Dataset Information

Hepatitis C transmission in young people who inject drugs: Insights using a dynamic model informed by state public health surveillance.

ABSTRACT: Increasing injection of heroin and prescription opioids have led to increases in the incidence of hepatitis C virus (HCV) infections in US young adults since the early 2000s. How best to interrupt transmission and decrease HCV prevalence in young people who inject drugs (PWID) is uncertain. We developed an age-stratified ordinary differential equation HCV transmission model of PWID aged 15-64, which we fit to Michigan HCV surveillance data among young PWID aged 15-29. We used Latin hypercube sampling to fit to data under 10,000 plausible model parameterizations. We used the best-fitting 10% of simulations to predict the potential impact of primary (reducing injection initiation), secondary (increasing cessation, reducing injection partners, or reducing injection drug use relapse), and tertiary (HCV treatment) interventions (over the period 2017-2030) on acute and chronic HCV cases by the year 2030. Treating 3 per 100 current and former PWID per year could reduce chronic HCV by 27.3% (range: 18.7-30.3%) and acute HCV by 23.6% (range: 6.7-29.5%) by 2030 among PWID aged 15-29 if 90% are cured (i.e. achieved sustained virologic response [SVR] to treatment). Reducing the number of syringe sharing partners per year by 10% was predicted to reduce chronic HCV by 15.7% (range: 9.4-23.8%) and acute cases by 21.4% (range: 14.2-32.3%) among PWID aged 15-29 by 2030. In simulations of combinations of interventions, reducing injection initiation, syringe sharing, and relapse rates each by 10% while increasing cessation rates by 10% predicted a 27.7% (range: 18.0-39.7%) reduction in chronic HCV and a 38.4% (range: 28.3-53.3%) reduction in acute HCV. Our results highlight the need for HCV treatment among both current and former PWID and the scale up of both primary and secondary interventions to concurrently reduce HCV prevalence and incidence in Michigan.

SUBMITTER: Gicquelais RE

PROVIDER: S-EPMC6690387 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 estimated deaths attributed yearly to HCV-related liver diseases. It disproportionally affects people who inject drugs (PWID). Currently there is no preventative vaccine and interventions feature long treatment durations with severe side-effects. Upcoming treatments will improve this situation, making possible large-scale treatment interventions. How these strategies should target HCV-infected PWID remains an important unanswered question. Previous models of HCV have lacked empirically grounded contact models of PWID. Here we report results on HCV transmission and treatment using simulated contact networks generated from an empirically grounded network model using recently developed statistical approaches in social network analysis. Our HCV transmission model is a detailed, stochastic, individual-based model including spontaneously clearing nodes. On transmission we investigate the role of number of contacts and injecting frequency on time to primary infection and the role of spontaneously clearing nodes on incidence rates. On treatment we investigate the effect of nine network-based treatment strategies on chronic prevalence and incidence rates of primary infection and re-infection. Both numbers of contacts and injecting frequency play key roles in reducing time to primary infection. The change from "less-" to "more-frequent" injector is roughly similar to having one additional network contact. Nodes that spontaneously clear their HCV infection have a local effect on infection risk and the total number of such nodes (but not their locations) has a network wide effect on the incidence of both primary and re-infection with HCV. Re-infection plays a large role in the effectiveness of treatment interventions. Strategies that choose PWID and treat all their contacts (analogous to ring vaccination) are most effective in reducing the incidence rates of re-infection and combined infection. A strategy targeting infected PWID with the most contacts (analogous to targeted vaccination) is the least effective.

Project description:ImportanceThe success of direct-acting antiviral therapies for chronic hepatitis C virus (HCV) infection led the World Health Organization to set elimination targets by 2030. For the United States to achieve these benchmarks, public health responses must target high-risk populations, such as people who inject drugs (PWID), a group with high rates of HCV incidence and low rates of treatment uptake.ObjectiveTo evaluate potential improvements in the HCV care cascade among PWID, focusing on improved testing, treatment uptake, and access to harm reduction.Design, setting, and participantsThis decision analytic model used a differential equation-based dynamic transmission model based on data from New Hampshire, an illustrative state with a large number of PWID and limited HCV treatment infrastructure. Surveillance data through 2020 was used for model parameterization, and the final analysis was conducted in May 2021.Main outcomes and measuresModel forecasts of chronic HCV cases and advanced-stage HCV outcomes from 2022 to 2045.ResultsA total of 6 scenarios were tested: (1) the base case, (2) improved harm reduction, (3) improved testing, (4) improved treatment, (5) improved testing and treatment, and (6) improved testing, treatment, and harm reduction. All scenarios with improved testing, treatment uptake, and/or access to harm reduction were associated with decreases in forecasted HCV prevalence and HCV-associated mortality compared with the base case. Improving harm reduction, testing, and treatment individually were forecast to reduce prevalence of HCV in 2045 from 69.7% in the base case to 62.8%, 45.7%, and 35.5%, respectively. Combining treatment and testing improvements was associated with a 2045 prevalence of 0.3%; adding harm reduction improvements was associated with further reductions in prevalence forecasts (to 0.2%), with fewer total treatments (10 960 vs 13 219 from 2022-2045).Conclusions and relevanceIn this modeling study, no single intervention was projected to achieve World Health Organization HCV elimination targets. Scenarios with improvements in both testing and treatment were associated with a prevalence of less than 3% by 2030 and achieved elimination targets. Adding improvements in harm reduction was associated with faster reductions in prevalence and fewer treatments.

Dataset Information

Hepatitis C transmission in young people who inject drugs: Insights using a dynamic model informed by state public health surveillance.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets