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

Walter R. Gilks; Daniela De Angelis; Nicholas E. Day

doi:10.1016/S0167-2789(99)00105-0

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 journal › Article › peer-review

2 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	145-151
Number of pages	7
Journal	Physica D: Nonlinear Phenomena
Volume	133
Issue number	1-4
DOIs	https://doi.org/10.1016/S0167-2789(99)00105-0
Publication status	Published - 10 Sept 1999

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

AIDS
Bayesian inference
Conditional independence model
Markov chain Monte Carlo
Prediction

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10.1016/S0167-2789(99)00105-0

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title = "Bayesian conditional-independence modeling of the AIDS epidemic in England and Wales",

abstract = "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].",

keywords = "AIDS, Bayesian inference, Conditional independence model, Markov chain Monte Carlo, Prediction",

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year = "1999",

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doi = "10.1016/S0167-2789(99)00105-0",

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T1 - Bayesian conditional-independence modeling of the AIDS epidemic in England and Wales

AU - Gilks, Walter R.

AU - Angelis, Daniela De

AU - Day, Nicholas E.

PY - 1999/9/10

Y1 - 1999/9/10

N2 - 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].

AB - 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].

KW - AIDS

KW - Bayesian inference

KW - Conditional independence model

KW - Markov chain Monte Carlo

KW - Prediction

UR - https://www.scopus.com/pages/publications/0040357184

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VL - 133

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JO - Physica D: Nonlinear Phenomena

JF - Physica D: Nonlinear Phenomena

IS - 1-4

ER -

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

Abstract

UN SDGs

Keywords

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