Modelling the spread of hepatitis C virus infection among injecting drug users in Glasgow: Implications for prevention

Testing to sustain hepatitis C elimination targets in people who inject drugs: A network-based model

Little is known about the level of testing required to sustain elimination of hepatitis C (HCV), once achieved. In this study, we model the testing coverage required to maintain HCV elimination in an injecting network of people who inject drugs (PWID). We test the hypothesis that network-based strategies are a superior approach to deliver testing. We created a dynamic injecting network structure connecting 689 PWID based on empirical data. The primary outcome was the testing coverage required per month to maintain prevalence at the elimination threshold over 5 years. We compared four testing strategies. Without any testing or treatment provision, the prevalence of HCV increased from the elimination threshold (11.68%) to a mean of 25.4% (SD 2.96%) over the 5-year period. To maintain elimination with random testing, on average, 4.96% (SD 0.83%) of the injecting network needs to be tested per month. However, with a 'bring your friends' strategy, this was reduced to 3.79% (SD 0.64%) of the network (p < .001). The addition of contact tracing improved the efficiency of both strategies. In conclusion, we report that network-based approaches to testing such as 'bring a friend' initiatives and contact tracing lower the level of testing coverage required to maintain elimination.

Non-Invasive Diagnosis of Liver Fibrosis in Chronic Hepatitis C using Mathematical Modeling and Simulation

Hepatitis C is a viral infection (HCV) that causes liver inflammation, and it was found that it affects over 170 million people around the world, with Egypt having the highest rate in the world. Unfortunately, serial liver biopsies, which can be invasive, expensive, risky, and inconvenient to patients, are typically used for the diagnosis of liver fibrosis progression. This study presents the development, validation, and evaluation of a prediction mathematical model for non-invasive diagnosis of liver fibrosis in chronic HCV. The proposed model in this article uses a set of nonlinear ordinary differential equations as its core and divides the population into six groups: Susceptible, Treatment, Responder, Non-Responder, Cured, and Fibrosis. The validation approach involved the implementation of two equivalent simulation models that examine the proposed process from different perspectives. A system dynamics model was developed to understand the nonlinear behavior of the diagnosis process over time. The system dynamics model was then transformed to an equivalent agent-based model to examine the system at the individual level. The numerical analysis and simulation results indicate that the earlier the HCV treatment is implemented, the larger the group of people who will become responders, and less people will develop complications such as fibrosis.

Injecting network structure determines the most efficient strategy to achieve Hepatitis C elimination in people who inject drugs

Transmission of Hepatitis C (HCV) continues via sharing of injection equipment between people who inject drugs (PWID). Network-based modelling studies have produced conflicting results about whether random treatment is preferable to targeting treatment at PWID with multiple partners. We hypothesise that differences in the modelled injecting network structure produce this heterogeneity. The study aimed to test how changing network structure affects HCV transmission and treatment effects. We created three dynamic injecting network structures connecting 689 PWID (UK-net, AUS-net and USA-net) based on published empirical data. We modelled HCV in the networks and at 5 years compared prevalence of HCV 1) with no treatment, 2) with randomly targeted treatment and 3) with treatment targeted at PWID with the most injecting partnerships (degree-based treatment). HCV prevalence at 5 years without treatment differed significantly between the three networks (UK-net (42.8%) vs. AUS-net (38.2%), p < 0.0001 and vs. USA-net (54.0%), p < 0.0001). In the treatment scenarios UK-net and AUS-net showed a benefit of degree-based treatment with a 5-year prevalence of 1.0% vs. 9.6% p < 0.0001 and 0.15% vs. 0.44%, p < 0.0001. USA-net showed no significant difference (29.3% vs. 29.2%, p = 0.0681). Degree-based treatment was optimised with low prevalence, moderate treatment coverage conditions whereas random treatment was optimised in low treatment coverage, high prevalence conditions. In conclusion, injecting network structure determines the transmission rate of HCV and the most efficient treatment strategy. In real-world injecting network structures, the benefit of targeting HCV treatment at individuals with multiple injecting partnerships may have been underestimated.

