论文标题
实施快速共vid-19检测的逐步合并测试
Implementing Stepped Pooled Testing for Rapid COVID-19 Detection
论文作者
论文摘要
Covid-19是一种病毒呼吸道大流行，已在全球范围内迅速扩散。需要大规模的人群测试才能遏制该疾病，但是在资源，成本和时间方面，这种测试却是过分的。最近，基于RT-PCR的合并测试已成为提高测试效率的一种有希望的方法。我们引入了跨越的汇总测试策略，这是一种概率驱动的方法，可大大减少识别大量人群中受感染者所需的测试数量。我们的综合方法结合了假阴性和正率的效果，不仅要准确确定合并效率，而且确定其准确性。在各种合理的情况下，我们表明，与测试人群的每个人相比，这种方法可大大降低测试成本，并降低测试的有效假阳性率。我们还概述了一个优化策略，以获取池大小，鉴于诊断协议参数和局部感染条件，该池大小最大化了合并的效率。
COVID-19, a viral respiratory pandemic, has rapidly spread throughout the globe. Large scale and rapid testing of the population is required to contain the disease, but such testing is prohibitive in terms of resources, cost and time. Recently RT-PCR based pooled testing has emerged as a promising way to boost testing efficiency. We introduce a stepped pooled testing strategy, a probability driven approach which significantly reduces the number of tests required to identify infected individuals in a large population. Our comprehensive methodology incorporates the effect of false negative and positive rates to accurately determine not only the efficiency of pooling but also it's accuracy. Under various plausible scenarios, we show that this approach significantly reduces the cost of testing and also reduces the effective false positive rate of tests when compared to a strategy of testing every individual of a population. We also outline an optimization strategy to obtain the pool size that maximizes the efficiency of pooling given the diagnostic protocol parameters and local infection conditions.
