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Epidemic spreading on weighted networks with adaptive topology based on infective information

Author

Listed:
  • Feng, Yun
  • Ding, Li
  • Huang, Yun-Han
  • Zhang, Li

Abstract

In this paper, we consider epidemic spreading on a weighted adaptive network in which the network topology varies according to the global and local infective information of individuals. We focus on the relationship between network topology and epidemic spreading. Interacting strength is defined to evaluate the level of how individuals’ infective information taking effects on their connections. The model is analyzed by discrete-time Monte-Carlo simulations with an initial BA scale-free network. It is found that greater interacting strength leads to higher epidemic threshold, lower average disease density of steady-state and shorter epidemic prevalent decay time. Besides, the interaction tends to change the initial BA scale-free network to a fat-tail network while the scaling exponent almost keeps unchanged. In addition, individual who reacts with local infective information will significantly restrain the outbreak of disease comparing to the one with global infective information, and this phenomenon becomes more notable if the interacting strength becomes greater.

Suggested Citation

  • Feng, Yun & Ding, Li & Huang, Yun-Han & Zhang, Li, 2016. "Epidemic spreading on weighted networks with adaptive topology based on infective information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 493-502.
    • Handle: RePEc:eee:phsmap:v:463:y:2016:i:c:p:493-502
    DOI: 10.1016/j.physa.2016.07.072
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    Citations

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    Cited by:

    1. Liu, Xiongding & Li, Tao & Xu, Hao & Liu, Wenjin, 2019. "Spreading dynamics of an online social information model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 497-510.
    2. Liu, Yujing & Ding, Li & An, Xuming & Hu, Ping & Du, Fuying, 2020. "Epidemic spreading on midscopic multi-layer network with optimal control mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Xiaoyang Liu & Chao Liu & Xiaoping Zeng, 2017. "Online Social Network Emergency Public Event Information Propagation and Nonlinear Mathematical Modeling," Complexity, Hindawi, vol. 2017, pages 1-7, June.
    4. Yunhan Huang & Quanyan Zhu, 2022. "Game-Theoretic Frameworks for Epidemic Spreading and Human Decision-Making: A Review," Dynamic Games and Applications, Springer, vol. 12(1), pages 7-48, March.

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