Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks
Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks
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COVID-19 大流行期间重新开放大学：最大限度减少活跃病例并延迟疫情爆发的测试策略
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发表时间：
2020
期刊：
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通讯作者：
C. McMahan
中科院分区：
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作者：
L. Rennert;C. Kalbaugh;Lu Shi;C. McMahan
背景资料：大学校园是病毒传播的理想环境，因此极有可能成为COVID-19爆发的温床。虽然整个学期的积极监测，例如广泛检测、接触者追踪和病例隔离，可能有助于发现和预防早期疫情，但如果发生更大规模的疫情，这些策略将是不够的。因此，有必要在学期开始时限制活动案例的初始数量。我们研究的影响，学期前NAT测试在大学环境中的疾病传播。研究方法：我们实现了简单的SARS-CoV-2感染的动态传播模型，以探讨学期前测试策略对整个学期活跃感染人数和占用隔离床的影响。我们假设传染期为3天，并改变R 0来代表整个学期疾病缓解策略的有效性。我们假设在学期开始时活跃病例的患病率为5%。NAT测试的灵敏度设置为90%。结果如下：如果没有学期前筛查是强制性的，活跃感染的峰值数量发生在10天内，峰值的大小是相当大的，范围从5,000活跃感染时，有效的缓解策略（R 0 = 1.25）实施到超过15,000活跃感染的有效策略（R 0 = 3）。当一个NAT测试是强制在校园到达后一周内，有效（R 0 = 1.25）和不太有效（R 0 = 3）缓解策略延迟高峰的发病时间分别为40天和17天，并导致峰值大小范围从1,000到超过15,000活跃感染。当两个NAT测试是强制性的，有效的（R 0 = 1.25）和不太有效的（R 0 = 3）缓解策略延迟高峰的开始，通过秋季学期结束和20天，分别，并导致峰值大小范围从小于1,000到超过15,000活跃感染。如果隔离病床的最高使用率设定为学生人数的2%，则在达到最高使用率之前，隔离病床只能用于两名确诊病例中的一名（R 0 = 1.25）至40名确诊病例中的一名（R 0 = 3）。结论：即使在整个学期中采取了非常有效的缓解策略，学期前测试不足也会导致疾病的早期和大规模激增，并导致大学迅速达到其隔离床位的容量。因此，我们建议在校园返回后一周内进行NAT测试。虽然这一策略足以推迟爆发的时间，但学期前的测试需要与有效的缓解策略结合实施，以减少爆发的规模。
Background: University campuses present an ideal environment for viral spread and are therefore at extreme risk of serving as a hotbed for a COVID-19 outbreak. While active surveillance throughout the semester such as widespread testing, contact tracing, and case isolation, may assist in detecting and preventing early outbreaks, these strategies will not be sufficient should a larger outbreak occur. It is therefore necessary to limit the initial number of active cases at the start of the semester. We examine the impact of pre-semester NAT testing on disease spread in a university setting. Methods: We implement simple dynamic transmission models of SARS-CoV-2 infection to explore the effects of pre-semester testing strategies on the number of active infections and occupied isolation beds throughout the semester. We assume an infectious period of 3 days and vary R0 to represent the effectiveness of disease mitigation strategies throughout the semester. We assume the prevalence of active cases at the beginning of the semester is 5%. The sensitivity of the NAT test is set at 90%. Results: If no pre-semester screening is mandated, the peak number of active infections occurs in under 10 days and the size of the peak is substantial, ranging from 5,000 active infections when effective mitigation strategies (R0 = 1.25) are implemented to over 15,000 active infections for less effective strategies (R0 = 3). When one NAT test is mandated within one week of campus arrival, effective (R0 = 1.25) and less effective (R0 = 3) mitigation strategies delay the onset of the peak to 40 days and 17 days, respectively, and result in peak size ranging from 1,000 to over 15,000 active infections. When two NAT tests are mandated, effective (R0 = 1.25) and less effective (R0 = 3) mitigation strategies delay the onset of the peak through the end of fall semester and 20 days, respectively, and result in peak size ranging from less than 1,000 to over 15,000 active infections. If maximum occupancy of isolation beds is set to 2% of the student population, then isolation beds would only be available for a range of 1 in 2 confirmed cases (R0 = 1.25) to 1 in 40 confirmed cases (R0 = 3) before maximum occupancy is reached. Conclusion: Even with highly effective mitigation strategies throughout the semester, inadequate pre-semester testing will lead to early and large surges of the disease and result in universities quickly reaching their isolation bed capacity. We therefore recommend NAT testing within one week of campus return. While this strategy is sufficient for delaying the timing of the outbreak, pre-semester testing would need to be implemented in conjunction with effective mitigation strategies to reduce the outbreak size.