Eric Tatara 1,2, Louis Shekhtman 3,4, Nicholson Collier 1,2, Marian Major 5, Scott Cotler 3, Basmattee Boodram 6, Jonathan Ozik 1,2, Harel Dahari 3
1 Consortium for Advanced Science and Engineering, University of Chicago (Chicago, USA), 2 Decision and Infrastructure Sciences, Argonne National Laboratory (Argonne, USA), 3 Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University Chicago (Maywwod, USA), 4 Department of Information Science and Applied Artificial Intelligence, Bar-Ilan University (Ramat Gan, Isarel), 5 Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration (Silver Spring, USA), 6 Division of Community Health Sciences, School of Public Health, University of Illinois at Chicago (Chicago, USA)
Introduction: Worldwide >50 million individuals are estimated to be chronically infected with hepatitis C virus (HCV), with ~1.0 million new infections occurring each year. In the US alone an estimated 4 million people are infected with the virus [1] . In 2023, there were an estimated 69,000 acute cases and 11,194 HCV-related deaths. People who inject drugs (PWID) are at high risk for acquiring and transmitting hepatitis C virus (HCV). Direct-acting antiviral (DAA) therapy leads to more than 95% cure rates. However, access, adherence and cost remain barriers to global elimination of HCV with DAA. Re-formulation of DAA to an injectable form to produce sustained concentrations for 24 weeks could not only cure HCV but also protect PWID from repeat infections by suppressing viral replication for 24 weeks with a single dose. In the current study, we aimed to study the effects of a 24-week long-acting DAA treatment among PWID to reach HCV micro-elimination in metropolitan Chicago, IL, USA.
Methods: We used our advanced Hepatitis C Elimination in PWID (HepCEP) agent-based modeling [2] in which HCV transmission probability is determined using a mathematical model of HCV RNA titers among people who share syringes [3]. The HepCEP model simulates the PWID population in Chicago Illinois, USA, and the expansive surrounding suburbs that span counties in Illinois, Wisconsin and Indiana. In this model, we included drug use and syringe sharing behaviors, and associated infection dynamics. In brief, this includes data from enrollees of a large syringe service program (n=6,000, 2006-13), the Chicago injection drug use data collection cycles of the National HIV Behavioral Surveillance (NHBS) survey from 2009 (n=545) and 2012 (n=209), and other local studies. The prevalence of HCV RNA in the population is 32%. DAA treatment enrollment is modelled as (unbiased) random sampling of infected PWID using an annual target enrollment rate of 7.5% of the total PWID population in Chicago and the surrounding area (32,000 individuals) to reach HCV elimination. Access to long-acting DAA was simulated for 10 years. We compared the mean frequencies (using stochastic model replicates) of reinfection and number of unique treatment courses between potential long-acting DAAs and ultra-short 4-week duration DAA-based treatment (e.g., [4]).
Results: The model predicts reaching HCV elimination with a long-acting DAA that provides cure and 24 weeks of protection from repeat infections during a 10-year treatment period results in fewer total infections (3,377, 95%CI: 3,298-3,456) compared to a 4-week DAA-based treatment duration (6,200, 95%CI: 5,960-6,441). Moreover, treatment duration of 24 weeks (15,946 treatments) versus 4 weeks (19,325 treatments) would result in a need for 3,379 fewer treatments.
Conclusions: Our modeling results predict that a 24-week long-acting DAA treatment would result in a reduced number of HCV infections compared to 4-week ultra short DAA-based treatment over a 10-year period to reach HCV micro-elimination in metropolitan Chicago due to greater duration of protection from repeat infections and further transmission.
References:
[1] Hall EW et al. Hepatology 2025;81:625-636.
[2] Tatara E and Shekhtman L et al. MedRxiv doi: https://doi.org/10.1101/2025.07.25.25332212.
[3] Major M et al. Sci Transl Med 2018 Jul 11;10(449):eaao4496.
[4] Cooke GS et al. Lancet 2025 405(10491):1769-1780
Reference: PAGE 34 (2026) Abstr 12302 [www.page-meeting.org/?abstract=12302]
Poster: Drug/Disease Modelling - Infection