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Impact of information adoption and the resulted self-protective actions on epidemic spreading in awareness-disease coupled multiplex networks

Author

Listed:
  • Huayan Pei

    (Lanzhou Jiaotong University
    Key Laboratory of Media Convergence Technology and Communication)

  • Ying Ding

    (Lanzhou Jiaotong University)

  • Guanghui Yan

    (Lanzhou Jiaotong University
    Key Laboratory of Media Convergence Technology and Communication)

Abstract

During the awareness-epidemic coupled spreading process, the self-protective actions resulted from information adoption can help to change the actual infection rate. In this paper, a UAPU-SEIR model is proposed by incorporating the impacts of information adoption and the resulting self-protective actions on epidemic transmission. Motivated by information adoption which greatly affects individuals’ subsequent behaviors, a new state abbreviated as P is introduced into the traditional unaware-aware-unaware model to describe the preventive action taken state after information adoption. Importantly, the infection rate of P-state individuals is closely related to information adoption probability. The Microscopic Markov Chain Approach (MMCA) is used to theoretically analyze the presented model and derive the outbreak threshold of epidemic. Simulation results suggest that under small epidemic infection rate, the proposed model significantly suppresses epidemic spreading speed and size, and results in higher epidemic threshold. Whereas, greater information adoption rate is needed to inhibit epidemic dissemination for increased infection rate. Besides, under the impact of information adoption and the resulted self-protective behaviors, accelerating information diffusion is able to both inhibit epidemic transmission and raise epidemic threshold. Current findings provide us a better understanding for the prevention and controlling of real infectious disease. Graphical abstract

Suggested Citation

  • Huayan Pei & Ying Ding & Guanghui Yan, 2024. "Impact of information adoption and the resulted self-protective actions on epidemic spreading in awareness-disease coupled multiplex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(5), pages 1-10, May.
    • Handle: RePEc:spr:eurphb:v:97:y:2024:i:5:d:10.1140_epjb_s10051-024-00693-5
    DOI: 10.1140/epjb/s10051-024-00693-5
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    References listed on IDEAS

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    1. Wang, Zhishuang & Guo, Quantong & Sun, Shiwen & Xia, Chengyi, 2019. "The impact of awareness diffusion on SIR-like epidemics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 134-147.
    2. Sun, Qingyi & Wang, Zhishuang & Zhao, Dawei & Xia, Chengyi & Perc, Matjaž, 2022. "Diffusion of resources and their impact on epidemic spreading in multilayer networks with simplicial complexes," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Wu, Jiang & Zuo, Renxian & He, Chaocheng & Xiong, Hang & Zhao, Kang & Hu, Zhongyi, 2022. "The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    4. Neil Ferguson, 2007. "Capturing human behaviour," Nature, Nature, vol. 446(7137), pages 733-733, April.
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