Simulation-Based Analysis of COVID-19 Spread Through Classroom Transmission on a University Campus
Arvin Hekmati, Mitul Luhar, Bhaskar Krishnamachari, Maja Matari\'c

TL;DR
This study models airborne COVID-19 transmission in university classrooms, evaluating how factors like masks, occupancy, and hybrid learning impact infection spread using simulation based on real course data.
Contribution
It introduces a novel $R_0^{eff}$ metric for classroom-specific transmission risk and applies it to real university data to compare in-person and hybrid class scenarios.
Findings
Universal mask usage reduces infections by 3.6 times.
Moving 90% of classes online reduces cases by 18 times.
Reducing occupancy to 20% further cuts infections by over 2 times.
Abstract
Airborne transmission is now believed to be the primary way that COVID-19 spreads. We study the airborne transmission risk associated with holding in-person classes on university campuses. We utilize a model for airborne transmission risk in an enclosed room that considers the air change rate for the room, mask efficiency, initial infection probability of the occupants, and also the activity level of the occupants. We introduce, and use for our evaluations, a metric that represents the ratio of new infections that occur over a week due to classroom interactions to the number of infected individuals at the beginning of the week. This can be seen as a surrogate for the well-known reproductive number metric, but limited in scope to classroom interactions and calculated on a weekly basis. The simulations take into account the possibility of repeated in-classroom…
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