4,009 research outputs found

    Dynamic modelling of hepatitis C virus transmission among people who inject drugs: a methodological review

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    Equipment sharing among people who inject drugs (PWID) is a key risk factor in infection by hepatitis C virus (HCV). Both the effectiveness and cost-effectiveness of interventions aimed at reducing HCV transmission in this population (such as opioid substitution therapy, needle exchange programs or improved treatment) are difficult to evaluate using field surveys. Ethical issues and complicated access to the PWID population make it difficult to gather epidemiological data. In this context, mathematical modelling of HCV transmission is a useful alternative for comparing the cost and effectiveness of various interventions. Several models have been developed in the past few years. They are often based on strong hypotheses concerning the population structure. This review presents compartmental and individual-based models in order to underline their strengths and limits in the context of HCV infection among PWID. The final section discusses the main results of the papers

    Impact of Hepatitis C Treatment as Prevention for People Who Inject Drugs is sensitive to contact network structure

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    Treatment as Prevention (TasP) using directly-acting antivirals has been advocated for Hepatitis C Virus (HCV) in people who inject drugs (PWID), but treatment is expensive and TasP’s effectiveness is uncertain. Previous modelling has assumed a homogeneously-mixed population or a static network lacking turnover in the population and injecting partnerships. We developed a transmission-dynamic model on a dynamic network of injecting partnerships using data from survey of injecting behaviour carried out in London, UK. We studied transmission on a novel exponential-clustered network, as well as on two simpler networks for comparison, an exponential unclustered and a random network, and found that TasP’s effectiveness differs markedly. With respect to an exponential-clustered network, the random network (and homogeneously-mixed population) overestimate TasP’s effectiveness, whereas the exponential-unclustered network underestimates it. For all network types TasP’s effectiveness depends on whether treated patients change risk behaviour, and on treatment coverage: higher coverage requires fewer total treatments for the same health gain. Whilst TasP can greatly reduce HCV prevalence, incidence of infection, and incidence of reinfection in PWID, assessment of TasP’s effectiveness needs to take account of the injecting-partnership network structure and post-treatment behaviour change, and further empirical study is required

    Combination interventions to prevent HCV transmission among people who inject drugs: modelling the impact of antiviral treatment, needle and syringe programs, and opiate substitution therapy

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    BackgroundInterventions such as opiate substitution therapy (OST) and high-coverage needle and syringe programs (HCNSP) cannot substantially reduce hepatitis C virus (HCV) prevalence among people who inject drugs (PWID). HCV antiviral treatment may prevent onward transmission. We project the impact of combining OST, HCNSP, and antiviral treatment on HCV prevalence/incidence among PWID.MethodsAn HCV transmission model among PWID was used to project the combinations of OST, HCNSP, and antiviral treatment required to achieve different prevalence and incidence reductions within 10 years for 3 chronic prevalence scenarios and the impact of HCV treatment if only delivered through OST programs. Multivariate and univariate sensitivity analyses were performed.ResultsLarge reductions (>45%) in HCV chronic prevalence over 10 years require HCV antiviral treatment. Scaling up OST and HCNSP substantially reduces the treatment rate required to achieve specific HCV prevalence reductions. If OST and HCNSP coverage were increased to 40% each (no coverage at baseline), then annually treating 10, 23, or 42 per 1000 PWID over 10 years would halve prevalence for 20%, 40%, or 60% baseline chronic HCV prevalences, respectively. Approximately 30% fewer treatments are necessary with new direct-acting antivirals. If coverage of OST and HCNSP is 50% at baseline, similar prevalence reductions require higher treatment rates for the same OST and HCNSP coverage.ConclusionsCombining antiviral treatment with OST with HCNSP is critical for achieving substantial reductions (>50%) in HCV chronic prevalence over 10 years. Empirical studies are required on how best to scale up antiviral treatment and combine treatment with other interventions

    Restrictions for reimbursement of interferon-free direct-acting antiviral drugs for HCV infection in Europe