The Geography of Opioid Use Disorder: A Data Triangulation Approach

Opioid use disorder is complex and not easily quantified among US populations because there are no dedicated reporting systems in place. We review indicators of opioid use disorder available at the state and county (human immunodeficiency virus diagnoses among people who inject drugs, hepatitis C diagnosis in people <50 years, opioid overdose death rates, and opioid prescription rate). The interpretation of the ecological results and the visualization of indicators at the local level will provide actionable insights for clinicians and public health officials seeking to mitigate the consequences of opioid use disorder at the patient and community levels.

A review of network simulation models of hepatitis C virus and HIV among people who inject drugs

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 (Erdös-Rényi, Stochastic Block, Watts-Strogatz, Barabási-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.

Per-Contact Infectivity of Hepatitis C Virus Acquisition in Association With Receptive Needle Sharing Exposures in a Prospective Cohort of Young Adult People who Inject Drugs in San Francisco, California

Background

Sharing needles and ancillary injecting equipment is a primary risk exposure for hepatitis C virus (HCV) infection among people who inject drugs (PWID); however, infectivity of these exposures is not well quantified. We aimed to estimate per-event HCV infectivity associated with receptive needle sharing (RNS) among susceptible PWID.

Methods

Participants in a prospective cohort study of young adult PWID who were anti-HCV and HCV RNA negative at baseline and attended at least 2 follow-up study visits between 2003 and 2014 were eligible. Data were selected from the first HCV-negative through the first HCV-positive visit (or last HCV-negative among those uninfected). Anti-HCV and HCV-RNA tests were used to determine infection status. A probabilistic exposure model linking observed HCV infection outcomes to self-reported exposure events was applied to estimate infectivity.

Results

Among 344 participants, a maximum likelihood estimate considering RNS yielded a pooled population per RNS event HCV probability of 0.25% (95% confidence interval [CI], 0.10%–0.43%), and 1.12% (95% CI, 0.48%–2.35%) among those who acquired any HCV infection (primary or reinfection).

Conclusions

HCV is highly infectious in association with RNS, a primary injection-related risk exposure. Our infectivity estimate among participants who acquired any HCV infection is 1.7 times higher than that estimated for HIV infection in PWID and 2.24 times higher than that estimated among health care workers exposed through needle sticks. The strengths of this study include the assessment of receptive needle sharing events, the prospective design, and relatively short recall and testing periods. These results can inform transmission models and research to prevent HCV infection.

Mathematical modeling of hepatitis c virus (HCV) prevention among people who inject drugs: A review of the literature and insights for elimination strategies

In 2016, the World Health Organization issued global elimination targets for hepatitis C virus (HCV), including an 80% reduction in HCV incidence by 2030. The vast majority of new HCV infections occur among people who inject drugs (PWID), and as such elimination strategies require particular focus on this population. As governments urgently require guidance on how to achieve elimination among PWID, mathematical modeling can provide critical information on the level and targeting of intervention are required. In this paper we review the epidemic modeling literature on HCV transmission and prevention among PWID, highlight main differences in mathematical formulation, and discuss key insights provided by these models in terms of achieving WHO elimination targets among PWID. Overall, the vast majority of modeling studies utilized a deterministic compartmental susceptible-infected-susceptible structure, with select studies utilizing individual-based network transmission models. In general, these studies found that harm reduction alone is unlikely to achieve elimination targets among PWID. However, modeling indicates elimination is achievable in a wide variety of epidemic settings with harm reduction scale-up combined with modest levels of HCV treatment for PWID. Unfortunately, current levels of testing and treatment are generally insufficient to achieve elimination in most settings, and require further scale-up. Additionally, network-based treatment strategies as well as prison-based treatment and harm reduction provision could provide important additional population benefits. Overall, epidemic modeling has and continues to play a critical role in informing HCV elimination strategies worldwide.

