Late HIV diagnosis: An application of flexible Bayesian approaches to understand associated factors and time to diagnosis in Ireland, 2015–2024

Abstract Objectives Late HIV diagnosis is associated with increased morbidity, mortality and onward transmission. The proportion diagnosed late reflects the combined effects of testing delays, incidence and migration, complicating its interpretation. We analysed national HIV surveillance data for Ireland (2015–2024) to understand the factors associated with late HIV diagnosis and testing delays. Methods We estimated prevalence ratios (PRs) for late diagnosis among new diagnoses using Bayesian logistic regression with marginal standardization. We investigated testing delays by estimating infection times and modelling truncation‐adjusted delay distributions with Bayesian lognormal regression. We conducted several sensitivity analyses for the main findings. Results Among 1551 included new HIV diagnoses with available information, 684 (44.1%) were late. This proportion exceeded 50% in several subgroups, including people aged over 50 years, people whose probable mode of transmission was heterosexual contact, and people born in sub‐Saharan Africa. Increasing age (adjusted PR per decade 1.20; 95% credible interval [CrI] 1.15–1.26) and heterosexual transmission (adjusted PR for heterosexual men vs. sex between men 1.43; 95% CrI 1.23–1.67) were associated with late diagnosis in both univariable and multivariable models. For in‐Ireland infections, median time from infection to diagnosis was estimated at 1.94 years (95% CrI 1.36–3.40), though this was particularly sensitive to modelling assumptions assessed in our sensitivity analyses, and the multivariable findings suggested longer time to diagnosis for men with heterosexual transmission in particular. For pre‐migration infections, median time from arrival to diagnosis was estimated at 0.60 years (95% CrI 0.47–0.83), and an estimated 50.5% of those diagnosed to date were late. Conclusion Late HIV diagnosis represents a significant challenge. Estimating time‐to‐diagnosis distributions may help separate the influence of testing delays from incidence and migration. The burden demonstrated across multiple groups highlights the need for normalization and expansion of HIV testing within and beyond traditional risk groups.