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    To access publisher's full text version of this article click on the hyperlink belowAll-oral direct-acting antiviral drugs (DAAs) for hepatitis C virus, which have response rates of 95% or more, represent a major clinical advance. However, the high list price of DAAs has led many governments to restrict their reimbursement. We reviewed the availability of, and national criteria for, interferon-free DAA reimbursement among countries in the European Union and European Economic Area, and Switzerland. Reimbursement documentation was reviewed between Nov 18, 2016, and Aug 1, 2017. Primary outcomes were fibrosis stage, drug or alcohol use, prescriber type, and HIV co-infection restrictions. Among the 35 European countries and jurisdictions included, the most commonly reimbursed DAA was ombitasvir, paritaprevir, and ritonavir, with dasabuvir, and with or without ribavirin (33 [94%] countries and jurisdictions). 16 (46%) countries and jurisdictions required patients to have fibrosis at stage F2 or higher, 29 (83%) had no listed restrictions based on drug or alcohol use, 33 (94%) required a specialist prescriber, and 34 (97%) had no additional restrictions for people co-infected with HIV and hepatitis C virus. These findings have implications for meeting WHO targets, with evidence of some countries not following the 2016 hepatitis C virus treatment guidelines by the European Association for the Study of Liver.UNSW (Sydney, Australia) CanHepC Trainee Program (Canada) National Health and Medical Research Council Australian Government Department of Healt

    Incarceration history and risk of HIV and hepatitis C virus acquisition among people who inject drugs: a systematic review and meta-analysis

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    Background People who inject drugs (PWID) experience a high prevalence of incarceration and might be at high risk of HIV and hepatitis C virus (HCV) infection during or after incarceration. We aimed to assess whether incarceration history elevates HIV or HCV acquisition risk among PWID. Methods In this systematic review and meta-analysis, we searched MEDLINE, Embase, and PsycINFO databases for studies in any language published from Jan 1, 2000 until June 13, 2017 assessing HIV or HCV incidence among PWID. We included studies that measured HIV or HCV incidence among community-recruited PWID. We included only studies reporting original results and excluded studies that evaluated incident infections by self-report. We contacted authors of cohort studies that met the inclusion or exclusion criteria, but that did not report on the outcomes of interest, to request data. We extracted and pooled data from the included studies using random-effects meta-analyses to quantify the associations between recent (past 3, 6, or 12 months or since last follow-up) or past incarceration and HIV or HCV acquisition (primary infection or reinfection) risk among PWID. We assessed the risk of bias of included studies using the Newcastle-Ottawa Scale. Between-study heterogeneity was evaluated using the I2 statistic and the P-value for heterogeneity. Findings We included published results from 20 studies and unpublished results from 21 studies. These studies originated from Australasia, western and eastern Europe, North and Latin America, and east and southeast Asia. Recent incarceration was associated with an 81% (relative risk [RR] 1·81, 95% CI 1·40–2·34) increase in HIV acquisition risk, with moderate heterogeneity between studies (I2=63·5%; p=0·001), and a 62% (RR 1·62, 95% CI 1·28–2·05) increase in HCV acquisition risk, also with moderate heterogeneity between studies (I2=57·3%; p=0·002). Past incarceration was associated with a 25% increase in HIV (RR 1·25, 95% CI 0·94–1·65) and a 21% increase in HCV (1·21, 1·02–1·43) acquisition risk. Interpretation Incarceration is associated with substantial short-term increases in HIV and HCV acquisition risk among PWID and could be a significant driver of HCV and HIV transmission among PWID. These findings support the need for developing novel interventions to minimise the risk of HCV and HIV acquisition, including addressing structural risks associated with drug laws and excessive incarceration of PWID

    HCV epidemiology in high-risk groups and the risk of reinfection

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    Injecting risk behaviours among people who inject drugs (PWID) and high-risk sexual practices among men who have sex with men (MSM) are important routes of hepatitis C virus (HCV) transmission. Current direct-acting antiviral treatment offers unique opportunities for reductions in HCV-related liver disease burden and epidemic control in high-risk groups, but these prospects could be counteracted by HCV reinfection due to on-going risk behaviours after successful treatment. Based on existing data from small and heterogeneous studies of interferon-based treatment, the incidence of reinfection after sustained virological response range from 2-6/100 person years among PWID to 10-15/100 person years among human immunodeficiency virus-infected MSM. These differences mainly reflect heterogeneity in study populations with regards to risk behaviours, but also reflect variations in study designs and applied virological methods. Increasing levels of reinfection are to be expected as we enter the interferon-free treatment era. Individual- and population-level efforts to address and prevent reinfection should therefore be undertaken when providing HCV care for people with on-going risk behaviour. Constructive strategies include acknowledgement, education and counselling, harm reduction optimization, scaled-up treatment including treatment of injecting networks, post-treatment screening, and rapid retreatment of reinfections

