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Modeling the Impact of Virtual Contact Network with Community Structure on the Epidemic Spreading

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  • Jianlin Zhou
  • Haiyan Liu

Abstract

The epidemic spreading is closely related to the spread of information, and it will coevolve with the information transmission. Considering that the network structure has a significant impact on network dynamics and the virtual contact networks have obvious community structures in reality, in this article, we built a multiplex network, which contains a community structure to explore the interplay of the coupled spread dynamics. We first use a microscopic Markov chain approach to characterize the coupled disease‐awareness dynamics and then analyze the effect of different factors on the coevolution of information dissemination and epidemic spreading based on the Monte Carlo simulation. The simulation results show that promoting the dissemination of information is indeed conducive to suppressing the spread of disease, but changing the process of disease transmission has no obvious effect on the information dissemination. The analysis also reveals that increasing the information transmission rate or decreasing the information recovery rate can promote the spread of information and inhibit the spread of diseases. In addition, taking preventive behaviors or decreasing the long‐distance jump also helps slow the epidemic spreading.

Suggested Citation

  • Jianlin Zhou & Haiyan Liu, 2022. "Modeling the Impact of Virtual Contact Network with Community Structure on the Epidemic Spreading," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:9551912
    DOI: 10.1155/2022/9551912
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    1. Wang, Huan & Ma, Chuang & Chen, Han-Shuang & Zhang, Hai-Feng, 2021. "Effects of asymptomatic infection and self-initiated awareness on the coupled disease-awareness dynamics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 400(C).
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