  As the global HIV pandemic enters its fourth decade, increasing numbers of
surveillance sites have been established which allows countries to look into
the epidemics at a finer scale, e.g. at sub-national level. However, the
epidemic models have been applied independently to the sub-national areas
within countries. An important technical barrier is that the availability and
quality of the data vary widely from area to area, and many areas lack data for
deriving stable and reliable results. To improve the accuracy of the results in
areas with little data, we propose a hierarchical model that utilizes
information efficiently by assuming similar characteristics of the epidemics
across areas within one country. The joint distribution of the parameters in
the hierarchical model can be approximated directly from the results of
independent fits without needing to the refit the data. As a result, the
hierarchical model has better predictive ability than the independent model as
shown in examples of multiple countries in Sub-Saharan Africa.