Acceptability of Rapid Point-of-Care Hepatitis C Tests Among People Who Inject Drugs and Utilize Syringe-Exchange Programs

People who inject drugs may benefit from point-of-care hepatitis C virus (HCV) testing offered at syringe exchanges. We sought to understand whether this population would be willing to undergo rapid HCV testing. We found that there was broad support for rapid HCV testing, especially among younger people who inject drugs with high perceived risk.

Modeling a dynamic bi-layer contact network of injection drug users and the spread of blood-borne infections

Injection drug users (IDUs) are at high risk of acquiring and spreading various blood-borne infections including human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV) and a number of sexually transmitted infections. These infections can spread among IDUs via risky sexual and needle-sharing contacts. To accurately model the spread of such contagions among IDUs, we build a bi-layer network that captures both types of risky contacts. We present methodology for inferring important model parameters, such as those governing network structure and dynamics, from readily available data sources (e.g., epidemiological surveys). Such a model can be used to evaluate the efficacy of various programs that aim to combat drug addiction and contain blood-borne diseases among IDUs. The model is especially useful for evaluating interventions that exploit the structure of the contact network. To illustrate, we instantiate a network model with data collected by a needle and syringe program in Chicago. We model sexual and needle-sharing contacts and the consequent spread of HIV and HCV. We use the model to evaluate the potential effects of a peer education (PE) program under different targeting strategies. We show that a targeted PE program would avert significantly more HIV and HCV infections than an untargeted program, highlighting the importance of reaching individuals who are centrally located in contact networks when instituting prevention programs.

Agent-Based Model Forecasts Aging of the Population of People Who Inject Drugs in Metropolitan Chicago and Changing Prevalence of Hepatitis C Infections

People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our studies highlight the importance of analyzing subpopulations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

Spatiotemporal Reconstruction of the Introduction of Hepatitis C Virus into Scotland and Its Subsequent Regional Transmission

A more comprehensive understanding of hepatitis C virus (HCV) transmission dynamics could facilitate public health initiatives to reduce the prevalence of HCV in people who inject drugs. We aimed to determine how HCV sequences entered and spread throughout Scotland and to identify transmission hot spots. A Scottish data set with embedded demographic data was created by sequencing the NS5B of 125 genotype 1a (Gt1a) samples and 166 Gt3a samples and analyzed alongside sequences from public databases. Applying Bayesian inference methods, we reconstructed the global origin and local spatiotemporal dissemination of HCV in Scotland. Scottish sequences mainly formed discrete clusters interspersed between sequences from the rest of the world; the most recent common ancestors of these clusters dated to 1942 to 1952 (Gt1a) and 1926 to 1942 (Gt3a), coincident with global diversification and distribution. Extant Scottish sequences originated in Edinburgh (Gt1a) and Glasgow (Gt3a) in the 1970s, but both genotypes spread from Glasgow to other regions. The dominant Gt1a strain differed between Edinburgh (cluster 2 [C2]), Glasgow (C3), and Aberdeen (C4), whereas significant Gt3a strain specificity occurred only in Aberdeen. Specific clusters initially formed separate transmission zones in Glasgow that subsequently overlapped, occasioning city-wide cocirculation. Transmission hot spots were detected with 45% of samples from patients residing in just 9 of Glasgow's 57 postcode districts. HCV was introduced into Scotland in the 1940s, concomitant with its worldwide dispersal likely arising from global-scale historical events. Cluster-specific transmission hubs were identified in Glasgow, the key Scottish city implicated in HCV dissemination. This fine-scale spatiotemporal reconstruction improves understanding of HCV transmission dynamics in Scotland.

