Model Simulates How Quickly COVID-19 Can Spread On A College Campus
A new model is cautiously optimistic about a university’s ability to control the spread of COVID-19 this fall—but that hinges largely on how much students socialize off-campus.
The model simulates a residential university with around 20,000 students and 2,500 instructors—not too dissimilar from Illinois State University. The researchers ran the model with and without different interventions to see how quickly COVID-19 would spread over a 100-day period. Their “baseline” interventions included moving all classes with 30+ students online, universal mask-wearing that is enforced, daily randomized testing of 3% of the university community, and other measures.
If those interventions are all in place, the model showed less than 66 infections in more than 95% of simulations.
“But there are a lot of ‘ifs’ in those sentences, and that’s where our main concern is. Because it’s a chain. And it’s only as strong its weakest link,” said Philip Gressman, a math professor at the University of Pennsylvania. He developed the model with Jennifer Peck, an economics professor at Swarthmore College.
Peck and Gressman’s model addresses some of the incredibly complex issues that colleges and universities are grappling with across the country. ISU’s administration will release updated reopening guidance this week. It is expected to include more work-from-home flexibility to help de-densify campus.
So which interventions were most effective in their model? Moving online any class with 30+ students was very effective. (ISU's Redbirds Return plan recommends moving "as many classes as possible with 50+ students to an online format.")
Requiring masks was “moderately important” in their model, and random testing and contact tracing had a lesser impact.
The researchers' model is based on the assumption students will refrain from most social contact while off campus—an assumption Peck herself concedes is “very optimistic.”
“What we’ve shown is that if the social side is under control, you can manage the spread through academic contacts. So having said that, can you get the social side of the contacts under control? At this point, that’s a first-order question,” Peck said.
Colleges will have to be intentional about educating students about the importance of social distancing and other measures.
“The fall is going to be really strange,” Gressman said. “Imagine what it’s going to be like if we’re successful. If we are, there’s gonna be this massive, highly visible effort to maintain control of the virus, and if we’re successful, students won’t see any infections at all. If it’s working, it will look like it’s wasted effort.”
And the universities themselves will have to avoid unforced errors.
One of them is over-quarantining. Peck and Gressman’s model flags that issue as stemming from the rate of false positives in current coronavirus tests. If you’re testing 3% of the campus every day, even a false positive rate of 0.8% would generate about five false positives per day. That could needlessly send 50 to 100 people into quarantine every day even if they were never at risk.
The solution: Re-run every positive test to make sure.
“If the prevalence is low, running the positive test again shouldn’t be very expensive because there’s not that many of them,” Gressman said. “It involves thinking about things differently and changing the way you’re being skeptical. When you see a positive test, don’t assume that it’s real. Check it.”
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