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The effects of global awareness on the spreading of epidemics in multiplex networks

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  • Zang, Haijuan

Abstract

It is increasingly recognized that understanding the complex interplay patterns between epidemic spreading and human behavioral is a key component of successful infection control efforts. In particular, individuals can obtain the information about epidemics and respond by altering their behaviors, which can affect the spreading dynamics as well. Besides, because the existence of herd-like behaviors, individuals are very easy to be influenced by the global awareness information. Here, in this paper, we propose a global awareness controlled spreading model (GACS) to explore the interplay between the coupled dynamical processes. Using the global microscopic Markov chain approach, we obtain the analytical results for the epidemic thresholds, which shows a high accuracy by comparison with lots of Monte Carlo simulations. Furthermore, considering other classical models used to describe the coupled dynamical processes, including the local awareness controlled contagion spreading (LACS) model, Susceptible–Infected–Susceptible–Unaware–Aware–Unaware (SIS–UAU) model and the single layer occasion, we make a detailed comparisons between the GACS with them. Although the comparisons and results depend on the parameters each model has, the GACS model always shows a strong restrain effects on epidemic spreading process. Our results give us a better understanding of the coupled dynamical processes and highlights the importance of considering the spreading of global awareness in the control of epidemics.

Suggested Citation

  • Zang, Haijuan, 2018. "The effects of global awareness on the spreading of epidemics in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1495-1506.
  • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1495-1506
    DOI: 10.1016/j.physa.2017.11.076
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    Citations

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    Cited by:

    1. Yu Chen & Wei Wang & Jinping Feng & Ying Lu & Xinqi Gong, 2020. "Maximizing multiple influences and fair seed allocation on multilayer social networks," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
    2. Jun, Seung-Pyo & Yoo, Hyoung Sun & Lee, Jae-Seong, 2021. "The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    3. Liu, Hui & Yang, Naiding & Yang, Zhao & Lin, Jianhong & Zhang, Yanlu, 2020. "The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    4. Wu, Qingchu & Chen, Shufang, 2022. "Coupled simultaneous evolution of disease and information on multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    5. Dong Wang & Yi Zhao & Hui Leng, 2020. "Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks," Mathematics, MDPI, vol. 8(11), pages 1-15, October.

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