IMPORTANCE

HCV is a major health burden and the leading cause of hepatocellular carcinoma. Public health needle exchange and "treatment as prevention" strategies targeting HCV are designed to reduce prevalence of the virus in people who inject drugs (PWID), potentially mitigating the future burden of HCV-associated liver disease. Understanding HCV transmission dynamics could increase the effectiveness of such public health initiatives by identifying and targeting regions playing a central role in virus dispersal. In this study, we examined HCV transmission in Scotland by analyzing the genetic relatedness of strains from PWID alongside data inferring the year individuals became infected and residential information at a geographically finer-scale resolution than in previous studies. Clusters of Scotland-specific strains were identified with regional specificity, and mapping the spread of HCV allowed the identification of key areas central to HCV transmission in Scotland. This research provides a basis for identifying HCV transmission hot spots.

Modeling hepatitis C virus transmission among people who inject drugs: Assumptions, limitations and future challenges

The discovery of highly effective hepatitis C virus (HCV) treatments has led to discussion of elimination and intensified interest in models of HCV transmission. In developed settings, HCV disproportionally affects people who inject drugs (PWID), and models are typically used to provide an evidence base for the effectiveness of interventions such as needle and syringe programs, opioid substitution therapy and more recently treating PWID with new generation therapies to achieve specified reductions in prevalence and / or incidence. This manuscript reviews deterministic compartmental S-I, deterministic compartmental S-I-S and network-based transmission models of HCV among PWID. We detail typical assumptions made when modeling injecting risk behavior, virus transmission, treatment and re-infection and how they correspond with available evidence and empirical data.

Strategies for hepatitis C testing and linkage to care for vulnerable populations: point-of-care and standard HCV testing in a mobile medical clinic

Despite new Hepatitis C virus (HCV) therapeutic advances, challenges remain for HCV testing and linking patients to care. A point-of-care (POC) HCV antibody testing strategy was compared to traditional serological testing to determine patient preferences for type of testing and linkage to treatment in an innovative mobile medical clinic (MMC). From 2012 to 2013, all 1,345 MMC clients in New Haven, CT underwent a routine health assessment, including for HCV. Based on patient preferences, clients could select between standard phlebotomy or POC HCV testing, with results available in approximately 1 week versus 20 min, respectively. Outcomes included: (1) accepting HCV testing; (2) preference for rapid POC HCV testing; and (3) linkage to HCV care. All clients with reactive test results were referred to a HCV specialty clinic. Among the 438 (32.6 %) clients accepting HCV testing, HCV prevalence was 6.2 % (N = 27), and 209 (47.7 %) preferred POC testing. Significant correlates of accepting HCV testing was lower for the "baby boomer" generation (AOR 0.67; 95 % CI 0.46-0.97) and white race (AOR 0.55; 95 % CI 0.36-0.78) and higher for having had a prior STI diagnosis (AOR 5.03; 95 % CI 1.76-14.26), prior injection drug use (AOR 2.21; 95 % CI 1.12-4.46), and being US-born (AOR 1.76; 95 % CI 1.25-2.46). Those diagnosed with HCV and preferring POC testing (N = 16) were significantly more likely than those choosing standard testing (N = 11) to be linked to HCV care within 30 days (93.8 vs. 18.2 %; p < 0.0001). HCV testing is feasible in MMCs. While patients equally preferred POC and standard HCV testing strategies, HCV-infected patients choosing POC testing were significantly more likely to be linked to HCV treatment. Important differences in risk and background were associated with type of HCV testing strategy selected. HCV testing strategies should be balanced based on costs, convenience, and ability to link to HCV treatment.

Expansion of HCV treatment access to people who have injected drugs through effective translation of research into public health policy: Scotland's experience

