S. Handcock, 2003. "Sexual contacts and epidemic thresholds," Nature, Nature, vol. 423(6940), pages 605-606, June.
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    Cited by:

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    5. Zhang, Ruixia & Li, Deyu & Jin, Zhen, 2015. "Dynamic analysis of a delayed model for vector-borne diseases on bipartite networks," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 342-352.
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    8. Xie, Yingkang & Wang, Zhen, 2021. "Transmission dynamics, global stability and control strategies of a modified SIS epidemic model on complex networks with an infective medium," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 23-34.
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    13. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
    14. Li, Tao & Liu, Xiongding & Wu, Jie & Wan, Chen & Guan, Zhi-Hong & Wang, Yuanmei, 2016. "An epidemic spreading model on adaptive scale-free networks with feedback mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 649-656.
    15. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.
    16. Leyi Zheng & Longkun Tang, 2019. "A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks," Complexity, Hindawi, vol. 2019, pages 1-14, February.
    17. Sanders, Johnathan & Noble, Benjamin & Van Gorder, Robert A. & Riggs, Cortney, 2012. "Mobility matrix evolution for an SIS epidemic patch model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6256-6267.
    18. Lei, Mingli & Cheong, Kang Hao, 2022. "Node influence ranking in complex networks: A local structure entropy approach," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    19. Wang, Yanhui & Bi, Lifeng & Lin, Shuai & Li, Man & Shi, Hao, 2017. "A complex network-based importance measure for mechatronics systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 180-198.
    20. Yang, Ming-Yuan & Wu, Zhen-Guo & Wu, Xin & Li, Sai-Ping, 2024. "Influential risk spreaders and systemic risk in Chinese financial networks," Emerging Markets Review, Elsevier, vol. 60(C).
    21. Wei, Xiaodan & Liu, Lijun & Zhou, Wenshu, 2017. "Global stability and attractivity of a network-based SIS epidemic model with nonmonotone incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 789-798.
    22. Wu, Yingbo & Li, Pengdeng & Yang, Lu-Xing & Yang, Xiaofan & Tang, Yuan Yan, 2017. "A theoretical method for assessing disruptive computer viruses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 325-336.

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