  Multi-parameter evidence synthesis (MPES) is receiving growing attention from
the epidemiological community as a coherent and flexible analytical framework
to accommodate a disparate body of evidence available to inform disease
incidence and prevalence estimation. MPES is the statistical methodology
adopted by the Health Protection Agency in the UK for its annual national
assessment of the HIV epidemic, and is acknowledged by the World Health
Organization and UNAIDS as a valuable technique for the estimation of adult HIV
prevalence from surveillance data. This paper describes the results of
utilizing a Bayesian MPES approach to model HIV prevalence in the Netherlands
at the end of 2007, using an array of field data from different study designs
on various population risk subgroups and with a varying degree of regional
coverage. Auxiliary data and expert opinion were additionally incorporated to
resolve issues arising from biased, insufficient or inconsistent evidence. This
case study offers a demonstration of the ability of MPES to naturally integrate
and critically reconcile disparate and heterogeneous sources of evidence, while
producing reliable estimates of HIV prevalence used to support public health
decision-making.
