Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Harvard Medical School, Boston, Massachusetts.
JAMA Netw Open. 2020 Jul 1;3(7):e2016818. doi: 10.1001/jamanetworkopen.2020.16818.
The coronavirus disease 2019 (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 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) screening performance standards that would permit the safe return of students to US residential college campuses for the fall 2020 semester.
DESIGN, SETTING, AND PARTICIPANTS: This analytic modeling study included a hypothetical cohort of 4990 students without SARS-CoV-2 infection and 10 with undetected, asymptomatic SARS-CoV-2 infection at the start of the semester. The decision and cost-effectiveness analyses were linked to a compartmental epidemic model to evaluate symptom-based screening and tests of varying frequency (ie, every 1, 2, 3, and 7 days), sensitivity (ie, 70%-99%), specificity (ie, 98%-99.7%), and cost (ie, $10/test-$50/test). Reproductive numbers (Rt) were 1.5, 2.5, and 3.5, defining 3 epidemic scenarios, with additional infections imported via exogenous shocks. The model assumed a symptomatic case fatality risk of 0.05% and a 30% probability that infection would eventually lead to observable COVID-19-defining symptoms in the cohort. Model projections were for an 80-day, abbreviated fall 2020 semester. This study adhered to US government guidance for parameterization data.
Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact.
At the start of the semester, the hypothetical cohort of 5000 students included 4990 (99.8%) with no SARS-CoV-2 infection and 10 (0.2%) with SARS-CoV-2 infection. Assuming an Rt of 2.5 and daily screening with 70% sensitivity, a test with 98% specificity yielded 162 cumulative student infections and a mean isolation dormitory daily census of 116, with 21 students (18%) with true-positive results. Screening every 2 days resulted in 243 cumulative infections and a mean daily isolation census of 76, with 28 students (37%) with true-positive results. Screening every 7 days resulted in 1840 cumulative infections and a mean daily isolation census of 121 students, with 108 students (90%) with true-positive results. Across all scenarios, test frequency was more strongly associated with cumulative infection than test sensitivity. This model did not identify symptom-based screening alone as sufficient to contain an outbreak under any of the scenarios we considered. Cost-effectiveness analysis selected screening with a test with 70% sensitivity every 2, 1, or 7 days as the preferred strategy for an Rt of 2.5, 3.5, or 1.5, respectively, implying screening costs of $470, $910, or $120, respectively, per student per semester.
In this analytic modeling study, screening every 2 days using a rapid, inexpensive, and even poorly sensitive (>70%) test, coupled with strict behavioral interventions to keep Rt less than 2.5, is estimated to maintain a controllable number of COVID-19 infections and permit the safe return of students to campus.
2019 年冠状病毒病(COVID-19)大流行对许多美国住宿学院构成生存威胁;要么在 9 月向学生开放大门,要么冒着严重的财务后果。
定义严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)筛查性能标准,以确保学生能够安全返回美国住宿学院校园,迎接 2020 年秋季学期的到来。
设计、地点和参与者:本分析模型研究包括一个假设的队列,共有 4990 名没有 SARS-CoV-2 感染的学生和 10 名感染 SARS-CoV-2 但无症状的学生。决策和成本效益分析与一个隔室流行模型相关联,以评估基于症状的筛查和不同频率(即每 1、2、3 和 7 天)、敏感性(即 70%-99%)、特异性(即 98%-99.7%)和成本(即 10 美元/测试-50 美元/测试)的测试。繁殖数(Rt)分别为 1.5、2.5 和 3.5,定义了 3 种流行情况,并通过外源性冲击额外感染了感染。该模型假设无症状病例的病死率为 0.05%,且队列中最终有 30%的感染会导致可观察到的 COVID-19 定义症状。模型预测为 80 天的简短 2020 年秋季学期。本研究遵守美国政府参数化数据的指导方针。
累积测试、感染和成本;每日隔离宿舍普查;增量成本效益;和预算影响。
在学期开始时,假设的 5000 名学生队列中包括 4990 名(99.8%)没有 SARS-CoV-2 感染的学生和 10 名(0.2%)感染 SARS-CoV-2 的学生。假设 Rt 为 2.5,每日筛查灵敏度为 70%,特异性为 98%的检测会导致 162 例学生累积感染,平均每日隔离宿舍普查为 116 例,有 21 名学生(18%)检测结果为真阳性。每天筛查两次会导致 243 例累积感染,平均每日隔离宿舍普查为 76 例,有 28 名学生(37%)检测结果为真阳性。每周筛查 7 次会导致 1840 例累积感染,平均每日隔离宿舍普查为 121 名学生,有 108 名学生(90%)检测结果为真阳性。在所有情况下,与检测敏感性相比,检测频率与累积感染的关系更为密切。该模型没有发现基于症状的筛查单独在我们考虑的任何情况下都不足以控制疫情爆发。成本效益分析选择每周筛查 2 天,使用灵敏度为 70%的检测,或每周筛查 1 天或 7 天,分别是 Rt 为 2.5、3.5 或 1.5 的首选策略,分别意味着每学期每个学生筛查成本为 470 美元、910 美元或 120 美元。
在这项分析模型研究中,使用快速、廉价、甚至敏感性较差(>70%)的检测,每 2 天进行一次筛查,并结合严格的行为干预措施,将 Rt 保持在 2.5 以下,预计可以控制 COVID-19 感染的数量,并确保学生安全返回校园。