Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, California, USA.
California Center for Population Research, Los Angeles, California, USA.
J Med Virol. 2021 Sep;93(9):5396-5404. doi: 10.1002/jmv.27054. Epub 2021 May 27.
Pooled testing is a potentially efficient alternative strategy for COVID-19 testing in congregate settings. We evaluated the utility and cost-savings of pooled testing based on imperfect test performance and potential dilution effect due to pooling and created a practical calculator for online use.
We developed a 2-stage pooled testing model accounting for dilution. The model was applied to hypothetical scenarios of 100 specimens collected during a one-week time-horizon cycle for varying levels of COVID-19 prevalence and test sensitivity and specificity, and to 338 skilled nursing facilities (SNFs) in Los Angeles County (Los Angeles) (data collected and analyzed in 2020).
Optimal pool sizes ranged from 1 to 12 in instances where there is a least one case in the batch of specimens. 40% of Los Angeles SNFs had more than one case triggering a response-testing strategy. The median number (minimum; maximum) of tests performed per facility were 56 (14; 356) for a pool size of 4, 64 (13; 429) for a pool size of 10, and 52 (11; 352) for an optimal pool size strategy among response-testing facilities. The median costs of tests in response-testing facilities were $8250 ($1100; $46,100), $6000 ($1340; $37,700), $6820 ($1260; $43,540), and $5960 ($1100; $37,380) when adopting individual testing, a pooled testing strategy using pool sizes of 4, 10, and optimal pool size, respectively.
Pooled testing is an efficient strategy for congregate settings with a low prevalence of COVID-19. Dilution as a result of pooling can lead to erroneous false-negative results.
在聚集性环境中， pooled testing 是一种潜在高效的 COVID-19 检测替代策略。我们评估了 pooled testing 的效用和成本节约，考虑到检测的不完美性能以及 pooling 导致的潜在稀释效应，并创建了一个实用的在线计算器。
我们开发了一个两阶段 pooled testing 模型，考虑了稀释效应。该模型应用于不同 COVID-19 流行率和检测灵敏度和特异性水平的 100 个标本在一周时间内采集的假设场景，以及洛杉矶县（洛杉矶）的 338 个熟练护理设施（SNF）（2020 年收集和分析的数据）。
在一批标本中至少有一个病例的情况下，最优池大小范围从 1 到 12。40%的洛杉矶 SNF 有超过一个病例触发反应性检测策略。对于池大小为 4 的 pooled testing，每个设施进行的测试中位数（最小值；最大值）为 56（14；356），对于池大小为 10 的 pooled testing，为 64（13；429），对于反应性检测设施中的最优池大小策略，为 52（11；352）。在反应性检测设施中，采用个体检测、pool 大小为 4、10 和最优池大小的 pooled testing 策略，测试的中位数成本分别为 8250 美元（1100 美元；46100 美元）、6000 美元（1340 美元；37700 美元）、6820 美元（1260 美元；43540 美元）和 5960 美元（1100 美元；37380 美元）。
Pooled testing 是 COVID-19 低流行率聚集性环境的有效策略。Pooling 导致的稀释可能导致错误的假阴性结果。
