The mixing groups gathered in the enclosed space form a complex contact network due to face-to-face interaction, which affects the status and role of different groups in social communication. The intricacies of epidemic spreading in mixing groups are intrinsically complicated. Multiple interactions and transmission add to the difficulties of understanding and forecasting the spread of infectious diseases in mixing groups. Despite the critical relevance of face-to-face interactions in real-world situations, there is a significant lack of comprehensive study addressing the unique issues of mixed groups, particularly those with complex face-to-face interactions. We introduce a novel model employing an agent-based approach to elucidate the nuances of face-to-face interactions within mixing groups. In this paper, we apply a susceptible-infected-susceptible process to mixing groups and integrate a temporal network within a specified time window to distinguish between individual movement patterns and epidemic spreading dynamics. Our findings highlight the significant impact of both the relative size of mixing groups and the groups’ mixing patterns on the trajectory of disease spread within the mixing groups. When group sizes differ significantly, high inter-group contact preference limits disease spread. However, if the minority reduces their intra-group preferences while the majority maintains high inter-group contact, disease spread increases. In balanced group sizes, high intra-group contact preferences can limit transmission, but asymmetrically reducing any group’s intra-group preference can lead to increased spread.
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September 2024
Research Article|
September 04 2024
Epidemic spreading on mixing group with face-to-face interaction
Wenbin Gu
;
Wenbin Gu
(Methodology, Visualization, Writing – original draft, Writing – review & editing)
1
School of Public Health, Chongqing Medical University
, Chongqing 400016, China
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Wenjie Li;
Wenjie Li
(Methodology, Visualization, Writing – original draft, Writing – review & editing)
1
School of Public Health, Chongqing Medical University
, Chongqing 400016, China
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Feng Gao
;
Feng Gao
(Methodology, Supervision, Writing – review & editing)
2
School of Artificial Intelligence, Chongqing University of Arts and Sciences
, Chongqing 402160, China
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Sheng Su
;
Sheng Su
(Methodology, Writing – review & editing)
3
School of Information and Software Engineering, University of Electronic Science and Technology of China
, Chengdu 611713, China
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Zengping Zhang;
Zengping Zhang
(Methodology, Writing – review & editing)
4
School of Computer & Information Management, Inner Mongolia University of Finance and Economics
, Hohhot 010070, China
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Xiaoyang Liu
;
Xiaoyang Liu
(Methodology, Writing – review & editing)
5
School of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054
, China
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Wei Wang
Wei Wang
a)
(Methodology, Supervision, Writing – review & editing)
1
School of Public Health, Chongqing Medical University
, Chongqing 400016, China
a)Author to whom correspondence should be addressed: wwzqbc@cqmu.edu.cn
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a)Author to whom correspondence should be addressed: wwzqbc@cqmu.edu.cn
Chaos 34, 093108 (2024)
Article history
Received:
June 10 2024
Accepted:
August 20 2024
Citation
Wenbin Gu, Wenjie Li, Feng Gao, Sheng Su, Zengping Zhang, Xiaoyang Liu, Wei Wang; Epidemic spreading on mixing group with face-to-face interaction. Chaos 1 September 2024; 34 (9): 093108. https://doi.org/10.1063/5.0222847
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