Dataset Information

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

ABSTRACT:

Background

Colleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic.

Objective

To examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses.

Design

The Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued by students and faculty, accounting for community transmissions.

Data sources

Data from published literature were used to obtain parameters related to COVID-19 and contact-hours.

Target population

Undergraduate students and faculty at U.S. colleges.

Time horizon

One semester (105 days).

Perspective

Modified societal.

Intervention

COVID-19 mitigation strategies, including social distancing, masks, and routine laboratory screening.

Outcome measures

Infections among students and faculty per 5000 students and per 1000 faculty, isolation days, tests, costs, cost per infection prevented, and cost per quality-adjusted life-year (QALY).

Results of base-case analysis

Among students, mitigation strategies reduced COVID-19 cases from 3746 with no mitigation to 493 with extensive social distancing and masks, and further to 151 when laboratory testing was added among asymptomatic persons every 3 days. Among faculty, these values were 164, 28, and 25 cases, respectively. Costs ranged from about $0.4 million for minimal social distancing to about $0.9 million to $2.1 million for strategies involving laboratory testing ($10 per test), depending on testing frequency. Extensive social distancing with masks cost $170 per infection prevented ($49 200 per QALY) compared with masks alone. Adding routine laboratory testing increased cost per infection prevented to between $2010 and $17 210 (cost per QALY gained, $811 400 to $2 804 600).

Results of sensitivity analysis

Results were most sensitive to test costs.

Limitation

Data are from multiple sources.

Conclusion

Extensive social distancing with a mandatory mask-wearing policy can prevent most COVID-19 cases on college campuses and is very cost-effective. Routine laboratory testing would prevent 96% of infections and require low-cost tests to be economically attractive.

Primary funding source

National Institutes of Health.

SUBMITTER: Losina E

PROVIDER: S-EPMC7755069 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

Losina Elena E Leifer Valia V Millham Lucia L Panella Christopher C Hyle Emily P EP Mohareb Amir M AM Neilan Anne M AM Ciaranello Andrea L AL Kazemian Pooyan P Freedberg Kenneth A KA

Annals of internal medicine 20201221 4

<h4>Background</h4>Colleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic.<h4>Objective</h4>To examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses.<h4>Design</h4>The Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued b ...[more]

PMID: 33347322

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Project description:The COVID-19 pandemic poses an existential threat to many US residential colleges: either they open their doors to students in September or they risk serious financial consequences. To define SARS-CoV-2 screening performance standards that would permit the safe return of students to campus for the Fall 2020 semester. Decision and cost-effectiveness analysis linked to a compartmental epidemic model to evaluate campus screening using tests of varying frequency (daily-weekly), sensitivity (70%-99%), specificity (98%-99.7%), and cost ($10-$50/test). Reproductive numbers Rt = {1.5, 2.5, 3.5} defined three epidemic scenarios, with additional infections imported via exogenous shocks. We generally adhered to US government guidance for parameterization data. A hypothetical cohort of 5000 college-age, uninfected students. Main Outcome(s) and Measure(s): Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact. All measured over an 80-day, abbreviated semester. With Rt = 2.5, daily screening with a 70% sensitive, 98% specific test produces 85 cumulative student infections and isolation dormitory daily census averaging 108 (88% false positives). Screening every 2 (7) days nets 135 (3662) cumulative infections and daily isolation census 66 (252) with 73% (4%) false positives. Across all scenarios, test frequency exerts more influence on outcomes than test sensitivity. Cost-effectiveness analysis selects screening every {2, 1, 7} days with a 70% sensitive test as the preferred strategy for Rt = {2.5, 3.5, 1.5}, implying a screening cost of {$470, $920, $120} per student per semester. Conclusions & Relevance: Rapid, inexpensive and frequently conducted screening (even if only 70% sensitive) would be cost-effective and produce a modest number of COVID-19 infections. While the optimal screening frequency hinges on the success of behavioral interventions to reduce the base severity of transmission (Rt), this could permit the safe return of student to campus.

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Dataset Information

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

Background

Objective

Design

Data sources

Target population

Time horizon

Perspective

Intervention

Outcome measures

Results of base-case analysis

Results of sensitivity analysis

Limitation

Conclusion

Primary funding source

Publications

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

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