论文标题
Pooltestr：用于使用合并样品估算患病率和回归建模的R包装
PoolTestR: An R package for estimating prevalence and regression modelling with pooled samples
论文作者
论文摘要
合并的测试（也称为小组测试），在汇总样品上进行诊断测试，在动物和人类中疾病的监测中具有广泛的应用。越来越常见的用例是分子异种措施（MX），其中通过捕获和测试大量载体（例如蚊子）来对载体传播疾病进行监视。开发了R包装套件，以满足日益大而复杂的分子异种调查调查的需求，但可以应用于分析涉及合并测试的任何数据。 Pooltestres包括简单而灵活的工具，以估计流行率并适合固定和混合效应的广义线性模型，以用于频繁和贝叶斯框架中的汇总数据。综合效应模型允许用户考虑在包括MX在内的调查中经常采用的层次采样设计。我们通过将其应用于大型合成数据集，以模拟使用层次采样设计的MX调查来证明pooltester的实用性。
Pooled testing (also known as group testing), where diagnostic tests are performed on pooled samples, has broad applications in the surveillance of diseases in animals and humans. An increasingly common use case is molecular xenomonitoring (MX), where surveillance of vector-borne diseases is conducted by capturing and testing large numbers of vectors (e.g. mosquitoes). The R package PoolTestR was developed to meet the needs of increasingly large and complex molecular xenomonitoring surveys but can be applied to analyse any data involving pooled testing. PoolTestR includes simple and flexible tools to estimate prevalence and fit fixed- and mixed-effect generalised linear models for pooled data in frequentist and Bayesian frameworks. Mixed-effect models allow users to account for the hierarchical sampling designs that are often employed in surveys, including MX. We demonstrate the utility of PoolTestR by applying it to a large synthetic dataset that emulates a MX survey with a hierarchical sampling design.
