Simulation-Based What-If Analysis for Controlling the Spread of COVID-19 in Universities
21 Pages Posted: 2 Sep 2020 Last revised: 3 Sep 2020
Date Written: August 24, 2020
A simulation model is developed to analyze the spread of COVID-19 in universities. The model can be used to conduct what-if analysis and to estimate infection cases and the probability of death for students and faculty/staff under different policies. For proof-of-concept, the model is simulated for a hypothetical university of 25,000 students and 3,000 faculty/staff in a US college town. In this case, students arrive on campus in September and the semester is planned to last for a 90-day period. In base run, absent major policies other than reactive testing at 500 tests per day (sensitivity=.8, specificity=.998), limited quarantine of 170 beds, and R0=3, the disease quickly spreads and the probability of having at least 1, 2, and 5 deaths by the middle of the semester reaches .94, .78, and .16 for students, and ~1, ~1, and ~1 for faculty/staff. Simulation results show that there is no silver bullet to avoid an outbreak and, instead, a combination of policies should be carefully implemented. The effectiveness of proactive testing highly depends on testing capacity (to maintain high test frequency) and, inversely, on the delay between symptom onset and test results. Contact tracing and quarantine only when combined with other policies such as rapid, frequent testing and mask use enforcement are effective. To decrease death likelihood, universities should ask all staff/faculty of over 60 years old, and a large fraction of 30-60 years old to work remotely.
Simulation results suggest these alternatives:
1) (almost) full remote operation from the beginning,
2) remote operation for high-risk individuals (all over 60s and most of 30-60s) in addition to frequent rapid tests, contact tracing with high capacity for quarantine, enforcing mask use, and social distancing.
Results show that the system is highly vulnerable, and considering implementation challenges, many universities are likely to close and switch to remote classes to avoid catastrophic outcomes. A simulation platform for what-if analysis is offered so marginal effectiveness of different policies, and different decision making thresholds for closure can be tested for universities of varying populations.
The model in Vensim is available. A web app is provided at https://forio.com/app/navidg/covid-19-v2/ and an instructional video is available at https://youtu.be/PrYarrpqa4Y for further analysis.
Note: Funding: None to declare
Declaration of Interest: None to declare
Keywords: COVID-19, coronavirus, SEIR, simulation, universities, college town, what-if analysis, system dynamics
Suggested Citation: Suggested Citation