期刊
ANNALS OF APPLIED STATISTICS
卷 1, 期 1, 页码 229-248出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/07-AOAS111
关键词
HIV/AIDS; predictive distribution; prevalence; random effects model; sampling importance resampling; susceptible-infected model; UNAIDS estimation and projection package; uncertainty assessment
资金
- Center for Statistics and the Social Sciences (CSSS)
- Center for Studies in Demography and Ecology (CSDE)
- Blumstein-Jordan Professorship
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%.
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