Modeling of the HIV infection epidemic in the Netherlands: A multi-parameter evidence synthesis approach

Stefano Conti*, Anne M. Presanis, Maaike G. van Veen, Maria Xiridou, Martin C. Donoghoe, Annemarie Rinder Stengaard, Daniela De Angelis

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)


    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.

    Original languageEnglish
    Pages (from-to)2359-2384
    Number of pages26
    JournalAnnals of Applied Statistics
    Issue number4
    Publication statusPublished - Dec 2011


    • Bayesian inference
    • Bias adjustment
    • Evidence synthesis
    • HIV infection
    • Hierarchical models


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