Browsing by Author "Cavanaugh, Kyle"

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    ItemOpen Access
    Assessment of Simulated Surveillance Testing and Quarantine in a SARS-CoV-2-Vaccinated Population of Students on a University Campus.
    (JAMA health forum, 2021-10) Motta, Francis C; McGoff, Kevin A; Deckard, Anastasia; Wolfe, Cameron R; Bonsignori, Mattia; Moody, M Anthony; Cavanaugh, Kyle; Denny, Thomas N; Harer, John; Haase, Steven B

    Importance

    The importance of surveillance testing and quarantine on university campuses to limit SARS-CoV-2 transmission needs to be reevaluated in the context of a complex and rapidly changing environment that includes vaccines, variants, and waning immunity. Also, recent US Centers for Disease Control and Prevention guidelines suggest that vaccinated students do not need to participate in surveillance testing.

    Objective

    To evaluate the use of surveillance testing and quarantine in a fully vaccinated student population for whom vaccine effectiveness may be affected by the type of vaccination, presence of variants, and loss of vaccine-induced or natural immunity over time.

    Design setting and participants

    In this simulation study, an agent-based Susceptible, Exposed, Infected, Recovered model was developed with some parameters estimated using data from the 2020 to 2021 academic year at Duke University (Durham, North Carolina) that described a simulated population of 5000 undergraduate students residing on campus in residential dormitories. This study assumed that 100% of residential undergraduates are vaccinated. Under varying levels of vaccine effectiveness (90%, 75%, and 50%), the reductions in the numbers of positive cases under various mitigation strategies that involved surveillance testing and quarantine were estimated.

    Main outcomes and measures

    The percentage of students infected with SARS-CoV-2 each day for the course of the semester (100 days) and the total number of isolated or quarantined students were estimated.

    Results

    A total of 5000 undergraduates were simulated in the study. In simulations with 90% vaccine effectiveness, weekly surveillance testing was associated with only marginally reduced viral transmission. At 50% to 75% effectiveness, surveillance testing was estimated to reduce the number of infections by as much as 93.6%. A 10-day quarantine protocol for exposures was associated with only modest reduction in infections until vaccine effectiveness dropped to 50%. Increased testing of reported contacts was estimated to be at least as effective as quarantine at limiting infections.

    Conclusions and relevance

    In this simulated modeling study of infection dynamics on a college campus where 100% of the student body is vaccinated, weekly surveillance testing was associated with a substantial reduction of campus infections with even a modest loss of vaccine effectiveness. Model simulations also suggested that an increased testing cadence can be as effective as a 10-day quarantine period at limiting infections. Together, these findings provide a potential foundation for universities to design appropriate mitigation protocols for the 2021 to 2022 academic year.
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    Implementation of a Pooled Surveillance Testing Program for Asymptomatic SARS-CoV-2 Infections on a College Campus - Duke University, Durham, North Carolina, August 2-October 11, 2020.
    (MMWR. Morbidity and mortality weekly report, 2020-11-20) Denny, Thomas N; Andrews, Laura; Bonsignori, Mattia; Cavanaugh, Kyle; Datto, Michael B; Deckard, Anastasia; DeMarco, C Todd; DeNaeyer, Nicole; Epling, Carol A; Gurley, Thaddeus; Haase, Steven B; Hallberg, Chloe; Harer, John; Kneifel, Charles L; Lee, Mark J; Louzao, Raul; Moody, M Anthony; Moore, Zack; Polage, Christopher R; Puglin, Jamie; Spotts, P Hunter; Vaughn, John A; Wolfe, Cameron R
    On university campuses and in similar congregate environments, surveillance testing of asymptomatic persons is a critical strategy (1,2) for preventing transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). All students at Duke University, a private research university in Durham, North Carolina, signed the Duke Compact (3), agreeing to observe mandatory masking, social distancing, and participation in entry and surveillance testing. The university implemented a five-to-one pooled testing program for SARS-CoV-2 using a quantitative, in-house, laboratory-developed, real-time reverse transcription-polymerase chain reaction (RT-PCR) test (4,5). Pooling of specimens to enable large-scale testing while minimizing use of reagents was pioneered during the human immunodeficiency virus pandemic (6). A similar methodology was adapted for Duke University's asymptomatic testing program. The baseline SARS-CoV-2 testing plan was to distribute tests geospatially and temporally across on- and off-campus student populations. By September 20, 2020, asymptomatic testing was scaled up to testing targets, which include testing for residential undergraduates twice weekly, off-campus undergraduates one to two times per week, and graduate students approximately once weekly. In addition, in response to newly identified positive test results, testing was focused in locations or within cohorts where data suggested an increased risk for transmission. Scale-up over 4 weeks entailed redeploying staff members to prepare 15 campus testing sites for specimen collection, developing information management tools, and repurposing laboratory automation to establish an asymptomatic surveillance system. During August 2-October 11, 68,913 specimens from 10,265 graduate and undergraduate students were tested. Eighty-four specimens were positive for SARS-CoV-2, and 51% were among persons with no symptoms. Testing as a result of contact tracing identified 27.4% of infections. A combination of risk-reduction strategies and frequent surveillance testing likely contributed to a prolonged period of low transmission on campus. These findings highlight the importance of combined testing and contact tracing strategies beyond symptomatic testing, in association with other preventive measures. Pooled testing balances resource availability with supply-chain disruptions, high throughput with high sensitivity, and rapid turnaround with an acceptable workload.