In a recent article in Nature, the COVID19 response for the University of Illinois at Urbana campus was detailed. Although a spike in cases reported at the end of August, 2020 led to some national news coverage suggesting it was a failure, I nevertheless consider it an illustration of good practices that should be emulated elsewhere.
The University of Illinois policy includes seven key elements that I consider to be essential, two of which are analytics:
Local-Level Analytic Model | Campus-level epidemic model estimates outcomes of policy alternatives Model includes assumptions regarding behavioral response to policies Model assumptions are explicit Model constructed and interpreted by team of data scientists |
Frequent Mandatory Testing | Saliva-based test reduces burden and discomfort Test required to be done by all students and faculty twice each week (which is 10-15 thousand tests per day) Samples acquired in 20 open-air tents around campus staffed by 200 people No RNA isolation step for test process to reduce cost and elapsed time Pre-process samples in warm water bath to inactivate virus for lab technician safety Samples processed by a team of 25 technicians working in shifts Results available on cell phone app within 24 hours Admission to campus buildings requires proof of compliance with testing |
Fast and Active Contact Tracing | Team of 60 contact tracers organized by campus Use multiple modes of contact, not just text messages and phone calls. |
Isolation of Cases and Contacts | 400 dorm rooms set aside for students living on campus to isolate or quarantine Target is to get everyone who tests positive isolated within 30 minutes of the result being available. |
Consequences for Non-Compliance | Failure to comply with testing leads to loss of academic standing Suspension of students going to parties despite positive results |
Dashboard Reports | Dashboard reporting |
Dynamic Policy Response | When a spike occurred due to students with positive results attending parties, they implemented 2-week ban on socializing in groups, increased test frequency in fraternity houses and dormitories where there were problems, and modified assumptions in analytic model |
The University of Illinois COVID19 dashboard reports are frequently updated, and illustrate the spike in new cases at the end of August and the subsequent decline in cases after the dynamic policy response was initiated. Also of note, because of the high rate of testing, the test positivity rate is at 0.44%, and even in the peak it never rose above 3%.