Seven years have elapsed since the Scottish Government launched its Hepatitis C Action Plan - a Plan to improve services to prevent transmission of infection, particularly among people who inject drugs (PWID), identify those infected and ensure those infected receive optimal treatment. The Plan was underpinned by industrial scale funding (around £100 million, in addition to the general NHS funding, will have been invested by 2015), and a web of accountable national and local multi-disciplinary multi-agency networks responsible for the planning, development and delivery of services. Initiatives ranged from the introduction of testing in specialist drug services through finger-prick blood sampling by non-clinical staff, to the setting of government targets to ensure rapid scale-up of antiviral therapy. The Plan was informed by comprehensive national monitoring systems, indicating the extent of the problem not just in terms of numbers infected, diagnosed and treated but also the more penetrative data on the number advancing to end-stage liver disease and death, and also through compelling modelling work demonstrating the potential beneficial impact of scaling-up therapy and the mounting cost of not acting. Achievements include around 50% increase in the proportion of the infected population diagnosed (38% to 55%); a sustained near two-and-a-half fold increase in the annual number of people initiated onto therapy (470 to 1050) with more pronounced increases among PWID (300 to 840) and prisoners (20 to 140); and reversing of an upward trend in the overall number of people living with chronic infection. The Action Plan has demonstrated that a Government-backed, coordinated and invested approach can transform services and rapidly improve the lives of thousands. Cited as "an impressive example of a national strategy" by the Global Commission on Drug Policy, the Scottish Plan has also provided fundamental insights of international relevance into the management of HCV among PWID.

Assessing the Long-Term Impact of Treating Hepatitis C Virus (HCV)-Infected People Who Inject Drugs in the UK and the Relationship between Treatment Uptake and Efficacy on Future Infections

Objective

The prevalence of the hepatitis C virus (HCV) remains high amongst people who inject drugs (PWID) and accounts for the majority of newly acquired infections. This study aims to quantify the value of treatment amongst PWID with more efficacious treatments and at increased uptake rates, with respect to the avoidance of future infections and subsequent long-term complications of HCV.

Methods

A dynamic HCV transmission and disease progression model was developed, incorporating acute and chronic infection and their long-term complications (decompensated cirrhosis, cancer, liver transplant and mortality), with the potential for HCV transmission to other PWID prior to successful treatment. The model was populated with prevalence and therapy data from a UK setting. Scenarios of current standard of care (SoC) treatment efficacy and uptake were compared to anticipated sustained virologic response (SVR) rates of 90–100% and increased uptake over varied horizons.

Results

SoC led to modest reductions in prevalence; >5% after 200 years. New treatments achieving 90% SVR could reduce prevalence below 5% within 60 years at current uptake rates or within 5 years if all patients are treated. Amongst 4,240 PWID, chronic HCV infections avoided as a result of increasing treatment uptake over the period 2015–2027 ranged from 20–580 and 34–912 with SoC and 90% SVR rates respectively. The reduction in downstream HCV infections due to increasing treatment uptake resulted in an approximate discounted gain of 300 life-years (from avoiding reduced life expectancy from HCV infection) and a gain of 1,700 QALYs (from avoiding the disutility of HCV infection and related complications), with a projected £5.4 million cost saving.

Conclusion

While improved SVR profiles led to reductions in modelled prevalence, increased treatment uptake was the key driver of future infections avoided. Increased treatment among PWID with new more efficacious therapies could significantly change the future dynamics, cost and health burden of HCV-related disease.

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

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 programmes 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 to underline their strengths and limits in the context of HCV infection among PWID. The final section discusses the main results of the papers.

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

With the development of new highly efficacious direct-acting antiviral (DAA) treatments for hepatitis C virus (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 article explores how using a networks-based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. 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 neighbors are treated. As treatment coverage increases, HCV prevalence at 10 years reduces for both the high- 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 1,000 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% confidence interval: 5.1-8.1).

CONCLUSION

Treat your friends is a feasible means of utilizing 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 also the community more broadly by reducing the prevalence of HCV among PWID.

Attendance at specialist hepatitis clinics and initiation of antiviral treatment among persons chronically infected with hepatitis C: examining the early impact of Scotland's Hepatitis C Action Plan

