1. Quantitative risk assessment of COVID-19 aerosol transmission indoors: a mechanistic stochastic web application
- Author
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Michael H. Bergin, Lucas Rocha-Melogno, Katherine Crank, Gregory C. Gray, Kyle Bibby, and Marc A. Deshusses
- Subjects
2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,business.industry ,Stochastic modelling ,food and beverages ,General Medicine ,complex mixtures ,Aerosol ,Risk analysis (engineering) ,Transmission (telecommunications) ,Environmental Chemistry ,Web application ,Environmental science ,Aerosol inhalation ,business ,Risk assessment ,Waste Management and Disposal ,Water Science and Technology - Abstract
An increasing body of literature suggests that aerosol inhalation plays a primary role in COVID-19 transmission, particularly in indoor settings. Mechanistic stochastic models can help public health professionals, engineers, and space planners understand the risk of aerosol transmission of COVID-19 to mitigate it. We developed such model and a user-friendly web application to meet the need of accessible risk assessment tools during the COVID-19 pandemic. We built our model based on the Wells-Riley model of respiratory disease transmission, using quanta emission rates obtained from COVID-19 outbreak investigations. In this report, three modelled scenarios were evaluated and compared to epidemiological studies looking at similar settings: classrooms, weddings, and heavy exercise sessions. We found that the risk of long-range aerosol transmission increased 309-332% when people were not wearing masks, and 424-488% when the room was poorly ventilated in addition to no masks being worn across the scenarios. Also, the risk of transmission could be reduced by ∼40-60% with ventilation rates of 5 ACH for 1-4 h exposure events, and ∼70% with ventilation rates of 10 ACH for 4 h exposure events. Relative humidity reduced the risk of infection (inducing viral inactivation) by a maximum of ∼40% in a 4 h exposure event at 70% RH compared to a dryer indoor environment with 25% RH. Our web application has been used by more than 1000 people in 52 countries as of September 1st, 2021. Future work is needed to obtain SARS-CoV-2 dose-response functions for more accurate risk estimates.
- Published
- 2021
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