Modelling Airborne Transmission and Ventilation Impacts of a COVID-19 Outbreak in a Restaurant in Guangzhou, China

ABSTRACT

Computational fluid dynamics (CFD) modelling was performed to simulate spatial and temporal airborne pathogen concentrations during an observed COVID-19 outbreak in a restaurant in Guangzhou, China. The reported seating configuration, overlap durations, room ventilation, layout, and dimensions were modelled in the CFD simulations to determine relative exposures and probabilities of infection. Results showed that the trends in the simulated probabilities of infection were consistent with the observed rates of infection at each of the tables surrounding the index patient. Alternative configurations that investigated different boundary conditions and ventilation conditions were also simulated. Increasing the fresh-air percentage to 10%, 50%, and 100% of the supply air reduced the accumulated pathogen mass in the room by an average of ∼30%, ∼70%, and ∼80%, respectively, over 73 min. The probability of infection was reduced by ∼10%, 40%, and 50%, respectively.

Highlights

• Computational fluid dynamics (CFD) models used to simulate pathogen concentrations

• Infection model developed using spatial and temporal CFD results

• Simulating spatial variability was important to match observed infection rates

• Recirculation increased exposures and probability of infection

• Increased fresh-air ventilation decreased exposures and probability of infection

KEYWORDS:

• CFD
• Guangzhou restaurant
• COVID-19
• SARS-CoV-2
• ventilation
• airborne transmission

Acknowledgements

The author thanks Stefan Domino, Andres Sanchez, Andrew Glen, Joshua Hubbard, Flint Pierce, Keith Matzen, Walt Witkowski, Gil Herrera, and David Peabody (UNM) for helpful discussions and information exchanged during the course of this project. This project was funded by the COVID-19 Rapid Response LDRD program (Project 220717/02). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This project was funded by the COVID-19 Rapid Response LDRD program (Project 220717/02). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.