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Multiple peaks patterns of epidemic spreading in multi-layer networks

Author

Listed:
  • Zheng, Muhua
  • Wang, Wei
  • Tang, Ming
  • Zhou, Jie
  • Boccaletti, S.
  • Liu, Zonghua

Abstract

The study of epidemic spreading on populations of networked individuals has seen recently a great deal of significant progresses. A common point in many of past studies is, however, that there is only one peak of infected density in each single epidemic spreading episode. At variance, real data from different cities over the world suggest that, besides a major single peak trait of infected density, a finite probability exists for a pattern made of two (or multiple) peaks. We show that such a latter feature is distinctive of a multilayered network of interactions, and reveal that a two peaks pattern may emerge from different time delays at which the epidemic spreads in between the two layers. Further, we show that the essential ingredient is a weak coupling condition between the layers themselves, while different degree distributions in the two layers are also helpful. Moreover, an edge-based theory is developed which fully explains all numerical results. Our findings may therefore be of significance for protecting secondary disasters of epidemics, which are definitely undesired in real life.

Suggested Citation

  • Zheng, Muhua & Wang, Wei & Tang, Ming & Zhou, Jie & Boccaletti, S. & Liu, Zonghua, 2018. "Multiple peaks patterns of epidemic spreading in multi-layer networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 135-142.
    • Handle: RePEc:eee:chsofr:v:107:y:2018:i:c:p:135-142
    DOI: 10.1016/j.chaos.2017.12.026
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    References listed on IDEAS

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    1. Erik M Volz & Joel C Miller & Alison Galvani & Lauren Ancel Meyers, 2011. "Effects of Heterogeneous and Clustered Contact Patterns on Infectious Disease Dynamics," PLOS Computational Biology, Public Library of Science, vol. 7(6), pages 1-13, June.
    2. Joel C Miller, 2014. "Epidemics on Networks with Large Initial Conditions or Changing Structure," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-9, July.
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    Cited by:

    1. Zhang, Ningbo & Yang, Qiwen & Zhu, Xuzhen, 2022. "The impact of social resource allocation on epidemic transmission in complex networks," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    2. Yang, Zheng & Wu, Jiao & He, Jiaxu & Xu, Kesheng & Zheng, Muhua, 2023. "Asymmetric inter-layer interactions induce a double transition of information spreading," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    3. Huang, Yubo & Dong, Hongli & Zhang, Weidong & Lu, Junguo, 2019. "Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 5-15.
    4. Chen, Dandan & Zheng, Muhua & Zhao, Ming & Zhang, Yu, 2018. "A dynamic vaccination strategy to suppress the recurrent epidemic outbreaks," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 108-114.
    5. Wang, Jun & Cai, Shimin & Wang, Wei & Zhou, Tao, 2023. "Link cooperation effect of cooperative epidemics on complex networks," Applied Mathematics and Computation, Elsevier, vol. 437(C).
    6. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2019. "Interacting model of rumor propagation and behavior spreading in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 168-177.
    7. Huang, Qi-An & Zhao, Jun-Chan & Wu, Xiao-Qun, 2022. "Financial risk propagation between Chinese and American stock markets based on multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).

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