论文标题
通过不完美测定的复杂调查的置信区间进行患病率估计
Confidence Intervals for Prevalence Estimates from Complex Surveys with Imperfect Assays
论文作者
论文摘要
我们提出了几种相关的方法来创建置信区间，以评估各种调查抽样设置中的疾病患病率。其中包括带有不完美测试的简单随机样品，具有完美测试的加权采样，并进行了不完美测试的加权采样，前两个设置被视为第三个特殊情况。我们的方法使用调查结果和测量敏感性和特异性的测量来构建融合的置信区间。我们证明我们的方法似乎可以保证在模拟设置中的覆盖范围，而竞争方法显示出比标称覆盖范围要低得多的方法。我们将我们的方法应用于2020年5月至7月之间未诊断的成年人对SARS-COV-2的血清估计调查。
We present several related methods for creating confidence intervals to assess disease prevalence in variety of survey sampling settings. These include simple random samples with imperfect tests, weighted sampling with perfect tests, and weighted sampling with imperfect tests, with the first two settings considered special cases of the third. Our methods use survey results and measurements of test sensitivity and specificity to construct melded confidence intervals. We demonstrate that our methods appear to guarantee coverage in simulated settings, while competing methods are shown to achieve much lower than nominal coverage. We apply our method to a seroprevalence survey of SARS-CoV-2 in undiagnosed adults in the United States between May and July 2020.
