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Coevolution of epidemic and infodemic on higher-order networks

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Listed:
  • Li, Wenyao
  • Cai, Meng
  • Zhong, Xiaoni
  • Liu, Yanbing
  • Lin, Tao
  • Wang, Wei

Abstract

Gathering events, e.g., going to gyms and meetings, are ubiquitous and crucial in the spreading phenomena, which induce higher-order interactions, and thus can be described as higher-order networks. Previous studies on the coevolution of epidemic-infodemic dynamics ignored the higher-order interactions in the social system, which affects our understanding of the reality spreading. We propose a mathematical framework for the coevolution of epidemic and infodemic on higher-order networks described by simplicial complex, and introduce the Microscopic Markov Chain Approach (MMCA) and mean-field approach to establish the dynamic process. We study the coevolution mathematical model on both artificial simplicial complex and real-world higher-order networks and find that the higher-order interactions show a ’double-edged sword’ role in shaping epidemic size, which is dependent on the breakout of infodemic. Furthermore, the higher-order networks enrich the phase diagram, inducing the emergence of discontinuous phase transition, hysteresis loop region, double transition and inter-epidemic region.

Suggested Citation

  • Li, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:chsofr:v:168:y:2023:i:c:s0960077923000036
    DOI: 10.1016/j.chaos.2023.113102
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    References listed on IDEAS

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    1. Zhiyong Hong & Huiyu Zhou & Zhishuang Wang & Qian Yin & Jingang Liu, 2023. "Coupled Propagation Dynamics of Information and Infectious Disease on Two-Layer Complex Networks with Simplices," Mathematics, MDPI, vol. 11(24), pages 1-17, December.

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