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

Abstract

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