Primary goals of the Hepatitis C Action Plan for Scotland Phase II (May 2008-March 2011) were to increase, among persons chronically infected with the hepatitis C (HCV) virus, attendance at specialist outpatient clinics and initiation on antiviral therapy. We evaluated progress towards these goals by comparing the odds, across time, of (a) first clinic attendance within 12 months of HCV diagnosis (n = 9747) and (b) initiation on antiviral treatment within 12 months of first attendance (n = 5736). Record linkage between the national HCV diagnosis (1996-2009) and HCV clinical (1996-2010) databases and logistic regression analyses were conducted for both outcomes. For outcome (a), 32% and 45% in the respective pre-Phase II (before 1 May 2008) and Phase II periods attended a specialist clinic within 12 months of diagnosis; the odds of attendance within 12 months increased over time (OR = 1.05 per year, 95% CI: 1.04-1.07), but was not significantly greater for persons diagnosed with HCV in the Phase II era, compared with the pre-Phase II era (OR = 1.1, 95% CI: 0.9-1.3), after adjustment for temporal trend. For outcome (b), 13% and 28% were initiated on treatment within 12 months of their first clinic attendance in the pre-Phase II and Phase II periods, respectively. Higher odds of treatment initiation were associated with first clinic attendance in the Phase II (OR = 1.9, 95% CI: 1.5-2.4), compared with the pre-Phase II era. Results were consistent with a positive impact of the Hepatitis C Action Plan on the treatment of chronically infected individuals, but further monitoring is required to confirm a sustained effect.

Hepatitis C transmission and treatment in contact networks of people who inject drugs

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.

Modelling the prevalence of HCV amongst people who inject drugs: an investigation into the risks associated with injecting paraphernalia sharing

BACKGROUND

In order to prevent the spread of the hepatitis C virus (HCV) amongst people who inject drugs (PWID), it is imperative that any injecting risk behaviour which may contribute to the transmission of disease has its role quantified. To inform public health organisations, mathematical modelling techniques were used to explore the risk of HCV infection through the sharing of injecting paraphernalia (including filters, cookers and water).

METHODS

A mathematical model was developed for the spread of HCV based on the injecting behaviour of PWID in Scotland, with transmission occurring through the sharing of needles/syringes and other injecting paraphernalia. Numerical simulations were used to estimate the transmission probability for HCV through the sharing of injecting paraphernalia such that the modelled endemic HCV prevalence fitted with that observed amongst PWID in Scotland.

RESULTS

The transmission probability of HCV through injecting paraphernalia was modelled to be over 8 times lower than that through needles/syringes (approximately 0.19-0.30% and 2.5%, respectively), assuming transmission occurs through a combination of at least filters and cookers. In the context of reported needle/syringe and paraphernalia sharing rates in Scotland, it is estimated that 38% and 62% of HCV infections are contributed by these practices, respectively. If needle/syringe sharing rates were to be twice those reported, the contributions would be 70% and 30%, respectively.

CONCLUSION

Given that the sharing of injecting paraphernalia among PWID is common, HCV transmission through this route could be contributing to the growing healthcare burden associated with this chronic disease. Every effort should therefore be made to establish (a) the contribution that paraphernalia sharing is making to the spread of HCV, and (b) the effectiveness of services providing sterile paraphernalia in preventing infection.

Decline in incidence of HIV and hepatitis C virus infection among injecting drug users in Amsterdam; evidence for harm reduction?

AIMS

In Amsterdam, HIV prevalence has nearly halved among injecting drug users (IDU) since 1990. Hepatitis C virus (HCV) prevalence also declined; HIV and HCV incidence dropped to nearly zero. We examined possible explanations for these time trends, among which the implementation of harm reduction measures aimed at reducing the risk behaviour of IDU.

DESIGN

We used individual-based modelling of the spread of HIV and HCV. Information about demographic parameters was obtained from the Amsterdam Cohort Study (ACS) among drug users. The model included changes in inflow of new IDU and death rates over time, the latter dependent on age and time since HIV seroconversion. We considered different scenarios of risk behaviour.

SETTING

IDU in Amsterdam.

MEASUREMENTS

Simulated HIV and HCV incidence and prevalence were compared with ACS data.

FINDINGS

Assuming that harm reduction measures had led to a strong decrease in risk behaviour over time improved the model fit (squared residuals decreased by 30%). However, substantial incidence and HIV prevalence decline were already reproduced by incorporating demographic changes into the model. In particular, lowered disease spread might be a result of depletion of high-risk IDU among those at risk for disease, and a decrease in the number of high-risk individuals in the population due to HIV-related mortality.

