DIH-LING LUH2026-10-162026-10-162025-12-01Pure ID: 14937199Pure UUID: 792c7d7c-a654-48f5-8f11-101565066f2910.1016/j.jfma.2025.10.020https://www.scopus.com/pages/publications/105019211222https://scholars.csmu.edu.tw/handle/123456789/25694Background/purpose: Hepatitis C virus (HCV) infection remains a global health challenge. The Changhua Integrated Program to Stop HCV Infection (CHIPS–C), launched in 2019, aimed to achieve HCV elimination in alignment with Taiwan's 2025 national target by combining general population testing with targeted micro-elimination strategies. Methods: Antecedent anti-HCV data were used to estimate viremic HCV prevalence to set diagnostic and treatment targets. HCV testing was embedded into services for marginalized populations, chronic disease management, and community-based multiple screening through collaboration among gastroenterologists and various specialties. Program performance was assessed using HCV care cascade indicators, and population-level impact was evaluated by care delivery channels, age, gender, geographic areas, and changes in HCV viremia prevalence. Results: Marginalized populations had an average HCV prevalence of 54.9 %, with moderate rates (5.8 %–7.4 %) in chronic disease groups and the lowest prevalence (2.6 %) in the general population. From 2005 to 2024, 513897 individuals were screened through the extensive, county-wide participation of all relevant care settings. High care cascade performance was consistently achieved across all care settings. Overall, 98.5 % (16675) of the estimated viremic cases were diagnosed, and 90.5 % (15098) of those diagnosed received treatment, exceeding the WHO's programmatic target. HCV viremia prevalence declined from 2.43 % in 2003 to 0.39 % in 2024, marking an 84.1 % reduction. Conclusion: The CHIPS–C program demonstrated that integrating HCV elimination within diverse communicable and noncommunicable disease programs can effectively accelerate progress toward elimination goals. This locally led, collaborative, and multi-channel strategy provides a scalable model for other regions with comparable HCV burdens.enjournal article