Journal
PHYSICS OF FLUIDS
Volume 33, Issue 2, Pages -Publisher
AIP Publishing
DOI: 10.1063/5.0040755
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Funding
- National Science Foundation [2031227]
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The COVID-19 pandemic has prompted studies of airborne transmission risk using Wells-Riley and computational fluid dynamics (CFD) models. Ventilation with moderate filtration in a classroom setting can reduce infection transmission probability significantly. Individual transmission route infection probabilities vary significantly, with local air patterns being the main driving factor.
The COVID-19 pandemic has driven numerous studies of airborne-driven transmission risk primarily through two methods: Wells-Riley and computational fluid dynamics (CFD) models. This effort provides a detailed comparison of the two methods for a classroom scenario with masked habitants and various ventilation conditions. The results of the studies concluded that (1) the Wells-Riley model agrees with CFD results without forced ventilation (6% error); (2) for the forced ventilation cases, there was a significantly higher error (29% error); (3) ventilation with moderate filtration is shown to significantly reduce infection transmission probability in the context of a classroom scenario; (4) for both cases, there was a significant amount of variation in individual transmission route infection probabilities (up to 220%), local air patterns were the main contributor driving the variation, and the separation distance from infected to susceptible was the secondary contributor; (5) masks are shown to have benefits from interacting with the thermal plume created from natural convection induced from body heat, which pushes aerosols vertically away from adjacent students.
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