Bayesian conditional-independence modeling of the AIDS epidemic in England and Wales

Walter R. Gilks*, Daniela De Angelis, Nicholas E. Day

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)


    We describe the use of conditional-independence modeling, Bayesian inference and Markov chain Monte Carlo, to model and project the HIV-AIDS epidemic in homosexual/bisexual males in England and Wales. Complexity in this analysis arises through selectively missing data, indirectly observed underlying processes, and measurement error. Our emphasis is on presentation and discussion of the concepts, not on the technicalities of this analysis, which can be found elsewhere [D. De Angelis, W.R. Gilks, N.E. Day, Bayesian projection of the the acquired immune deficiency syndrome epidemic (with discussion), Applied Statistics, in press].

    Original languageEnglish
    Pages (from-to)145-151
    Number of pages7
    JournalPhysica D: Nonlinear Phenomena
    Issue number1-4
    Publication statusPublished - 10 Sept 1999


    • AIDS
    • Bayesian inference
    • Conditional independence model
    • Markov chain Monte Carlo
    • Prediction


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