Cargando…

Extending Bayesian back-calculation to estimate age and time specific HIV incidence

CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their inter-related contribution to the observed surveillance data. This paper, extends existing approaches to age-specific settings, perm...

Descripción completa

Detalles Bibliográficos
Autores principales: Brizzi, Francesco, Birrell, Paul J., Plummer, Martyn T., Kirwan, Peter, Brown, Alison E., Delpech, Valerie C., Gill, O. Noel, De Angelis, Daniela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776486/
https://www.ncbi.nlm.nih.gov/pubmed/30811019
http://dx.doi.org/10.1007/s10985-019-09465-1
_version_ 1783456433917919232
author Brizzi, Francesco
Birrell, Paul J.
Plummer, Martyn T.
Kirwan, Peter
Brown, Alison E.
Delpech, Valerie C.
Gill, O. Noel
De Angelis, Daniela
author_facet Brizzi, Francesco
Birrell, Paul J.
Plummer, Martyn T.
Kirwan, Peter
Brown, Alison E.
Delpech, Valerie C.
Gill, O. Noel
De Angelis, Daniela
author_sort Brizzi, Francesco
collection PubMed
description CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their inter-related contribution to the observed surveillance data. This paper, extends existing approaches to age-specific settings, permitting the joint estimation of age- and time-specific incidence and diagnosis rates and the derivation of other epidemiological quantities of interest. This allows the identification of specific age-groups at higher risk of infection, which is crucial in directing public health interventions. We investigate, through simulation studies, the suitability of various bivariate splines for the non-parametric modelling of the latent age- and time-specific incidence and illustrate our method on routinely collected data from the HIV epidemic among gay and bisexual men in England and Wales. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10985-019-09465-1) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6776486
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-67764862019-10-17 Extending Bayesian back-calculation to estimate age and time specific HIV incidence Brizzi, Francesco Birrell, Paul J. Plummer, Martyn T. Kirwan, Peter Brown, Alison E. Delpech, Valerie C. Gill, O. Noel De Angelis, Daniela Lifetime Data Anal Article CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their inter-related contribution to the observed surveillance data. This paper, extends existing approaches to age-specific settings, permitting the joint estimation of age- and time-specific incidence and diagnosis rates and the derivation of other epidemiological quantities of interest. This allows the identification of specific age-groups at higher risk of infection, which is crucial in directing public health interventions. We investigate, through simulation studies, the suitability of various bivariate splines for the non-parametric modelling of the latent age- and time-specific incidence and illustrate our method on routinely collected data from the HIV epidemic among gay and bisexual men in England and Wales. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10985-019-09465-1) contains supplementary material, which is available to authorized users. Springer US 2019-02-27 2019 /pmc/articles/PMC6776486/ /pubmed/30811019 http://dx.doi.org/10.1007/s10985-019-09465-1 Text en © The Author(s) 2019 OpenAccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Brizzi, Francesco
Birrell, Paul J.
Plummer, Martyn T.
Kirwan, Peter
Brown, Alison E.
Delpech, Valerie C.
Gill, O. Noel
De Angelis, Daniela
Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title_full Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title_fullStr Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title_full_unstemmed Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title_short Extending Bayesian back-calculation to estimate age and time specific HIV incidence
title_sort extending bayesian back-calculation to estimate age and time specific hiv incidence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776486/
https://www.ncbi.nlm.nih.gov/pubmed/30811019
http://dx.doi.org/10.1007/s10985-019-09465-1
work_keys_str_mv AT brizzifrancesco extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT birrellpaulj extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT plummermartynt extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT kirwanpeter extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT brownalisone extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT delpechvaleriec extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT gillonoel extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence
AT deangelisdaniela extendingbayesianbackcalculationtoestimateageandtimespecifichivincidence