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Modeling the Risk of In-Person Instruction During the COVID-19 Pandemic

Author

Listed:
  • Brian Liu

    (Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Yujia Zhang

    (Center for Applied Mathematics, Cornell University, Ithaca, New York 14853)

  • Shane G. Henderson

    (School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853)

  • David B. Shmoys

    (School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853)

  • Peter I. Frazier

    (School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853)

Abstract

During the COVID-19 pandemic, safely implementing in-person indoor instruction was a high priority for universities nationwide. To support this effort at Cornell University, we developed a mathematical model for estimating the risk of SARS-CoV-2 transmission in university classrooms. This model was used to evaluate combinations of feasible interventions for classrooms at Cornell during the COVID-19 pandemic and identify the best set of interventions that allow for higher occupancy levels, matching the prepandemic numbers of in-person courses, despite a limited number of large classrooms. Importantly, we determined that requiring masking in dense classrooms with unrestricted seating when more than 90% of students were vaccinated was easy to implement, incurred little logistical or financial cost, and allowed classes to be held at full capacity. A retrospective analysis at the end of the semester confirmed the model’s assessment that the proposed classroom configuration was safe. Our framework is generalizable and was used to support reopening decisions at Stanford University. In addition, our framework is flexible and applies to a wide range of indoor settings. It was repurposed for large university events and gatherings, and it can be used to support planning indoor space use to avoid transmission of infectious diseases across various industries, from secondary schools to movie theaters and restaurants.

Suggested Citation

  • Brian Liu & Yujia Zhang & Shane G. Henderson & David B. Shmoys & Peter I. Frazier, 2024. "Modeling the Risk of In-Person Instruction During the COVID-19 Pandemic," Interfaces, INFORMS, vol. 54(6), pages 537-552, November.
    • Handle: RePEc:inm:orinte:v:54:y:2024:i:6:p:537-552
    DOI: 10.1287/inte.2023.0076
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    References listed on IDEAS

    as
    1. Ewen Callaway, 2021. "Delta coronavirus variant: scientists brace for impact," Nature, Nature, vol. 595(7865), pages 17-18, July.
    2. Amy B. Gore & Mary E. Kurz & Matthew J. Saltzman & Blake Splitter & William C. Bridges & Neil J. Calkin, 2022. "Clemson University’s Rotational Attendance Plan During COVID-19," Interfaces, INFORMS, vol. 52(6), pages 553-567, November.
    3. Carol Johnson & Rick L. Wilson, 2022. "Practice Summary: A Multiobjective Assignment Model for Optimal Socially Distanced Classrooms for the Spears School of Business at Oklahoma State University," Interfaces, INFORMS, vol. 52(3), pages 295-300, May.
    4. Lauren E Cipriano & Wael M R Haddara & Gregory S Zaric & Eva A Enns, 2021. "Impact of university re-opening on total community COVID-19 burden," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-16, August.
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