Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China.
Epidemiol Infect. 2021 Jan 5;149:e17. doi: 10.1017/S0950268820003155.
A pooled sample analysis strategy for novel coronavirus (severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)) is proposed for a large population in this paper. The population to be tested is divided into divisions based on earlier observed detection rate of SARS-CoV-2 first. Samples collected are then grouped in appropriate pooled size. The number of tests per person in that population is expressed as a function of two variables: the observed detection rate and the pooled size or number of samples grouped. The minimum number of tests per person can be further shown to be a function of only one of these two variables, because these two parameters are found to be related at this minimum. A management scheme on grouping the samples is proposed in order to reduce the number of tests, to save time, which is of utmost importance in fighting an epidemic. The proposed testing scheme will be useful for supporting the government in making decisions to handle regular routine detection tests for identifying asymptomatic patients and implementing health code system in large population of millions of citizens. Another important point is to use smaller number of test kits, allowing more resources to speed up the mass screening tests, particularly in places not so rich.
本文提出了一种针对大人群的新型冠状病毒（严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2））的汇总样本分析策略。首先根据早期观察到的 SARS-CoV-2 检出率对要检测的人群进行分组。然后将采集的样本按适当的合并大小分组。该人群每人的检测次数表示为两个变量的函数：观察到的检出率和合并大小或分组的样本数量。进一步证明，每人的最小检测次数可以仅作为这两个变量之一的函数，因为在这种最小值下，发现这两个参数是相关的。为了减少测试次数，节省时间，提出了一种样本分组管理方案，这在应对疫情方面至关重要。所提出的测试方案将有助于支持政府做出决策，以进行常规例行检测，以识别无症状患者，并在数百万公民的庞大人群中实施健康码系统。另一个重要的点是使用更少数量的测试试剂盒，从而可以利用更多的资源来加快大规模筛查测试，特别是在不那么富裕的地方。
