Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA.
ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, UT, USA.
J R Soc Interface. 2021 Jun;18(179):20210155. doi: 10.1098/rsif.2021.0155. Epub 2021 Jun 16.
Rapid and widespread implementation of infectious disease surveillance is a critical component in the response to novel health threats. Molecular assays are the preferred method to detect a broad range of viral pathogens with high sensitivity and specificity. The implementation of molecular assay testing in a rapidly evolving public health emergency, such as the ongoing COVID-19 pandemic, can be hindered by resource availability or technical constraints. We present a screening strategy that is easily scaled up to support a sustained large volume of testing over long periods of time. This non-adaptive pooled-sample screening protocol employs Bayesian inference to yield a reportable outcome for each individual sample in a single testing step (no confirmation of positive results required). The proposed method is validated using clinical specimens tested using a real-time reverse transcription polymerase chain reaction test for SARS-CoV-2. This screening protocol has substantial advantages for its implementation, including higher sample throughput, faster time to results, no need to retrieve previously screened samples from storage to undergo retesting, and excellent performance of the algorithm's sensitivity and specificity compared with the individual test's metrics.
快速广泛地实施传染病监测是应对新出现的健康威胁的关键组成部分。分子检测是检测广泛的病毒病原体的首选方法，具有高灵敏度和特异性。在不断发展的突发公共卫生事件中实施分子检测，如当前的 COVID-19 大流行，可能会受到资源可用性或技术限制的阻碍。我们提出了一种筛选策略，该策略易于扩展，可在长时间内支持大量持续的检测。这种非适应性混合样本筛选方案利用贝叶斯推断，在单个检测步骤中为每个单独样本提供可报告的结果（无需确认阳性结果）。该方法使用针对 SARS-CoV-2 的实时逆转录聚合酶链反应检测进行临床标本验证。与单个检测的指标相比，该筛选方案在实施方面具有显著优势，包括更高的样本通量、更快的检测结果时间、无需从存储中检索之前筛选的样本进行重新检测，以及算法灵敏度和特异性的优异性能。
