This study provides an update on hepatitis C virus (HCV) estimates across Italy up to January 2021. A mathematical probabilistic modelling approach, including a Markov chain for liver disease progression, was used to estimate current HCV viraemic burden. Prevalence was defined by geographic area using an estimated annual historical HCV incidence by age, treatment, and migration rate from the Italian National database (ISTAT). Viraemic infection was estimated for the main HCV transmission routes by stages F0-F3 (patients without liver cirrhosis, i.e., potentially asymptomatic liver disease) and F4 (patients with liver cirrhosis, i.e., potentially symptomatic liver disease). By January 2021, we estimated that there were 398,610 individuals in Italy with active HCV infection (prevalence of 0.66%; 95% CI: 0.66-0.67), of which 287,730 (0.48%; 95% CI: 0.46-0.59%) were stage F0-F3. Prevalence values for all individuals with active HCV infection were: North 0.54% (95% CI: 0.53-0.54%), Central 0.88% (95% CI: 0.87-0.89%), South 0.72% (95% CI: 0.71-0.73%), and the Isles 0.67% (95% CI: 0.66-0.68%). The population at risk for previous/current drug injection accounted for 48.6% of all individuals with active HCV infection. A modelling approach such as this to estimate and update the prevalence of active HCV infection could be a useful methodology for the evaluation of healthcare policies related to HCV elimination plans.

Prevalence of hepatitis C virus estimates of undiagnosed individuals in different Italian regions. A mathematical modelling approach by route of transmission and fibrosis progression with results up to January 2021 / Kondili, Loreta A; Andreoni, Massimo; Aghemo, Alessio; Mastroianni, Claudio Maria; Merolla, Rocco; Gallinaro, Valentina; Craxì, Antonio. - In: NEW MICROBIOLOGICA. - ISSN 1121-7138. - 45:4(2022), pp. 249-259.

Prevalence of hepatitis C virus estimates of undiagnosed individuals in different Italian regions. A mathematical modelling approach by route of transmission and fibrosis progression with results up to January 2021

Mastroianni, Claudio Maria;
2022

Abstract

This study provides an update on hepatitis C virus (HCV) estimates across Italy up to January 2021. A mathematical probabilistic modelling approach, including a Markov chain for liver disease progression, was used to estimate current HCV viraemic burden. Prevalence was defined by geographic area using an estimated annual historical HCV incidence by age, treatment, and migration rate from the Italian National database (ISTAT). Viraemic infection was estimated for the main HCV transmission routes by stages F0-F3 (patients without liver cirrhosis, i.e., potentially asymptomatic liver disease) and F4 (patients with liver cirrhosis, i.e., potentially symptomatic liver disease). By January 2021, we estimated that there were 398,610 individuals in Italy with active HCV infection (prevalence of 0.66%; 95% CI: 0.66-0.67), of which 287,730 (0.48%; 95% CI: 0.46-0.59%) were stage F0-F3. Prevalence values for all individuals with active HCV infection were: North 0.54% (95% CI: 0.53-0.54%), Central 0.88% (95% CI: 0.87-0.89%), South 0.72% (95% CI: 0.71-0.73%), and the Isles 0.67% (95% CI: 0.66-0.68%). The population at risk for previous/current drug injection accounted for 48.6% of all individuals with active HCV infection. A modelling approach such as this to estimate and update the prevalence of active HCV infection could be a useful methodology for the evaluation of healthcare policies related to HCV elimination plans.
2022
hcv; hepatitis c infection; markov chain; prevalence; undiagnosed
01 Pubblicazione su rivista::01a Articolo in rivista
Prevalence of hepatitis C virus estimates of undiagnosed individuals in different Italian regions. A mathematical modelling approach by route of transmission and fibrosis progression with results up to January 2021 / Kondili, Loreta A; Andreoni, Massimo; Aghemo, Alessio; Mastroianni, Claudio Maria; Merolla, Rocco; Gallinaro, Valentina; Craxì, Antonio. - In: NEW MICROBIOLOGICA. - ISSN 1121-7138. - 45:4(2022), pp. 249-259.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1668599
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