Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings.
Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings.
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DOI：
10.1126/scitranslmed.abf1568
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发表时间：
2021-04-14
影响因子：
17.1
通讯作者：
Mina MJ
中科院分区：
文献类型：
--
作者：
Cleary B;Hay JA;Blumenstiel B;Harden M;Cipicchio M;Bezney J;Simonton B;Hong D;Senghore M;Sesay AK;Gabriel S;Regev A;Mina MJ
使用建模和实验数据确定了简单的小组测试设计，以改善资源有限环境中的 SARS-CoV-2 监测。频繁、准确的基于 RT-PCR 的检测对于预防和管理 SARS-CoV-2 感染至关重要；然而，主动感染监测仍然常常受到时间或资源的限制。克利里等人。证明，考虑到人群水平的病毒流行率和个体病毒载量，可以在理论上和使用人类拭子和痰样本进行体外验证的情况下，以最小的灵敏度损失进行汇总测试，从而提高效率。巴拉克等人。研究表明，对 133,816 份医院采集的患者鼻咽样本进行汇总检测，消除了四分之三的检测反应，且敏感性仅略有下降，证明了该方法在现场的有效性。这两项研究都表明，在测试前考虑合并单个样本可以可靠地提高 SARS-CoV-2 的测试通量。病毒学检测对于遏制严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 至关重要，但许多环境在检测方面面临严重限制。分组测试提供了一种通过测试组合样本池来提高吞吐量的方法；然而，大多数拟议的设计尚未解决有关灵敏度损失和实施可行性的关键问题。在这里，我们结合了流行病传播的数学模型和根据经验得出的 SARS-CoV-2 感染病毒动力学，以确定对流行率变化稳健的汇集设计，并确认针对个体感染时间进程的敏感性损失。我们表明，仅使用几十个汇总测试即可准确估计从 0.02% 到 20% 的广泛范围内的患病率，并且使用的测试数量比个体识别所需的测试数量少 400 倍。然后，我们详尽地评估了不同池化设计在各种资源限制下最大化检测到的感染数量的能力，发现简单的池化设计在给定预算下可以识别出的真阳性数量是单独测试的 20 倍。至关重要的是，我们仅使用 48 次测试，并通过对 960 个样本进行汇总样本鉴定，准确估计 2304 个样本中 1% 的患病率，从而证实我们的理论结果可以使用汇总的人类鼻咽标本转化为实践。我们的结果表明，考虑到采样病毒载量的变化可以提供关于合并如何影响检测感染的敏感性的细致入微的图景。使用简单、实用的小组测试设计可以极大地提高资源有限环境中的监视能力。
Simple group testing designs to improve SARS-CoV-2 surveillance in resource-constrained settings are identified using modeling and experimental data. Frequent and accurate RT-PCR–based testing is essential for preventing and managing SARS-CoV-2 infection; however, active infection surveillance is still often limited by time or resources. Cleary et al. demonstrate that considering population-level viral prevalence and individual viral loads allows for efficiency gains upon pooled testing with minimal loss of sensitivity, both theoretically and as validated in vitro using human swab and sputum samples. Barak et al. show that pooled testing of 133,816 hospital-collected patient nasopharyngeal samples eliminated three quarters of testing reactions with only a minor reduction in sensitivity, demonstrating the efficacy of the approach in the field. Both studies suggest that considered pooling of individual samples before testing could reliably increase SARS-CoV-2 testing throughput. Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.
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影响因子：
3.7
作者：
Arevalo-Rodriguez I;Buitrago-Garcia D;Simancas-Racines D;Zambrano-Achig P;Del Campo R;Ciapponi A;Sued O;Martinez-García L;Rutjes AW;Low N;Bossuyt PM;Perez-Molina JA;Zamora J
通讯作者：
Zamora J
影响因子：
33.9
作者：
Hamner, Lea;Dubbel, Polly;Leibrand, Howard
通讯作者：
Leibrand, Howard
DOI：
10.1016/j.jmii.2020.06.003
发表时间：
2021-02-19
影响因子：
7.4
作者：
Huang, Yen-Ta;Tu, Yu-Kang;Lai, Pei-Chun
通讯作者：
Lai, Pei-Chun
影响因子：
3.7
作者：
Hsiang MS;Hwang J;Kunene S;Drakeley C;Kandula D;Novotny J;Parizo J;Jensen T;Tong M;Kemere J;Dlamini S;Moonen B;Angov E;Dutta S;Ockenhouse C;Dorsey G;Greenhouse B
通讯作者：
Greenhouse B
影响因子：
17.1
作者：
Barak N;Ben-Ami R;Sido T;Perri A;Shtoyer A;Rivkin M;Licht T;Peretz A;Magenheim J;Fogel I;Livneh A;Daitch Y;Oiknine-Djian E;Benedek G;Dor Y;Wolf DG;Yassour M;Hebrew University-Hadassah COVID-19 Diagnosis Team
通讯作者：
Hebrew University-Hadassah COVID-19 Diagnosis Team