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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Sep 13, 2020
Date Accepted: Mar 3, 2021
Date Submitted to PubMed: Apr 9, 2021

The final, peer-reviewed published version of this preprint can be found here:

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

Benneyan J, Gehrke C, Ilies I, Nehls N

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

JMIR Public Health Surveill 2021;7(4):e24292

DOI: 10.2196/24292

PMID: 33667173

PMCID: 8030657

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

  • James Benneyan; 
  • Christopher Gehrke; 
  • Iulian Ilies; 
  • Nicole Nehls

ABSTRACT

Background:

Significant uncertainty exists in many countries about the safety of, and best strategies for, reopening college and university campuses until the Covid-19 pandemic is better controlled. Little also is known about the effects on-campus students may have on local higher-risk communities.

Objective:

We aimed to estimate potential community and campus Covid-19 exposures, infections, and mortality due to various university reopening and precaution plans under current ranges of assumptions and uncertainties.

Methods:

We developed and calibrated campus-only, community-only, and campus-x-community epidemic differential equation and agent-based models. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, accuracy optimization algorithms, and Monte Carlo simulation; models were cross-validated against each other using February-June 2020 data from heterogeneous U.S. counties and states. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites and publications. All scenarios were simulated assuming 16-week semesters and estimated ranges for Covid-19 prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Additional student and community exposures, infections, and mortality were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify intervention inputs with largest and smallest effects.

Results:

As a base case with no precautions (or no compliance), predicted 16-week student infections and mortality under normal operations ranged significantly from 471 to 9,495 (median: 2,286, SD: 2,627) and 0 to 123 (median: 9, SD: 14) per 10,000 students, respectively. The maximum active exposures across a semester was 15.76% of all students warranting tracing. Total additional community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21 per 10,000 residents, respectively. 1% and 5% of on-campus students were infected after a mean (SD) of 11 (3) and 76 (17) days, respectively; >10% students infected by the end of a semester in 34.8% of scenarios, with the greatest increase (first inflection point) occurring on average on day 84 (SD: 10.2 days). Common reopening precautions reduced infections by 24% to 26% and mortality by 36% to 50% in both populations. Uncertainties in many factors, however, produced tremendous variability in all results, ranging from medians by -67% to +342%.

Conclusions:

Consequences on community and student Covid-19 exposures, infections, and mortality of reopening physical campuses are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Implications include needs for criteria to adapt campus operations mid-semester, methods to detect when necessary, and contingency plans for doing so.


 Citation

Please cite as:

Benneyan J, Gehrke C, Ilies I, Nehls N

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

JMIR Public Health Surveill 2021;7(4):e24292

DOI: 10.2196/24292

PMID: 33667173

PMCID: 8030657

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