Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Division of General Internal Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
J Adolesc Health. 2021 Jan;68(1):28-34. doi: 10.1016/j.jadohealth.2020.09.038. Epub 2020 Nov 3.
The optimal approach to identify SARS-CoV-2 infection among college students returning to campus is unknown. Recommendations vary from no testing to two tests per student. This research determined the strategy that optimizes the number of true positives and negatives detected and reverse transcription polymerase chain reaction (RT-PCR) tests needed.
A decision tree analysis evaluated five strategies: (1) classifying students with symptoms as having COVID-19, (2) RT-PCR testing for symptomatic students, (3) RT-PCR testing for all students, (4) RT-PCR testing for all students and retesting symptomatic students with a negative first test, and (5) RT-PCR testing for all students and retesting all students with a negative first test. The number of true positives, true negatives, RT-PCR tests, and RT-PCR tests per true positive (TTP) was calculated.
Strategy 5 detected the most true positives but also required the most tests. The percentage of correctly identified infections was 40.6%, 29.0%, 53.7%, 72.5%, and 86.9% for Strategies 1-5, respectively. All RT-PCR strategies detected more true negatives than the symptom-only strategy. Analysis of TTP demonstrated that the repeat RT-PCR strategies weakly dominated the single RT-PCR strategy and that the thresholds for more intensive RT-PCR testing decreased as the prevalence of infection increased.
Based on TTP, the single RT-PCR strategy is never preferred. If the cost of RT-PCR testing is of concern, a staged approach involving initial testing of all returning students followed by a repeat testing decision based on the measured prevalence of infection might be considered.
确定大学生返校时识别 SARS-CoV-2 感染的最佳方法尚不清楚。建议从对所有学生均不进行检测到对每个学生进行两次检测不等。本研究旨在确定能够优化检测到的真阳性和真阴性数量以及逆转录聚合酶链反应（RT-PCR）检测数量的策略。
决策树分析评估了五种策略：（1）将有症状的学生归类为 COVID-19 患者；（2）对有症状的学生进行 RT-PCR 检测；（3）对所有学生进行 RT-PCR 检测；（4）对所有学生进行 RT-PCR 检测，如果第一次检测结果为阴性，则对有症状的学生进行重复检测；（5）对所有学生进行 RT-PCR 检测，如果第一次检测结果为阴性，则对所有学生进行重复检测。计算真阳性、真阴性、RT-PCR 检测数量和每个真阳性的 RT-PCR 检测数量（TTP）。
策略 5 检测到的真阳性数量最多，但也需要进行最多的检测。策略 1-5 分别正确识别出 40.6%、29.0%、53.7%、72.5%和 86.9%的感染病例。所有 RT-PCR 策略均比仅通过症状进行检测的策略检测到更多的真阴性。TTP 分析表明，重复 RT-PCR 策略在弱优势于单次 RT-PCR 策略，且随着感染率的增加，更密集 RT-PCR 检测的阈值降低。
基于 TTP，单次 RT-PCR 策略绝不是首选。如果 RT-PCR 检测的成本是一个问题，则可以考虑采用分阶段的方法，最初对所有返校学生进行检测，然后根据已测量的感染流行率决定是否进行重复检测。
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