Wang, Zhaozhi ORCID: https://orcid.org/0000-0002-8986-0554, Jia, Fuchen ORCID: https://orcid.org/0000-0003-1850-7961, Galea, Edwin ORCID: https://orcid.org/0000-0002-0001-6665, Ewer, John ORCID: https://orcid.org/0000-0003-0609-272X and Grandison, Angus ORCID: https://orcid.org/0000-0002-9714-1605 (2025) Transmission of SARS-CoV-2 via larger respiratory droplets in a restaurant environment. Safety Science. ISSN 0925-7535 (Print), 1879-1042 (Online) (In Press)

	PDF (Author's Accepted Manuscript) 50732 GALEA_Transmission_Of_SARS-CoV-2_Via_Larger_Respiratory_Droplets_In_A_Restaurant_Environment_(AAM)_2025.pdf - Accepted Version Restricted to Repository staff only Download (1MB) | Request a copy
	PDF (Supplemental Material) 50732 GALEA_Transmission_Of_SARS-CoV-2_Via_Larger_Respiratory_Droplets_In_A_Restaurant_Environment_(SUPPLEMENTAL)_2025.pdf - Supplemental Material Restricted to Repository staff only Download (1MB) | Request a copy

Abstract

A coupled Wells-Riley and CFD modelling technique utilising a multi-size droplet approach is adopted to investigate the transmission route in a COVID-19 infection event. The event occurred in a restaurant in China during 2020 and involved a single suspected index patient and 88 other patrons. Using a multi-size droplet approach involving droplets up to 40 µm and a back-calculated quanta generation rate, nine secondary infections are predicted in the infection region, as in actual event. Furthermore, in the non-infection region, seating 68 susceptibles, an additional 1.7 infections are predicted. This compares with 23.3 infections when using the aerosol modelling approach (1 µm droplets). It is also estimated, using tracer gas data from an experiment conducted in this restaurant and simulation data using a small droplet model (5 µm), both reported in the literature, that there would be 22.0 and 6.1 infections respectively, within the non-infection region. Thus, from these studies, only the multi-size droplet model, with droplets up to 40 µm can produce a reasonable estimation of the number of secondary infections. This suggests that the transmission of SARS-CoV-2 in this event is dominated by larger droplets, not aerosols or small droplets. The study also suggests that for this event, high ventilation rates alone are not an appropriate mitigation. This research challenges the findings of other researchers that infections in this event were due to small droplets and poor ventilation. Furthermore, table partitions and restricting dining duration are demonstrated to mitigate infection risk, reducing secondary infections by over 50%.

This is potentially a high impact paper as it represents an important validation of the coupled CFD-Wells Riley modelling approach. It demonstrates an important capability for predicting infection probability resulting from airborne pathogens. It also demonstrates that aerosols cannot explain infection events within a restaurant environment.

Item Type:	Article
Uncontrolled Keywords:	COVID-19, restaurant environment, CFD, Wells-Riley model, larger droplet, ventilation, table partition.
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QR Microbiology > QR355 Virology
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	26 Jun 2025 07:59
URI:	https://gala.gre.ac.uk/id/eprint/50732

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