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Effectiveness and policies analysis of pool testing method for COVID-19
Kybernetes ( IF 2.5 ) Pub Date : 2021-09-07 , DOI: 10.1108/k-01-2021-0052
Yang Liu 1 , Yi Chen 2 , Kefan Xie 1 , Jia Liu 2
Affiliation  

Purpose

This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully.

Design/methodology/approach

The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected.

Findings

If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N).

Originality/value

This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round.



中文翻译:

COVID-19池检测方法的有效性和政策分析

目的

本研究旨在弄清楚 SARS-CoV-2 对 COVID-19 的池测试方法是否有效以及最佳样本量是否在一组中。此外,由于感染率一开始是未知的,本研究旨在提出一种多重抽样方法,使池测试方法能够成功利用。

设计/方法/途径

作者基于概率建模验证了SARS-CoV-2对COVID-19的池检测方法在核酸检测试剂盒短缺的情况下是有效的。在这种方法中,测试是在多个案例样本上一起进行的。如果该群的检测结果为阴性,则表明该群中没有一例感染新冠病毒。反之,如果该束的检测结果为阳性,则对样本进行逐个检测,以确认哪些病例被感染。

发现

如果感染率极低,在使用相同数量的检测试剂盒的情况下,采用合并检测方式预计可检测的病例数远远超过逐一检测方式。只有当感染率小于 0.3078 时,池测试方法才有效。感染率越高,一组中的最佳样本量越小。如果采用合并检测法检测N个样本,而一批样本量为G,则所需检测试剂盒数量在区间( N / G , N )内。

原创性/价值

本研究证明,混合检测法不仅适用于检测试剂盒紧缺的情况,也适用于大人群整体或抽样检测的情况。更重要的是,它计算了一组中不同感染率对应的最佳样本量。此外,还提出了多重采样方法。在这种方法中,整个测试过程分为几轮,其中一组中的样本量不同。实际感染率是通过逐轮抽检逐步准确估算出来的。

更新日期:2021-09-07
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