Abstract

The group testing procedure divides sampled units into several groups, and then obtains an overall test result for each group. It is used to identify specific individuals who have a given attribute, or to estimate the overall prevalence of the attribute in the population. We here investigate how group retesting can improve precision of estimation and its cost-efficiency, which are important considerations for investigators. Retesting uses two or more group stages, with repeat testing of the original samples at each stage. Previous authors have proposed a procedure with two stages having equal group sizes, and where the number of groups tested at the second stage is based on the number of positive groups in the first stage. In this paper, our main focus is on estimating the prevalence $p$ of affected individuals in a population, and identifying cost-efficient experimental designs, when using two-stage testing with unequal group sizes at each stage. We use analytical solutions for the precision of estimation, together with simulations to evaluate various experimental designs. We consider the value of retesting at the second stage, and determine when using only one stage of testing might be sufficiently precise.

摘要

组测试程序将抽样单元分成若干组，然后获得每组的总体测试结果。它用于识别具有给定属性的特定个体，或估计该属性在人群中的总体流行程度。我们在这里研究小组重新测试如何提高估计的精度及其成本效益，这是调查人员的重要考虑因素。重新测试使用两个或更多组阶段，在每个阶段重复测试原始样本。以前的作者提出了一个具有相等组大小的两个阶段的程序，其中第二阶段测试的组数基于第一阶段的阳性组数。在本文中，我们的主要重点是估计患病率$p$群体中受影响的个体，并确定具有成本效益的实验设计，当在每个阶段使用不等组大小的两阶段测试时。我们使用估计精度的分析解决方案，以及模拟来评估各种实验设计。我们在第二阶段考虑重新测试的价值，并确定何时仅使用一个测试阶段可能足够精确。