论文标题
COVID-19的小组测试中的小组设计：法国案例研究
Group design in group testing for COVID-19 : A French case-study
论文作者
论文摘要
小组测试是一种筛查策略，涉及将人口分为几个分离的受试者组。在最简单的实现中，每个组在第一阶段进行了一次测试，而在第二阶段，仅在正组中（如果有的话）进行单独测试。在本文中，我们解决了小组测试设计的问题，该问题旨在确定有限人群组的组分配给每个组大小的基数约束以及对预期测试总数的约束，同时满足预期的预期伪造负面分类和假阳性分类的线性组合。首先，我们表明Aprahmian等人引入的属性和模型。可以扩展到组测试设计问题，然后将其建模为特定图表上约束的最短路径问题。我们设计并实施了一种临时算法来解决此问题。基于基于SantéPublique法国关于COVID-19筛查测试的数据，计算实验的结果非常有前途。
Group testing is a screening strategy that involves dividing a population into several disjointed groups of subjects. In its simplest implementation, each group is tested with a single test in the first phase, while in the second phase only subjects in positive groups, if any, need to be tested again individually. In this paper, we address the problem of group testing design, which aims to determine a partition into groups of a finite population in such a way that cardinality constraints on the size of each group and a constraint on the expected total number of tests are satisfied while minimizing a linear combination of the expected number of false negative and false positive classifications. First, we show that the properties and model introduced by Aprahmian et al. can be extended to the group test design problem, which is then modeled as a constrained shortest path problem on a specific graph. We design and implement an ad hoc algorithm to solve this problem. On instances based on Santé Publique France data on Covid-19 screening tests, the results of the computational experiments are very promising.
