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

Area of Science:

• Public Health
• Computational Epidemiology
• Infectious Disease Modeling

Background:

• Infectious diseases pose a significant global public health challenge, necessitating effective prevention and management strategies, especially during pandemics.
• Unique settings like conference venues require specific attention due to concentrated human interaction and potential for rapid disease spread.
• Understanding transmission dynamics in short-duration, high-contact events is crucial for mitigating public health risks.

Purpose of the Study:

• To develop and utilize a computational model simulating infectious disease transmission within a one-day conference setting.
• To identify key transmission points and dynamics, including close-contact interactions, diverse attendee encounters, and restroom environments.
• To assess the effectiveness of various control strategies in curbing disease dissemination during such events.

Main Methods:

• An agent-based model was employed to simulate individual attendee activities and interactions within a conference venue.
• The model captured proximity seating during meetings, diverse interactions during breaks (rest and meal), and potential transmission in restrooms.
• Simulations focused on close-contact transmission between infected and susceptible individuals over a condensed timeframe.

Main Results:

• The study elucidated the complex dynamics of infectious disease transmission specific to conference environments.
• Analysis revealed critical interaction points and periods contributing to disease spread.
• The efficacy of different control measures for reducing transmission was evaluated through simulation.

Conclusions:

• The developed numerical framework provides a valuable tool for assessing infectious disease transmission risks at short-duration conferences.
• Findings offer actionable insights for conference organizers to implement targeted prevention and control measures.
• This research contributes to a proactive approach to managing public health threats in event settings.