Numerical simulation on the transmission risk of SARS-CoV-2 during a typical elevator ride

Abstract

Throughout the COVID-19 pandemic, several cases of infection associated with elevator rides have been reported. To systematically assess the risk of droplet transmission in an elevator, this study employed computational fluid dynamics (CFD) together with a modified stochastic dose–response model to quantify the infection risk for occupants. Simulation is conducted during a 2-min elevator ride for two individuals facing each other, without considering mask-wearing. Various factors such as ventilation outlet position, ventilation rates, air temperature, relative humidity, ventilation techniques, breathing patterns, and body types have been analyzed in order to assess the inhalation risks for occupants. Their infection probabilities for different viral strains are also considered. The findings highlight the effectiveness of the top-to-bottom ventilation approach. Nasal breathing has risk-reducing benefits, and ventilation rates of 30–50 air changes per hour (ACH) play an important role in reducing the risk of infection. Moreover, the study further reveals that air curtain systems outperform side ventilation. Temperature, relative humidity, the infected individual’s breathing behavior, and the body types between infected and exposed individuals are shown to exert various degrees of influence on droplet transmission.