The Annals of Applied Statistics

Probabilistic projections of HIV prevalence using Bayesian melding

Leontine Alkema, Adrian E. Raftery, and Samuel J. Clark

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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%.

Article information

Ann. Appl. Stat., Volume 1, Number 1 (2007), 229-248.

First available in Project Euclid: 29 June 2007

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HIV/AIDS predictive distribution prevalence random effects model sampling importance resampling susceptible-infected model UNAIDS estimation and projection package uncertainty assessment


Alkema, Leontine; Raftery, Adrian E.; Clark, Samuel J. Probabilistic projections of HIV prevalence using Bayesian melding. Ann. Appl. Stat. 1 (2007), no. 1, 229--248. doi:10.1214/07-AOAS111.

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