Document resource
Introduction Although the rate of new diagnoses in Italy has decreased over the past 10 years, late diagnoses increased since 2015. This could affect the extent and trend of undiagnosed infections and for this reason, our objective was to obtain an estimate of the number of individuals who ignore their HIV status, as well as monitor their trend.Material and Methods We applied the ECDC modelling tool (vers. 3.1.2) considering all HIV diagnoses registered in the Italian HIV Surveillance System from 2010 to 2024. In brief, the tool uses surveillance data categorized by CD4 count at diagnosis into four strata (≥500, 350–499, 200–349, < 200) and apply a multi-state back-calculation assuming 1980 as the start of the epidemic, with user-defined intervals to specify the probability of diagnosis over calendar period. In particular, we made two alternative hypotheses on the probability of diagnosis: in the first (Model A) we assumed a constant diagnosis probability during 2010-2024 with a change in 2012 when all Italian regions were included in Surveillance System (100% coverage). In the second hypothesis (Model B), we added a change in 2017 approximately halfway through the period, when we observed a significant decrease in the diagnoses. Of note, in the models we did not consider possible deaths for the HIV diagnoses.Results Estimates of HIV-diagnosed and undiagnosed are shown in the figure by the model A and the model B. In both models, we estimated a similar increasing trend of total diagnosed, whilst a nearly constant decline in HIV-undiagnosed cases, with a slight increase starting in 2017 in model B ( figure 1). These estimates were for model A and B in 2024, respectively: 136.058 diagnosed (95% CI: 115.060 - 157.496) and 127.552 diagnosed (95% CI: 110.890 - 146.885), whilst those undiagnosed were 8.812 (7.424 - 10.332) and 9.800 (95% CI: 7.438 - 11.790).Conclusions We estimated a number of undiagnosed of about 8.800 to 9.800 according to different probability of diagnosis assumptions in the tool, with slightly higher model B-estimate, most likely due to the increase in late diagnoses in recent years. We estimated a decline in undiagnosed, independently of the assumptions made in diagnosis probability. The estimates of both total diagnosed and undiagnosed cases obtained using the tool were similar to those estimated at the beginning of the study period using other methods and sources, especially in the case of Model B (1). The most recent estimates of those diagnosed in 2024 should be confirmed by an ongoing CARPHA 3 study on all PLHIV in Italy.Abstract P14 Figure 1Pattern of total HIV diagnosed and HIV undiagnosed estimated by ECDC modelling tool, 2010-2024