Modelling infectious disease transmission dynamics in conference environments: An agent-based approach

Xue Liu; Yue Deng; Jingying Huang; Yuhong Zhang; Jinzhi Lei; Xue Liu; Yue Deng; Jingying Huang; Yuhong Zhang; Jinzhi Lei

doi:10.3934/mbe.2026041

Mathematical Biosciences and Engineering

2026, Volume 23, Issue 4: 1096-1120. doi: 10.3934/mbe.2026041

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Research article

Modelling infectious disease transmission dynamics in conference environments: An agent-based approach

1.
School of Mathematical Sciences, Tiangong University, Tianjin 300387, China
2.
School of Mathematics, Shandong University, China
3.
School of Software, Tiangong University, Tianjin 300387, China
4.
School of Computer Science and Technology, Tiangong University, Tianjin 300387, China
5.
Shanghai Qinhe Web Technology Software Development Co., Ltd
6.
Center for Applied Mathematics, Tiangong University, Tianjin 300387, China
^† These authors contributed equally

Received: 15 January 2026 Revised: 17 February 2026 Accepted: 26 February 2026 Published: 10 March 2026

The looming threat of infectious diseases perpetually challenges the global public health landscape. Central to addressing this concern is the imperative to prevent and manage disease transmission during pandemics, particularly in unique settings. This study addresses the transmission dynamics of infectious diseases within conference venues by presenting a computational model that simulates transmission processes over a condensed timeframe (one day), beginning with sporadic cases. Our model captures the activities of individual attendees within the conference venue, including meetings, rest breaks, and meal breaks. While meetings entail proximity seating, rest and lunch periods allow attendees to interact with diverse individuals. Moreover, the restroom environment poses an additional avenue for potential infection transmission. Employing an agent-based model, we meticulously replicated the transmission dynamics of infectious diseases, with a specific emphasis on close-contact interactions between infected and susceptible individuals. Through comprehensive analysis of model simulations, we elucidated the intricacies of disease transmission dynamics within conference settings and assessed the efficacy of control strategies to curb disease dissemination. Ultimately, our study provides a numerical framework for assessing the risk of infectious disease transmission during short-duration conferences, furnishing conference organizers with valuable insights to inform the implementation of targeted prevention and control measures.
- COVID-19,
- infectious disease,
- agent-based model,
- computational model,
- epidemic dynamics
Citation: Xue Liu, Yue Deng, Jingying Huang, Yuhong Zhang, Jinzhi Lei. Modelling infectious disease transmission dynamics in conference environments: An agent-based approach[J]. Mathematical Biosciences and Engineering, 2026, 23(4): 1096-1120. doi: 10.3934/mbe.2026041

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Abstract

The looming threat of infectious diseases perpetually challenges the global public health landscape. Central to addressing this concern is the imperative to prevent and manage disease transmission during pandemics, particularly in unique settings. This study addresses the transmission dynamics of infectious diseases within conference venues by presenting a computational model that simulates transmission processes over a condensed timeframe (one day), beginning with sporadic cases. Our model captures the activities of individual attendees within the conference venue, including meetings, rest breaks, and meal breaks. While meetings entail proximity seating, rest and lunch periods allow attendees to interact with diverse individuals. Moreover, the restroom environment poses an additional avenue for potential infection transmission. Employing an agent-based model, we meticulously replicated the transmission dynamics of infectious diseases, with a specific emphasis on close-contact interactions between infected and susceptible individuals. Through comprehensive analysis of model simulations, we elucidated the intricacies of disease transmission dynamics within conference settings and assessed the efficacy of control strategies to curb disease dissemination. Ultimately, our study provides a numerical framework for assessing the risk of infectious disease transmission during short-duration conferences, furnishing conference organizers with valuable insights to inform the implementation of targeted prevention and control measures.

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