标题： 使用贝叶斯融合的HIV流行率概率预测 显示英文标题

标题： Probabilistic projections of HIV prevalence using Bayesian melding

摘要： 联合国艾滋病规划署（UNAIDS）开发了估计与预测包（EPP），用于基于产前诊所观察到的流行趋势来估算和短期预测国家层面的HIV流行率。评估其估算和预测的不确定性对于知情的政策决策至关重要，我们建议使用贝叶斯融会方法达到此目的。利用流行率数据和其他关于EPP模型输入参数的信息，可以得出概率性的HIV流行率预测，即一组未来流行率轨迹上的概率分布。我们将产前诊所的流行率与人群流行率联系起来，并通过随机效应模型来考虑诊所间的变异性。推导出了诊所流行率的预测区间以检验模型。我们讨论了乌干达EPP模型的预测结果以及贝叶斯融会程序的结果，在那里1990年流行率达到峰值约28%；2010年的95%预测区间从2%到7%。 显示英文摘要

摘要： 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%.