Simulating COVID-19 in a University Environment

TL;DR

This study uses a detailed agent-based model to evaluate COVID-19 mitigation strategies in universities, highlighting the importance of testing, contact tracing, class size reduction, and managing social exposure for safe in-person instruction.

Contribution

It introduces a comprehensive stochastic agent-based simulation to assess COVID-19 interventions in university settings, providing insights into effective measures for outbreak control.

Findings

Large-scale testing, contact tracing, and quarantining are essential.

High test specificity reduces quarantine burden.

Moving large classes online helps control outbreaks.

Abstract

Residential colleges and universities face unique challenges in providing in-person instruction during the COVID-19 pandemic. Administrators are currently faced with decisions about whether to open during the pandemic and what modifications of their normal operations might be necessary to protect students, faculty and staff. There is little information, however, on what measures are likely to be most effective and whether existing interventions could contain the spread of an outbreak on campus. We develop a full-scale stochastic agent-based model to determine whether in-person instruction could safely continue during the pandemic and evaluate the necessity of various interventions. Simulation results indicate that large scale randomized testing, contact-tracing, and quarantining are important components of a successful strategy for containing campus outbreaks. High test specificity is critical for keeping the size of the quarantine population manageable. Moving the largest classes online is also crucial for controlling both the size of outbreaks and the number of students in quarantine. Increased residential exposure can significantly impact the size of an outbreak, but it is likely more important to control non-residential social exposure among students. Finally, necessarily high quarantine rates even in controlled outbreaks imply significant absenteeism, indicating a need to plan for remote instruction of quarantined students.