Infection risk and economic activity trade-offs: decision-making in indoor venue operations for pandemic preparedness

During epidemics, decision-making regarding intervention measures faces complex trade-offs. Interventions targeting indoor venues can mitigate disease spread, since they are associated with higher infection risk for respiratory pathogens. However, as experienced during the COVID-19 pandemic, these measures can lead to economic losses, especially in the hospitality sector. In this study, we propose a hybrid modeling and simulation framework to provide decision support for reducing the infection risk in indoor venues while maintaining viable economic activity. Our framework integrates (i) a microscopic pedestrian model for human movement, (ii) a hybrid simulation model for virus spread and transmission, and (iii) a multi-criteria decision-making approach to identify the best service options. The framework is demonstrated for the SARS-CoV-2 infection risk. The restaurant case study results illustrate that maximizing the distance between seating groups can have a limited effect on the infection risk. Service duration and service capacity are key determinants of expected economic activity, but they constitute significant trade-offs: the former has a substantial impact on the infection risk, and the latter drives the probability of infectious introductions. Our analysis demonstrates the need for multi-criteria approaches during an outbreak and consideration of the epidemiological context for operational decision-making, even at an individual venue.

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Publication Details

Journal
Journal of Simulation
Published
2025-10-03
DOI
https://doi.org/10.1080/17477778.2025.2546481
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Infection risk and economic activity trade-offs: decision-making in indoor venue operations for pandemic preparedness

Yilin Huang, Quirine A. ten Bosch, Büşra Atamer Balkan, Dorine C. Duives et al.
Journal of Simulation
COVID-19 epidemiological studies
article

Infection risk and economic activity trade-offs: decision-making in indoor venue operations for pandemic preparedness

Yilin Huang, Quirine A. ten Bosch, Büşra Atamer Balkan, Dorine C. Duives, Martijn Sparnaaij
article en

Abstract

During epidemics, decision-making regarding intervention measures faces complex trade-offs. Interventions targeting indoor venues can mitigate disease spread, since they are associated with higher infection risk for respiratory pathogens. However, as experienced during the COVID-19 pandemic, these measures can lead to economic losses, especially in the hospitality sector. In this study, we propose a hybrid modeling and simulation framework to provide decision support for reducing the infection risk in indoor venues while maintaining viable economic activity. Our framework integrates (i) a microscopic pedestrian model for human movement, (ii) a hybrid simulation model for virus spread and transmission, and (iii) a multi-criteria decision-making approach to identify the best service options. The framework is demonstrated for the SARS-CoV-2 infection risk. The restaurant case study results illustrate that maximizing the distance between seating groups can have a limited effect on the infection risk. Service duration and service capacity are key determinants of expected economic activity, but they constitute significant trade-offs: the former has a substantial impact on the infection risk, and the latter drives the probability of infectious introductions. Our analysis demonstrates the need for multi-criteria approaches during an outbreak and consideration of the epidemiological context for operational decision-making, even at an individual venue.

Journal of Simulation
Wageningen University & Research (NL), Delft University of Technology (NL)
ZonMw, Technische Universiteit Delft, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases
Openalex Percentile: Top 69%
COVID-19 epidemiological studies
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