A Novel Municipal-Level Approach to Uncover the Hidden Burden of Hepatitis C: A Replicable Model for National Elimination Strategies.

BACKGROUND

Hepatitis C Virus (HCV) remains a global health challenge as WHO elimination targets are not achievable in most countries, mainly due to the high number of undiagnosed individuals. In Italy, where national elimination efforts are ongoing, regional disparities further hinder progress. This study aimed to characterize the hidden burden of chronic HCV infection across t he territory of the Province of Salerno, Southern Italy, to suggest a novel municipal-level screening approach, with implications for national strategies.

METHODS

We analyzed records of residents diagnosed with chronic HCV infection and linked to care between 2015 and 2022. Data included age, sex, municipality of residence, HCV genotype, and fibrosis stage. Observed prevalence was compared with expected prevalence derived from national/regional benchmarks. Municipalities were categorized as urban or rural based on the resident population.

RESULTS

A total of 3528 cases were identified across 139 municipalities. Patients had a mean age of 63 years, and 54% were male. Half were diagnosed at an advanced stage (F3-F4), with genotype 1b being predominant. The hidden burden increased with age and showed a higher prevalence in rural areas compared to urban ones, with values of about 7 vs. 3 per 1000 inhabitants respectively. Logistic regression analysis identified age, male sex, urban residence, and genotype 1b as factors associated with advanced fibrosis or cirrhosis.

CONCLUSIONS

This is the first Italian study to apply a standardized municipal-level classification to quantify the hidden burden of HCV. The model identifies underdiagnosed areas, highlights urban-rural disparities (a higher degree of underdiagnosis in rural areas versus a higher frequency of late diagnosis in urban ones), and provides a replicable tool for precision public health. Its adoption could enhance national HCV elimination efforts by supporting targeted screening, optimized resource allocation, and equitable access to care.