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Open Access

COVID-19 Spread Simulation in a Crowd Intelligence Network

Linzhi Shan1, Hongbo Sun1( )
School of Computer and Control Engineering, Yantai University, Yantai 264005, China
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Abstract

In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and self-protection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19.

Keywords

COVID-19epidemic spread simulationmultiple scenesmulti-layer coupled network

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International Journal of Crowd Science
Volume 6 Issue 3,
September 2022
Pages 117-127
DOI: 10.26599/IJCS.2022.9100002
Cite this article:
Shan L, Sun H. COVID-19 Spread Simulation in a Crowd Intelligence Network. International Journal of Crowd Science, 2022, 6(3): 117-127. https://doi.org/10.26599/IJCS.2022.9100002

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Received: 29 December 2021
Revised: 24 January 2022
Accepted: 25 January 2022
Published: 09 August 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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