PROBABILISTIC PROJECTIONS OF HIV PREVALENCE USING BAYESIAN MELDING
PROBABILISTIC PROJECTIONS OF HIV PREVALENCE USING BAYESIAN MELDING
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DOI：
10.1214/07-aoas111
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发表时间：
2007-06-01
影响因子：
1.8
通讯作者：
Clark, Samuel J.
中科院分区：
文献类型：
--
作者：
Alkema, Leontine;Raftery, Adrian E.;Clark, Samuel J.
联合国艾滋病毒/艾滋病联合规划署(艾滋病规划署)编制了估计和预测程序包，以便根据产前诊所观察到的流行趋势，对艾滋病毒流行率进行国家估计和短期预测。评估其估计和预测的不确定性对于明智的政策决策非常重要，我们建议使用贝叶斯融合来实现这一目的。流行数据和关于EPP模型的输入参数的其他信息被用来导出概率HIV流行预测，即一组未来流行轨迹上的概率分布。我们将产前门诊患病率与人口患病率联系起来，并使用随机效应模型来解释诊所之间的变异性。为了检验该模型，还推导了临床流行的预测区间。我们讨论了EPP模型给出的预测和乌干达贝叶斯融合程序的结果，乌干达的流行率在1990年达到28%左右的峰值；2010年95%的预测区间从2%到7%不等。
The Joint United Nations Programme on HIV/AIDS (UNAIDS) has developed the Estimation and Projection Package (EPP) for making national estimates and short-term projections of HIV prevalence based on observed prevalence trends at antenatal clinics. Assessing the uncertainty about its estimates and projections is important for informed policy decision making, and we propose the use of Bayesian melding for this purpose. Prevalence data and other information about the EPP model's input parameters are used to derive a probabilistic HIV prevalence projection, namely a probability distribution over a set of future prevalence trajectories. We relate antenatal clinic Prevalence to population prevalence and account for variability between clinics using a random effects model. Predictive intervals for clinic prevalence are derived for checking the model. We discuss predictions given by the EPP model and the results of the Bayesian melding procedure for Uganda, where prevalence peaked at around 28% in 1990; the 95% prediction interval for 2010 ranges from 2% to 7%.