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Hepatitis C virus treatment as prevention in an extended network of people who inject drugs in the USA: a modelling study.

ABSTRACT: BACKGROUND:Chronic infections with hepatitis C virus (HCV) and HIV are highly prevalent in the USA and concentrated in people who inject drugs. Treatment as prevention with highly effective new direct-acting antivirals is a prospective HCV elimination strategy. We used network-based modelling to analyse the effect of this strategy in HCV-infected people who inject drugs in a US city. METHODS:Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment. FINDINGS:Our model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network. INTERPRETATION:Successful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded. FUNDING:National Institute on Drug Abuse.

SUBMITTER: Zelenev A

PROVIDER: S-EPMC5860640 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Hepatitis C virus treatment as prevention in an extended network of people who inject drugs in the USA: a modelling study.

Zelenev Alexei A Li Jianghong J Mazhnaya Alyona A Basu Sanjay S Altice Frederick L FL

The Lancet. Infectious diseases 20171115 2

<h4>Background</h4>Chronic infections with hepatitis C virus (HCV) and HIV are highly prevalent in the USA and concentrated in people who inject drugs. Treatment as prevention with highly effective new direct-acting antivirals is a prospective HCV elimination strategy. We used network-based modelling to analyse the effect of this strategy in HCV-infected people who inject drugs in a US city.<h4>Methods</h4>Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, U ...[more]

PMID: 29153265

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Project description:BackgroundApproximately 1% of adults in Thailand are infected with hepatitis C virus (HCV). New direct-acting antiviral agents achieve sustained virologic responses in >95% of HCV-infected patients and are becoming available in countries around the world. To prepare for new HCV treatment options in Thailand, this study characterized HCV infections among people who inject drugs (PWID) in Bangkok.MethodsThe Bangkok Tenofovir Study (BTS) was a pre-exposure prophylaxis trial conducted among PWID, 2005-2013. Blood specimens were randomly selected from PWID screened for the BTS, to test for anti-HCV antibody and HCV RNA. The HVR1 region was amplified by polymerase chain reaction, using multiplex primer sets with unique identifier sequences; amplification products were pooled in sets of 25; and consensus sequencing was performed to characterize individual HCV genotypes.ResultsThe median age of 3679 participants tested for anti-HCV antibody was 31 years, 3016 (82.0%) were male and 447 (12.2%) were HIV infected. The prevalence of anti-HCV antibody was 44.3%. The adjusted odds of testing positive for anti-HCV antibody were higher in men (adjusted odds ratio [aOR] 3.2, 95% confidence interval [CI] 2.4-4.3), those aged 40 years or older (aOR 2.7, 95% CI 2.1-3.5), those who had more than a primary school education (aOR 1.7, 95% CI 1.4-2.1), and those who tested HIV positive (aOR 5.2, 95% CI 3.7-7.4). HCV RNA was detected in 644 (81.3%) of the 792 anti-HCV antibody-positive specimens, yielding an HCV RNA-positive prevalence of 36.0% (95% CI 33.8-38.2). Among a random sample of 249 of the 644 specimens, 218 could be characterized, and the most common HCV subtypes were 1a (30.3%), 1b (12.8%), 3a (35.8%), 3b (6.9%) and 6n (8.7%).ConclusionThe prevalence of anti-HCV antibody among PWID was 44.3% and more than one third (36.0%) were HCV RNA positive. Genotypes 1, 3 and 6 accounted for all typable infections. As the government of Thailand considers introduction of direct-acting antiviral medications for people with hepatitis C, it will be important to ensure that the medications target these subtypes.

Project description:Background and aimsTo reduce hepatitis C virus (HCV) transmission among people who inject drugs (PWID), Scottish Government-funded national strategies, launched in 2008, promoted scaling-up opioid substitution therapy (OST) and needle and syringe provision (NSP), with some increases in HCV treatment. We test whether observed decreases in HCV incidence post-2008 can be attributed to this intervention scale-up.DesignA dynamic HCV transmission model among PWID incorporating intervention scale-up and observed decreases in behavioural risk, calibrated to Scottish HCV prevalence and incidence data for 2008/09.SettingScotland, UK.ParticipantsPWID.MeasurementsModel projections from 2008 to 2015 were compared with data to test whether they were consistent with observed decreases in HCV incidence among PWID while incorporating the observed intervention scale-up, and to determine the impact of scaling-up interventions on incidence.FindingsWithout fitting to epidemiological data post-2008/09, the model incorporating observed intervention scale-up agreed with observed decreases in HCV incidence among PWID between 2008 and 2015, suggesting that HCV incidence decreased by 61.3% [95% credibility interval (CrI) = 45.1-75.3%] from 14.2/100 person-years (py) (9.0-20.7) to 5.5/100 py (2.9-9.2). On average, each model fit lay within 84% (10.1/12) of the confidence bounds for the 12 incidence data points against which the model was compared. We estimate that scale-up of interventions (OST + NSP + HCV treatment) and decreases in high-risk behaviour from 2008 to 2015 resulted in a 33.9% (23.8-44.6%) decrease in incidence, with the remainder [27.4% (17.6-37.0%)] explained by historical changes in OST + NSP coverage and risk pre-2008. Projections suggest that scaling-up of all interventions post-2008 averted 1492 (657-2646) infections over 7 years, with 1016 (308-1996), 404 (150-836) and 72 (27-137) due to scale-up of OST + NSP, decreases in high-risk behaviour and HCV treatment, respectively.ConclusionsMost of the decline in hepatitis C virus (HCV) incidence in Scotland between 2008 and 2015 appears to be attributable to intervention scale-up (opioid substitution therapy and needle and syringe provision) due to government strategies on HCV and drugs.

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Hepatitis C virus treatment as prevention in an extended network of people who inject drugs in the USA: a modelling study.

Publications

Hepatitis C virus treatment as prevention in an extended network of people who inject drugs in the USA: a modelling study.

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