    The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs

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    With the development of new highly efficacious direct acting antiviral treatments (DAAs) for hepatitis C (HCV), the concept of treatment as prevention is gaining credence. To date the majority of mathematical models assume perfect mixing with injectors having equal contact with all other injectors. This paper explores how using a networks based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. Method: Using observational data we parameterized an Exponential Random Graph Model containing 524 nodes. We simulated transmission of HCV through this network using a discrete time, stochastic transmission model. The effect of five treatment strategies on the prevalence of HCV was investigated; two of these strategies were 1) treat randomly selected nodes and 2) “treat your friends” where an individual is chosen at random for treatment and all their infected neighbours are treated. Results: As treatment coverage increases, HCV prevalence at 10 years reduces for both the high efficacy and low efficacy treatment. Within each set of parameters, the “treat your friends” strategy performed better than the random strategy being most marked for higher efficacy treatment. For example over 10 years of treating 25 per 1000 PWID, the prevalence drops from 50% to 40% for the random strategy, and to 33% for the “treat your friends” strategy (6.5% difference, 95% CI 5.1 – 8.1%). Discussion: “Treat your friends” is a feasible means of utilising network strategies to improve treatment efficiency. In an era of highly efficacious and highly tolerable treatment such an approach will benefit not just the individual but the community more broadly by reducing the prevalence of HCV amongst PWID

    Int J Drug Policy

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    Network modelling is a valuable tool for simulating hepatitis C virus (HCV) and HIV transmission among people who inject drugs (PWID) and assessing the potential impact of treatment and harm-reduction interventions. In this paper, we review literature on network simulation models, highlighting key structural considerations and questions that network models are well suited to address. We describe five approaches (Erd\uf6s-R\ue9nyi, Stochastic Block, Watts-Strogatz, Barab\ue1si-Albert, and Exponential Random Graph Model) used to model partnership formation with emphasis on the strengths of each approach in simulating different features of real-world PWID networks. We also review two important structural considerations when designing or interpreting results from a network simulation study: (1) dynamic vs. static network and (2) injection only vs. both injection and sexual networks. Dynamic network simulations allow partnerships to evolve and disintegrate over time, capturing corresponding shifts in individual and population-level risk behaviour; however, their high level of complexity and reliance on difficult-to-observe data has driven others to develop static network models. Incorporating both sexual and injection partnerships increases model complexity and data demands, but more accurately represents HIV transmission between PWID and their sexual partners who may not also use drugs. Network models add the greatest value when used to investigate how leveraging network structure can maximize the effectiveness of health interventions and optimize investments. For example, network models have shown that features of a given network and epidemic influence whether the greatest community benefit would be achieved by allocating hepatitis C or HIV treatment randomly, versus to those with the most partners. They have also demonstrated the potential for syringe services and "buddy sharing" programs to reduce disease transmission.U38 PS004644/PS/NCHHSTP CDC HHSUnited States/P30 DA040500/DA/NIDA NIH HHSUnited States/P30 AI042853/AI/NIAID NIH HHSUnited States/CC/CDC HHSUnited States/R01 DA046527/DA/NIDA NIH HHSUnited States/2022-01-05T00:00:00Z31740175PMC872979210782vault:4066

    Hepatitis C transmission and treatment as prevention - The role of the injecting network

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    Background: The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV, culminating in a network-based approach to provision of direct-acting antiviral therapy. Methods: Between 2005 and 2010 we followed a cohort of 413 PWID, measuring HCV incidence, prevalence and injecting risk, including network-related factors. We developed an individual-based HCV transmission model, using it to simulate the spread of HCV through the empirical social network of PWID. In addition, we created an empirically grounded network model of injecting relationships using exponential random graph models (ERGMs), allowing simulation of realistic networks for investigating HCV treatment and intervention strategies. Our empirical work and modelling underpins the TAP Study, which is examining the feasibility of community-based treatment of PWID with DAAs. Results: We observed incidence rates of HCV primary infection and reinfection of 12.8 per 100 person-years (PY) (95%CI: 7.7-20.0) and 28.8 per 100 PY (95%CI: 15.0-55.4), respectively, and determined that HCV transmission clusters correlated with reported injecting relationships. Transmission modelling showed that the empirical network provided some protective effect, slowing HCV transmission compared to a fully connected, homogenous PWID population. Our ERGMs revealed that treating PWID and all their contacts was the most effective strategy and targeting treatment to infected PWID with the most contacts the least effective. Conclusion: Networks-based approaches greatly increase understanding of HCV transmission and will inform the implementation of treatment as prevention using DAAs
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