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

ABSTRACT: 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.

SUBMITTER: Brizzi F

PROVIDER: S-EPMC6776486 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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

Brizzi Francesco F Birrell Paul J PJ Plummer Martyn T MT Kirwan Peter P Brown Alison E AE Delpech Valerie C VC Gill O Noel ON De Angelis Daniela D

Lifetime data analysis 20190227 4

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-g ...[more]

PMID: 30811019

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