Niu Xiaoyue, Zhang Amy, Brown Tim, Puckett Robert, Mahy Mary, Bao Le
aDepartment of Statistics, Pennsylvania State University, University Park, Pennsylvania bEast-West Center, Honolulu, Hawaii, USA cStrategic Information and Evaluation Department, UNAIDS, Geneva, Switzerland.
AIDS. 2017 Apr;31 Suppl 1(Suppl 1):S51-S59. doi: 10.1097/QAD.0000000000001426.
The article aims to give Spectrum/estimation and projection package (EPP) users and the scientific community a basic understanding of the underlying statistical model used to incorporate hierarchical structure in HIV subnational estimation, and to show how it has been implemented in the Spectrum/EPP interface for improving subepidemic estimation. The article also provides recommended default settings for this new model.
We apply a generalized linear mixed-effects model on antenatal clinics prevalence data to get area-specific prevalence and uncertainty estimates, and transform those estimates to auxiliary data. We then fit the EPP model to both the observed data and auxiliary data.
We apply the proposed methods to four countries with different levels of data availability. We compare the out-of-sample prediction accuracy of the proposed method with varying auxiliary sample sizes and EPP without auxiliary data.
We find that borrowing information from data-rich areas to data-sparse areas using our proposed method improves EPP fit in data-sparse areas. We recommend using the sample size estimated from generalized linear mixed-effects model as the default auxiliary sample size.
本文旨在让Spectrum/估计与预测软件包（EPP）的用户以及科学界对用于在艾滋病毒次国家级估计中纳入分层结构的基础统计模型有基本的了解，并展示该模型在Spectrum/EPP界面中是如何实现以改进亚流行估计的。本文还提供了针对这个新模型的推荐默认设置。
我们对产前诊所患病率数据应用广义线性混合效应模型，以获得特定地区的患病率和不确定性估计，并将这些估计转换为辅助数据。然后，我们将EPP模型应用于观测数据和辅助数据。
我们将所提出的方法应用于四个数据可得性水平不同的国家。我们比较了所提出方法在不同辅助样本量下以及无辅助数据的EPP的样本外预测准确性。
我们发现，使用我们提出的方法从数据丰富地区向数据稀疏地区借用信息，可改善数据稀疏地区的EPP拟合。我们建议将从广义线性混合效应模型估计的样本量作为默认辅助样本量。
