Comparative assessment of airborne infection risk tools in enclosed spaces: Implications for disease control

Amar Aganovic; Giorgio Buonanno; Guangyu Cao; Christian Delmaar; Jarek Kurnitski; Alex Mikszewski; Lidia Morawska; Lucie C Vermeulen; Pawel Wargocki

doi:10.1016/j.idm.2024.11.003

Comparative assessment of airborne infection risk tools in enclosed spaces: Implications for disease control

Infect Dis Model. 2024 Nov 28;10(1):338-352. doi: 10.1016/j.idm.2024.11.003. eCollection 2025 Mar.

Authors

Amar Aganovic¹, Giorgio Buonanno^{2

3}, Guangyu Cao⁴, Christian Delmaar⁵, Jarek Kurnitski^{6

7}, Alex Mikszewski³, Lidia Morawska^{3

8}, Lucie C Vermeulen⁵, Pawel Wargocki⁹

Affiliations

¹ Department of Automation and Process Engineering, UiT the Arctic University of Norway, Tromsø, Norway.
² Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy.
³ International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld, Australia.
⁴ Department of Energy and Process Engineering, Norwegian University of Science and Technology - NTNU, Trondheim, Norway.
⁵ Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
⁶ Department of Civil Engineering and Architecture, Tallinn University of Technology, Tallinn, Estonia.
⁷ Department of Civil Engineering, Aalto University, Espoo, Finland.
⁸ Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, United Kingdom.
⁹ Department of Environmental and Resource Engineering, Technical University of Denmark, Copenhagen, Denmark.

Abstract

The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the importance of understanding transmission modes and implementing effective mitigation strategies. Recognizing airborne transmission as a primary route has reshaped public health measures, emphasizing the need to optimize indoor environments to reduce risks. Numerous tools have emerged to assess airborne infection risks in enclosed spaces, providing valuable resources for public health authorities, researchers, and the general public. However, comparing the outputs of these tools is challenging because of variations in assumptions, mathematical models, and data sources. We conducted a comprehensive review, comparing digital airborne infection risk calculators using standardized building-specific input parameters. These tools generally produce similar and consistent outputs with identical inputs. Variations mainly stem from model selection and the handling of unsteady viral load conditions. Differences in source term calculations, including particle emission concentrations and respiratory activity, also contribute to disparities. These differences are minor compared to the inherent uncertainties in risk assessment. Consistency in results increases with higher ventilation rates, showing a robust trend across models. However, inconsistencies arose in the inclusion of face masks, often due to the lack of detailed efficiency values. Despite some differences, the overall consistency underscores the value of these tools in public health strategy and infectious disease control. We also compared some of the model's efforts to conduct retrospective assessments against reported transmission events by assuming input parameters to the models so that the calculated risk would closely fit the original outbreak infection rate. Thus, validating these models against past outbreaks remains challenging because of the lack of essential input information from observed events. This comparative analysis demonstrates the importance of transparent data sources and justifiable model assumptions to enhance the reliability and precision of risk assessments.

Keywords: Airborne transmission; Infection risk calculators; Infection risk tools; Respiratory virus.