Theme: Social Science & Policy Research Year: 2022
Background:
The World Health Organization (WHO) has called for eliminating hepatitis C virus (HCV) as a global
public health threat by 2030. To meet the elimination targets, PWID as a high-risk subgroup require
prioritization for treatment especially given the impact of COVID-19; however, governments would
need to rely on population level models that include PWID to assess levels of transmission and
evaluate elimination strategies. Our model estimates treatment levels in PWID that would enable
the United States (US) to reach its targets for 2030.
Methods:
We developed a deterministic compartmental model of HCV transmission to estimate the treatment
reach needed in specific sub-populations that drive the epidemic to achieve elimination targets. The
population is divided into three risk groups: general population, PWID in the community, and a
prison population. Pathways allow groups to be modelled as current and former, and treatment
pathways are tracked for all groups. People in the model move between compartments due to
cessation or relapse from injection drug use and/or incarceration or release from prison.
Results:
The model suggests that there are several potential solutions to achieve the 2030 incidence
elimination target, depending on whether the limiting factor is number of treatments, net cost,
overall health gain or the relative cost-effectiveness of the policy. For example, a 75/33 (per 1000
PWID) split in treatment reach between incarcerated and community PWID from 2022-2030 would
achieve the WHO target with about 6 million treatments, generating approximately 11.5 million
quality-adjusted life-years (QALYs) at an estimated cost of $6,000 per QALY gained.
Conclusion:
WHO elimination targets can only be reached in the US if treatment is quickly scaled up in high-risk
populations such as community-based and incarcerated PWID. Our model allows for policy makers
to investigate a range of treatment allocation strategies based on essential limits, goals, and
constraints.
Disclosure of Interest Statement:
AbbVie funded this study and participated in the study design; study research; collection, analysis
and interpretation of data; and writing, reviewing and approving of this publication. All authors had
access to the data, and participated in the development, review, and approval, and in the decision to
submit this publication. No honoraria or payments were made for authorship.
Stevens W is an employee of Medicus Economics, LLC. Medicus Economics has received funding
from AbbVie Inc. for this project.
Jeffries D is a contractor of Medicus Economics, LLC.
Marx SE, Jiao S, Collins MA, and Kaur J are full-time employees of AbbVie and may hold AbbVie
stock and/or stock options.