Evaluating the effectiveness of a population-level health intervention to increment HCV treatment coverage in tuscany region, Italy: An interrupted time series analysis

Worldwide, an estimated 57.8 million people are chronically infected with the Hepatitis C virus (HCV). The advent of direct-acting antivirals (DAAs) has made possible the definition of elimination targets by 2030. This study aimed to evaluate the effectiveness of a population-level health intervention to expand access to HCV treatment in the Tuscany Region, Italy. We used individual-level administrative data from the Tuscany region, collected between January 2015 and December 2022. Data include monthly observations on i) the number of serological tests to detect HCV, ii) the number of PCR tests to detect HCV and, iii) the number of prescriptions of direct-acting antivirals against HCV. We implemented an Interrupted Time Series (ITS) model, where the primary outcome was the number of monthly prescriptions of direct-acting antivirals, while the number of tests to detect HCV were included as control variables. The analysis was implemented i) in the general population, ii) in specific sub-population groups. Results show that the health intervention promoted by the Tuscany Regional Health Authority was highly effective in increasing DAAs treatment coverage in the general population, while no significant effects were observed among sub-population groups. Findings of this study provide evidence to support policies at national and subnational levels to booster HCV screening and simplify access to DAA prescriptions.

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PLoS ONE
Published
2025-05-16
DOI
https://doi.org/10.1371/journal.pone.0306733
Primary Topic
Hepatitis C virus research
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article
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article

Evaluating the effectiveness of a population-level health intervention to increment HCV treatment coverage in tuscany region, Italy: An interrupted time series analysis

Chiara Seghieri, L. Ceccarelli, Lara Tavoschi, Costanza Tortú
PLoS ONE
Hepatitis C virus research
article

Evaluating the effectiveness of a population-level health intervention to increment HCV treatment coverage in tuscany region, Italy: An interrupted time series analysis

Chiara Seghieri, L. Ceccarelli, Lara Tavoschi, Costanza Tortú
article en

Abstract

Worldwide, an estimated 57.8 million people are chronically infected with the Hepatitis C virus (HCV). The advent of direct-acting antivirals (DAAs) has made possible the definition of elimination targets by 2030. This study aimed to evaluate the effectiveness of a population-level health intervention to expand access to HCV treatment in the Tuscany Region, Italy. We used individual-level administrative data from the Tuscany region, collected between January 2015 and December 2022. Data include monthly observations on i) the number of serological tests to detect HCV, ii) the number of PCR tests to detect HCV and, iii) the number of prescriptions of direct-acting antivirals against HCV. We implemented an Interrupted Time Series (ITS) model, where the primary outcome was the number of monthly prescriptions of direct-acting antivirals, while the number of tests to detect HCV were included as control variables. The analysis was implemented i) in the general population, ii) in specific sub-population groups. Results show that the health intervention promoted by the Tuscany Regional Health Authority was highly effective in increasing DAAs treatment coverage in the general population, while no significant effects were observed among sub-population groups. Findings of this study provide evidence to support policies at national and subnational levels to booster HCV screening and simplify access to DAA prescriptions.

PLoS ONEVol. 20(5)
University of Pisa (IT), Scuola Superiore Sant'Anna (IT)
Good health and well-being
Openalex Percentile: Top 84%
Hepatitis C virus research
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Evaluating the effectiveness of a population-level health intervention to increment HCV treatment coverage in tuscany region, Italy: An interrupted time series analysis — Chiara Seghieri, L. Ceccarelli, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS