Quantitative Microbial Risk Assessment for Airborne Transmission of SARS-CoV-2 via Breathing, Speaking, Singing, Coughing, and Sneezing.

BACKGROUND: Evidence for indoor airborne transmission of SARS-CoV-2 is accumulating. OBJECTIVES: We assessed of the risk of illness due to airborne SARS-CoV-2 particles from breathing, speaking, singing, coughing, and sneezing in indoor environments. METHODS: A risk assessment model, AirCoV2, for exposure to SARS-CoV-2 particles in aerosol droplets was developed. Previously published data on droplets expelled by breathing, speaking, singing, coughing, and sneezing by an infected person were used as inputs. Scenarios encompassed virus concentration, exposure time, and ventilation. Newly collected data of virus RNA copies in mucus from patients are presented. RESULTS: The expelled volume of aerosols was highest for a sneeze, followed by a cough, singing, speaking, and breathing. After 20 min of exposure, at 107 RNA copies/mL in mucus, all mean illness risks were largely estimated to be below 0.001, except for the "high" sneeze scenario. At virus concentrations above 108 RNA copies/mL, and after 2 h of exposure, in the high and "low" sneeze scenarios, the high cough scenario and the singing scenario, risks exceeded 0.01 and may become very high, whereas the low coughing scenario, the high and low speaking scenarios and the breathing scenario remained below 0.1. After 2 h of exposure, singing became the second highest risk scenario. One air exchange per hour reduced risk of illness by about a factor of 2. Six air exchanges per hour reduced risks of illness by a factor of 8-13 for the sneeze and cough scenarios and by a factor of 4-9 for the other scenarios. DISCUSSION: The large variation in the volume of expelled aerosols is discussed. The model calculations indicated that SARS-CoV-2 transmission via aerosols outside of the 1.5-m social distancing norm can occur. Virus concentrations in aerosols and/or the amount of expelled aerosol droplets need to be high for substantial transmission via this route. AirCoV2 is made available as interactive computational tool. https://doi.org/10.1289/EHP7886.