Risk assessment of airborne COVID-19 exposure in social settings

Abstract

The COVID-19 pandemic has led to many countries oscillating between various states of lock-down as they seek to balance keeping the economy and essential services running and minimizing the risk of further transmission. Decisions are made about which activities to keep open across a range of social settings and venues guided only by ad hoc heuristics regarding social distancing and personal hygiene. Hence, we propose the dual use of computational fluid dynamic simulations and surrogate aerosol measurements for location-specific assessment of risk of infection across different real-world settings. We propose a 3-tiered risk assessment scheme to facilitate classification of scenarios into risk levels based on simulations and experiments. Threshold values of <54 and >840 viral copies and <5% and >40% of original aerosol concentration are chosen to stratify low, medium, and high risk. This can help prioritize allowable activities and guide implementation of phased lockdowns or re-opening. Using a public bus in Singapore as a case study, we evaluate the relative risk of infection across scenarios such as different activities and passenger positions and demonstrate the effectiveness of our risk assessment methodology as a simple and easily interpretable framework. For example, this study revealed that the bus's air-conditioning greatly influences dispersion and increases the risk of certain seats and that talking can result in similar relative risk to coughing for passengers around an infected person. Both numerical and experimental approaches show similar relative risk levels with a Spearman's correlation coefficient of 0.74 despite differing observables, demonstrating applicability of this risk assessment methodology to other scenarios.

Computational study on the transmission of the SARS-CoV-2 virus through aerosol in an elevator cabin: Effect of the ventilation system

“…We hope that the approach used and the insight gained in this study will be illuminating, e.g., in the settings of buses, classrooms and conference rooms. 61–63 Other effects like Brownian motion might be needed in future studies. 64 Hopefully more researchers will conduct similar investigations for crowded public places as we battle the SARS-CoV-2 virus.…”

A review on indoor airborne transmission of COVID-19– modelling and mitigation approaches

“…A detailed mathematical description related to the evaporation of the water content of particles can be found in reference [ 106 ]. It should be noted that numerical studies focusing on the dispersion of heavy particles (droplets) have modeled the evaporation of particles along with their properties [ 88 , 89 , 112 , 124 , 125 ]. However, based on our review and observations, in most previous works, the characteristics of small particles ejected have been assumed to be similar to that of water.…”

The emission and dynamics of droplets from human expiratory activities and COVID-19 transmission in public transport system: A review

“…(2) 59% of the initial droplets are deposited within 2 m, and droplet concentration declines to 87% at 3 m. Mesgarpour et al, 2021 [ 63 ] Bus CFD and measurement 3.6 m s −1 from supply vent; 1.9 m s −1 from supply vent The neighboring passengers down-wind of the cougher are typically at a higher risk than the other passengers. Ooi et al, 2021 [ 58 ] Bus CFD Ventilation off in a stationary bus; different sets of windows opened (1) Opening the window next to the index case leads to high exposure to the front. (2) Opening the windows in the front row reduces the exposure.…”

“…The seating of the index case and other passengers relative to the air supply and return is an important factor influencing the infection risk. Ooi et al [ 58 ] found that the neighboring passengers downwind of the cougher are typically at a higher risk than the other passengers. When the infection source is near the return outlet, the infection risk for other passengers decreases [ 23 ].…”