Open Access
February 2014 Estimation of HIV Burden through Bayesian Evidence Synthesis
Daniela De Angelis, Anne M. Presanis, Stefano Conti, A. E. Ades
Statist. Sci. 29(1): 9-17 (February 2014). DOI: 10.1214/13-STS428


Planning, implementation and evaluation of public health policies to control the human immunodeficiency virus (HIV) epidemic require regular monitoring of disease burden. This includes the proportion living with HIV, whether diagnosed or not, and the rate of new infections in the general population and in specific risk groups and regions. Estimation of these quantities is not straightforward: data informing them directly are not typically available, but a wealth of indirect information from surveillance systems and ad hoc studies can inform functions of these quantities. In this paper we show how the estimation problem can be successfully solved through a Bayesian evidence synthesis approach, relaxing the focus on “best available” data to which classical methods are typically restricted. This more comprehensive and flexible use of evidence has led to the adoption of our proposed approach as the official method to estimate HIV prevalence in the United Kingdom since 2005.


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Daniela De Angelis. Anne M. Presanis. Stefano Conti. A. E. Ades. "Estimation of HIV Burden through Bayesian Evidence Synthesis." Statist. Sci. 29 (1) 9 - 17, February 2014.


Published: February 2014
First available in Project Euclid: 9 May 2014

zbMATH: 1332.62409
MathSciNet: MR3201841
Digital Object Identifier: 10.1214/13-STS428

Keywords: Bayesian inference , disease burden , evidence synthesis , Graphical model , HIV

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.29 • No. 1 • February 2014
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