Modeling for COVID-19 college reopening decisions: Cornell, a case study

• Published in: Proceedings of the National Academy of Sciences - PNAS 2022-01, Vol.119 (2)
• Main Authors: Frazier, Peter I, Cashore, J Massey, Duan, Ning, Henderson, Shane G, Janmohamed, Alyf, Liu, Brian, Shmoys, David B, Wan, Jiayue, Zhang, Yujia
• Format: Article
• Language: English
• Subjects: Asymptomatic; Asymptomatic infection; Asymptomatic Infections - epidemiology; Biological Sciences; Colleges & universities; Coronaviruses; COVID-19; COVID-19 - diagnosis; COVID-19 - epidemiology; COVID-19 - prevention & control; COVID-19 - transmission; COVID-19 vaccines; Decision Making; Decisions; Epidemic models; Epidemiological Models; Epidemiology; Humans; Mass Screening; Mathematical models; Modelling; Pandemics; Parameter sensitivity; Parameter uncertainty; Physical Sciences; Return to School - methods; SARS-CoV-2 - isolation & purification; Screening; Students; Uncertainty; Undergraduate study; United States - epidemiology; Universities; Vaccination; Viral diseases; Young adults
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2112532119

We consider epidemiological modeling for the design of COVID-19 interventions in university populations, which have seen significant outbreaks during the pandemic. A central challenge is sensitivity of predictions to input parameters coupled with uncertainty about these parameters. Nearly 2 y into the pandemic, parameter uncertainty remains because of changes in vaccination efficacy, viral variants, and mask mandates, and because universities' unique characteristics hinder translation from the general population: a high fraction of young people, who have higher rates of asymptomatic infection and social contact, as well as an enhanced ability to implement behavioral and testing interventions. We describe an epidemiological model that formed the basis for Cornell University's decision to reopen for in-person instruction in fall 2020 and supported the design of an asymptomatic screening program instituted concurrently to prevent viral spread. We demonstrate how the structure of these decisions allowed risk to be minimized despite parameter uncertainty leading to an inability to make accurate point estimates and how this generalizes to other university settings. We find that once-per-week asymptomatic screening of vaccinated undergraduate students provides substantial value against the Delta variant, even if all students are vaccinated, and that more targeted testing of the most social vaccinated students provides further value.