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- W3210538030 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." @default.
- W3210538030 created "2021-11-08" @default.
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- W3210538030 date "2021-11-13" @default.
- W3210538030 modified "2023-09-27" @default.
- W3210538030 title "Quantitative risk assessment of COVID-19 aerosol transmission indoors: a mechanistic stochastic web application" @default.
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- W3210538030 doi "https://doi.org/10.1080/09593330.2021.1998228" @default.
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