Imperial College London
Alternate

DrMichaelPickles

Faculty of Medicine, School of Public Health

Advanced Research Fellow
 
 
 
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m.pickles

 
 
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Location

 

School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Dureau:2016:10.1111/rssc.12116,
author = {Dureau, J and Kalogeropoulos, K and Vickerman, P and Pickles, M and Boily, M-C},
doi = {10.1111/rssc.12116},
journal = {Journal of the Royal Statistical Society Series C - Applied Statistics},
pages = {237--257},
title = {A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data},
url = {http://dx.doi.org/10.1111/rssc.12116},
volume = {65},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Evaluation of large-scale intervention programmes against human immunodeficiency virus (HIV) is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the frequency of condom use over time, or other self-reported behaviour changes, for which we generally have limited or potentially biased data. We employ a Bayesian inference methodology that incorporates an HIV transmission dynamics model to estimate condom use time trends from HIV prevalence data. Estimation is implemented via particle Markov chain Monte Carlo methods, applied for the first time in this context. The preliminary choice of the formulation for the time varying parameter reflecting the proportion of condom use is critical in the context studied, because of the very limited amount of condom use and HIV data available. We consider various novel formulations to explore the trajectory of condom use over time, based on diffusion-driven trajectories and smooth sigmoid curves. Numerical simulations indicate that informative results can be obtained regarding the amplitude of the increase in condom use during an intervention, with good levels of sensitivity and specificity performance in effectively detecting changes. The application of this method to a real life problem demonstrates how it can help in evaluating HIV interventions based on a small number of prevalence estimates, and it opens the way to similar applications in different contexts.
AU  - Dureau,J
AU  - Kalogeropoulos,K
AU  - Vickerman,P
AU  - Pickles,M
AU  - Boily,M-C
DO  - 10.1111/rssc.12116
EP  - 257
PY  - 2016///
SN  - 0035-9254
SP  - 237
TI  - A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data
T2  - Journal of the Royal Statistical Society Series C - Applied Statistics
UR  - http://dx.doi.org/10.1111/rssc.12116
UR  - http://hdl.handle.net/10044/1/30538
VL  - 65
ER  -
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