HIV 预防研究中的 HIV 发病率横断面估计。
Cross-sectional HIV incidence estimation in HIV prevention research.
机构信息
Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
出版信息
J Acquir Immune Defic Syndr. 2013 Jul;63 Suppl 2(0 2):S233-9. doi: 10.1097/QAI.0b013e3182986fdf.
Abstract
Accurate methods for estimating HIV incidence from cross-sectional samples would have great utility in prevention research. This report describes recent improvements in cross-sectional methods that significantly improve their accuracy. These improvements are based on the use of multiple biomarkers to identify recent HIV infections. These multiassay algorithms (MAAs) use assays in a hierarchical approach for testing that minimizes the effort and cost of incidence estimation. These MAAs do not require mathematical adjustments for accurate estimation of the incidence rates in study populations in the year before sample collection. MAAs provide a practical, accurate, and cost-effective approach for cross-sectional HIV incidence estimation that can be used for HIV prevention research and global epidemic monitoring.
摘要
准确估计 HIV 发病率的方法对于预防研究具有很大的实用价值。本报告描述了横断面研究方法的最新改进，这些改进显著提高了其准确性。这些改进基于使用多种生物标志物来识别最近的 HIV 感染。这些多指标检测算法（Multiassay Algorithm，MAA）采用分层检测方法，将检测所需的精力和成本降到最低，从而进行检测。这些 MAA 不需要进行数学调整，就可以准确估计在样本采集前一年的研究人群中的发病率。MAA 为横断面 HIV 发病率估计提供了一种实用、准确和具有成本效益的方法，可用于 HIV 预防研究和全球疫情监测。
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