Wu Jiacheng, Crawford Forrest W, Raag Mait, Heimer Robert, Uusküla Anneli
Department of Biostatistics, University of Washington, Seattle, WA, United States of America.
Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.
PLoS One. 2017 Nov 2;12(11):e0185711. doi: 10.1371/journal.pone.0185711. eCollection 2017.
Estimating the size of key risk populations is essential for determining the resources needed to implement effective public health intervention programs. Several standard methods for population size estimation exist, but the statistical and practical assumptions required for their use may not be met when applied to HIV risk groups. We apply three approaches to estimate the number of people who inject drugs (PWID) in the Kohtla-Järve region of Estonia using data from a respondent-driven sampling (RDS) study: the standard "multiplier" estimate gives 654 people (95% CI 509-804), the "successive sampling" method gives estimates between 600 and 2500 people, and a network-based estimate that uses the RDS recruitment chain gives between 700 and 2800 people. We critically assess the strengths and weaknesses of these statistical approaches for estimating the size of hidden or hard-to-reach HIV risk groups.
估计关键风险人群的规模对于确定实施有效的公共卫生干预项目所需的资源至关重要。存在几种估计人群规模的标准方法，但将其应用于艾滋病毒风险群体时，可能无法满足其使用所需的统计和实际假设。我们运用三种方法，利用应答驱动抽样（RDS）研究的数据，来估计爱沙尼亚科赫特拉-耶尔韦地区注射毒品者（PWID）的人数：标准的“乘数”估计得出654人（95%置信区间509 - 804），“连续抽样”方法得出的估计人数在600至2500人之间，而基于网络的估计（使用RDS招募链）得出的人数在700至2800人之间。我们严格评估了这些统计方法在估计隐藏的或难以接触到的艾滋病毒风险群体规模方面的优缺点。
