Comparing methods of calculating COVID-19 transmission risk in classrooms
Comparing methods of calculating COVID-19 transmission risk in classrooms lead image
Children are back in school in the U.S. as the COVID-19 pandemic continues. To help government and school officials make informed decisions about the viability of in-person schooling during a pandemic, scientists have conducted risk assessment studies on virus exposure in classrooms.
Most of these studies use a mathematical Wells-Riley model to model transmission. Foster et al. compared the Wells-Riley model with a different model known as Computational Fluid Dynamics for modeling airborne disease transmission. Their research showed that CFD agrees closely with the Wells-Riley model, and also provided a more detailed method of investigating transmission paths.
“Even for a simple classroom with 10 occupants there are 90 different potential ‘infectious – susceptible’ transmission paths,” said author Aaron Foster. “By studying all of these paths we were able to reveal a large variation in risk due to the varying air patterns in the room.”
The researchers used the models to see how transmission occurs during an hour-long class.
“This is an area of uncertainty that hasn’t been considered in this level of detail,” said Foster. “I believe it is important both for understanding how to reduce the spread of COVID-19 and also for studying the mechanics of super-spreading events.”
They hope their work will help refine Wells-Riley calculators for use in other research.
“Although this work has been focused on COVID-19, the concepts and analysis techniques can be applied to any application where the inhalation of an aerosol or gas in an enclosed space is important,” said Foster. “These concepts could be applied to other areas such as industrial safety, biological weapons defense and other airborne diseases.”
Source: “Estimating COVID-19 exposure in a classroom setting: A comparison between mathematical and numerical models,” by Aaron Foster and Michael Kinzel, Physics of Fluids (2021). The article can be accessed at https://doi.org/10.1063/5.0040755 .
This paper is part of the open 2021 Flow and the Virus Special Collection, learn more here . Submission Deadline: June 30, 2021.
