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

Francesco Brizzi, Paul J Birrell, Martyn T Plummer, Peter Kirwan, Alison E Brown, Valerie C Delpech, O Noel Gill, Daniela De Angelis

Research output: Contribution to journalArticle (Academic Journal)peer-review

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.

Original languageEnglish
JournalLifetime Data Analysis
DOIs
Publication statusPublished - 27 Feb 2019

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