  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%.
