Department of HIV/AIDS, National Institute for Research in Tuberculosis, Chennai, India.
Department of HIV/AIDS, National Institute for Research in Tuberculosis, Chennai, India.
Diagn Microbiol Infect Dis. 2021 Oct;101(2):115432. doi: 10.1016/j.diagmicrobio.2021.115432. Epub 2021 May 17.
SARS-CoV-2 has surged across the globe causing the ongoing COVID-19 pandemic. Systematic testing to facilitate index case isolation and contact tracing is needed for efficient containment of viral spread. The major bottleneck in leveraging testing capacity has been the lack of diagnostic resources. Pooled testing is a potential approach that could reduce cost and usage of test kits. This method involves pooling individual samples and testing them 'en bloc'. Only if the pool tests positive, retesting of individual samples is performed. Upon reviewing recent articles on this strategy employed in various SARS-CoV-2 testing scenarios, we found substantial diversity emphasizing the requirement of a common protocol. In this article, we review various theoretically simulated and clinically validated pooled testing models and propose practical guidelines on applying this strategy for large scale screening. If implemented properly, the proposed approach could contribute to proper utilization of testing resources and flattening of infection curve.
SARS-CoV-2 在全球范围内迅速传播,导致了持续的 COVID-19 大流行。为了有效控制病毒传播,需要进行系统的检测,以方便确定初始病例并进行接触者追踪。利用检测能力的主要瓶颈一直是缺乏诊断资源。合并检测是一种潜在的方法,可以降低检测试剂盒的成本和使用量。这种方法涉及将个体样本合并并进行整体检测。只有当混合样本检测呈阳性时,才会对个体样本进行重新检测。在回顾了最近关于这种策略在各种 SARS-CoV-2 检测场景中的应用的文章后,我们发现存在很大的差异,这强调了需要制定一个共同的协议。在本文中,我们回顾了各种理论模拟和临床验证的合并检测模型,并提出了在大规模筛查中应用该策略的实用指南。如果实施得当,所提出的方法可以有助于合理利用检测资源和减缓感染曲线。