Community and Campus COVID-19 Risk Uncertainty Under University Reopening Scenarios: Model-Based Analysis (Preprint)

Abstract

BACKGROUND Significant uncertainty has existed about the safety of reopening college and university campuses before the COVID-19 pandemic is better controlled. Moreover, little is known about the effects that on-campus students may have on local higher-risk communities. OBJECTIVE We aimed to estimate the range of potential community and campus COVID-19 exposures, infections, and mortality under various university reopening plans and uncertainties. METHODS We developed campus-only, community-only, and campus × community epidemic differential equations and agent-based models, with inputs estimated via published and grey literature, expert opinion, and parameter search algorithms. Campus opening plans (spanning fully open, hybrid, and fully virtual approaches) were identified from websites and publications. Additional student and community exposures, infections, and mortality over 16-week semesters were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outliers. Sensitivity analyses were conducted to inform potential effective interventions. RESULTS Predicted 16-week campus and additional community exposures, infections, and mortality for the base case with no precautions (or negligible compliance) varied significantly from their medians (4- to 10-fold). Over 5% of on-campus students were infected after a mean of 76 (SD 17) days, with the greatest increase (first inflection point) occurring on average on day 84 (SD 10.2 days) of the semester and with total additional community exposures, infections, and mortality ranging from 1-187, 13-820, and 1-21 per 10,000 residents, respectively. Reopening precautions reduced infections by 24%-26% and mortality by 36%-50% in both populations. Beyond campus and community reproductive numbers, sensitivity analysis indicated no dominant factors that interventions could primarily target to reduce the magnitude and variability in outcomes, suggesting the importance of comprehensive public health measures and surveillance. CONCLUSIONS Community and campus COVID-19 exposures, infections, and mortality resulting from reopening campuses are highly unpredictable regardless of precautions. Public health implications include the need for effective surveillance and flexible campus operations.

Validation of “Personal Protective Equipment Conservation Strategies Tool” to Predict Consumption of N95s, Facemasks, and Gowns During Pandemic-Related Shortages

“…Although these models could be modified to focus exclusively on ED PPE consumption, neither could be used to predict PPE consumption based on the most restrictive strategies for PPE used in our setting. Even using the staffing-based calculations of other models, the total number of patients is a required input to predict PPE consumption 16,17 . In our setting, stakeholders recommended restrictive PPE strategies requiring staff to reuse PPE across one or multiple shifts, independent of patient load and length of stay.…”

“…These resources use average consumption of PPE to estimate future use, relying on a number of assumptions around disease burden stability. Other simulation models to predict the consumption of PPE, developed concurrently to our own, generate outputs for a hospital, including inpatient and ICU patients 16,17 . Although these models could be modified to focus exclusively on ED PPE consumption, neither could be used to predict PPE consumption based on the most restrictive strategies for PPE used in our setting.…”