Background

Despite severe outbreaks of COVID-19 among colleges and universities across the USA during the Fall 2020 semester, the majority of institutions did not routinely test students. While high-frequency repeated testing is considered the most effective strategy for disease mitigation, most institutions do not have the necessary infrastructure or funding for implementation. Therefore, alternative strategies for testing the student population are needed. Our study detailed the implementation and results of testing strategies to mitigate SARS-CoV-2 spread on a university campus, and we aimed to assess the relative effectiveness of the different testing strategies.

Methods

For this retrospective cohort study, we included 6273 on-campus students arriving to a large public university in the rural USA (Clemson, SC, USA) for in-person instruction in the Fall 2020 semester (Sept 21 to Nov 25). Individuals arriving after Sept 23, those who tested positive for SARS-CoV-2 before Aug 19, and student athletes and band members were not included in this study. We implemented two testing strategies to mitigate SARS-CoV-2 spread during this period: a novel surveillance-based informative testing (SBIT) strategy, consisting of random surveillance testing to identify outbreaks in residence hall buildings or floors and target them for follow-up testing (Sept 23 to Oct 5); followed by a repeated weekly surveillance testing (Oct 6 to Nov 22). Relative changes in estimated weekly prevalence were examined. We developed SARS-CoV-2 transmission models to compare the relative effectiveness of weekly testing (900 daily surveillance tests), SBIT (450 daily surveillance tests), random surveillance testing (450 daily surveillance tests), and voluntary testing (0 daily surveillance tests) on disease mitigation. Model parameters were based on our empirical surveillance data in conjunction with published sources.

Findings

SBIT was implemented from Sept 23 to Oct 5, and identified outbreaks in eight residence hall buildings and 45 residence hall floors. Targeted testing of residence halls was 2·03 times more likely to detect a positive case than random testing (95% CI 1·67–2·46). Weekly prevalence was reduced from a peak of 8·7% to 5·6% during this 2-week period, a relative reduction of 36% (95% CI 27–44). Prevalence continued to decrease after implementation of weekly testing, reaching 0·8% at the end of in-person instruction (week 9). SARS-CoV-2 transmission models concluded that, in the absence of SBIT (ie, voluntary testing only), the total number of COVID-19 cases would have increased by 154% throughout the semester. Compared with SBIT, random surveillance testing alone would have resulted in a 24% increase in COVID-19 cases. Implementation of weekly testing at the start of the semester would have resulted in 36% fewer COVID-19 cases throughout the semester compared with SBIT, but it would require twice the number of daily tests.

Interpretation

It is imperative that institutions rigorously test students during the 2021 academic year. When high-frequency testing (eg, weekly) is not possible, SBIT is an effective strategy to mitigate disease spread among the student population that can be feasibly implemented across colleges and universities.

Funding

Clemson University, USA.

中文翻译：

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基于监测的信息测试，用于检测和遏制公立大学校园内的 SARS-CoV-2 爆发：一项观察和建模研究

背景

尽管 2020 年秋季学期在美国各地的高校中爆发了严重的 COVID-19，但大多数机构并未对学生进行常规测试。虽然高频重复检测被认为是缓解疾病最有效的策略，但大多数机构没有实施所需的基础设施或资金。因此，需要用于测试学生群体的替代策略。我们的研究详细介绍了减轻 SARS-CoV-2 在大学校园传播的测试策略的实施和结果，我们旨在评估不同测试策略的相对有效性。

方法

在这项回顾性队列研究中，我们纳入了 6273 名在校学生，他们在 2020 年秋季学期（9 月 21 日至 11 月 25 日）抵达美国农村地区（美国南卡罗来纳州克莱姆森）的一所大型公立大学接受面对面教学。9 月 23 日之后抵达的个人、8 月 19 日之前 SARS-CoV-2 检测呈阳性的个人以及学生运动员和乐队成员不包括在本研究中。在此期间，我们实施了两种测试策略来减轻 SARS-CoV-2 的传播：一种新型的基于监测的信息测试 (SBIT) 策略，包括随机监测测试，以识别宿舍楼或楼层的疫情并针对它们进行后续跟进测试（9 月 23 日至 10 月 5 日）；随后每周重复进行一次监测测试（10 月 6 日至 11 月 22 日）。检查了估计的每周患病率的相对变化。我们开发了 SARS-CoV-2 传播模型来比较每周测试（900 次每日监测测试）、SBIT（450 次每日监测测试）、随机监测测试（450 次每日监测测试）和自愿测试（0 次每日监测测试）的相对有效性) 减轻疾病。模型参数基于我们的经验监测数据以及已发布的资源。

发现

SBIT 于 9 月 23 日至 10 月 5 日实施，并在 8 栋宿舍楼和 45 层宿舍楼中发现了疫情。宿舍的针对性测试检测出阳性病例的可能性是随机测试的 2·03 倍 (95% CI 1·67–2·46)。在这 2 周期间，每周流行率从 8·7% 的峰值降低到 5·6%，相对降低了 36% (95% CI 27–44)。在实施每周测试后，患病率继续下降，在面对面指导结束时（第 9 周）达到 0·8%。SARS-CoV-2 传播模型得出的结论是，在没有 SBIT（即仅自愿检测）的情况下，整个学期 COVID-19 病例总数将增加 154%。与 SBIT 相比，仅随机监测测试就会导致 COVID-19 病例增加 24%。

解释

机构必须在 2021 学年严格测试学生。当无法进行高频检测（例如，每周一次）时，SBIT 是一种有效的策略，可以减轻疾病在学生群体中的传播，并且可以跨高校实施。

资金

美国克莱姆森大学。