CONCLUSIONS

Marked decreases in HIV and HCV in Amsterdam since 1990 could be due partly to harm reduction measures; however, they may also be attributable largely to changes in the IDU population. Future research aimed at quantifying the benefits of interventions should not neglect the impact of natural epidemic progression and demographic changes.

A mathematical model for HIV and hepatitis C co-infection and its assessment from a statistical perspective

The hepatitis C virus (HCV) and the human immunodeficiency virus (HIV) are a clear threat for public health, with high prevalences especially in high risk groups such as injecting drug users. People with HIV infection who are also infected by HCV suffer from a more rapid progression to HCV-related liver disease and have an increased risk for cirrhosis and liver cancer. Quantifying the impact of HIV and HCV co-infection is therefore of great importance. We propose a new joint mathematical model accounting for co-infection with the two viruses in the context of injecting drug users (IDUs). Statistical concepts and methods are used to assess the model from a statistical perspective, in order to get further insights in: (i) the comparison and selection of optional model components, (ii) the unknown values of the numerous model parameters, (iii) the parameters to which the model is most 'sensitive' and (iv) the combinations or patterns of values in the high-dimensional parameter space which are most supported by the data. Data from a longitudinal study of heroin users in Italy are used to illustrate the application of the proposed joint model and its statistical assessment. The parameters associated with contact rates (sharing syringes) and the transmission rates per syringe-sharing event are shown to play a major role.

Review of models used to predict the future numbers of individuals with severe hepatitis C disease: therapeutic and cost implications

Hepatitis C represents a major public health issue with approximately 170 million individuals infected with the virus worldwide. The greatest burden from hepatitis C virus infection will come from the long-term complications of this chronic liver disease, namely decompensated cirrhosis and hepatocellular carcinoma. If those that are responsible for the management of hepatitis C virus-infected individuals, particularly those with severe disease, are to do so effectively and efficiently, future resources need to be planned for. Accordingly, it is important that models to forecast the extent, type and cost of hepatitis C virus-related disease are developed. In this article, the authors review published forecasting studies to examine the different methods adopted and results produced.

ASSESSING THE EFFECTS OF INTRAVENOUS DRUG USE ON HEPATITIS C TRANSMISSION DYNAMICS

A mathematical model for the transmission dynamics of Hepatitis C virus (HCV) have been proposed and investigated. The model presented looks into preferential sexual contacts between intravenous drug users and non-drug users. The threshold parameters of the model are determined and stabilities analysed. Both analytic and numerical simulations show that increase in intravenous drug use in addition to sex results in an increase of HCV cases. Thus, safe sex and treatment of HCV alone are not enough to curtail the transmission of HCV. Effective control of HCV require strategies that are tailor made for intravenous drug users.

Risk of Hepatitis C virus re-infection following spontaneous viral clearance in injecting drug users: a systematic review

BACKGROUND

In order to develop new ways to prevent Hepatitis C virus (HCV) transmission amongst injecting drug users (IDUs), it is necessary to fully understand the dynamics of this disease. We reviewed the evidence on three key areas of HCV transmission in this population: the rate of acute HCV infection amongst IDUs who have spontaneously resolved a previous infection, the rate of chronic HCV infection amongst IDUs who have spontaneously resolved a previous infection, and the ability of IDUs to be re-infected with either the same or a different HCV genotype.

METHODS

A literature search of PUBMED (January 1950 to January 2009), EMBASE (January 1980 to January 2009) and PsycINFO (January 1967 to January 2009) for English language, primary research papers was undertaken to identify longitudinal studies examining HCV re-infection following spontaneous viral clearance amongst IDUs.

RESULTS

The systematic review identified three studies that satisfied the inclusion and exclusion criteria. Regarding the risk of acute HCV infection amongst IDUs, the findings from the three studies were conflicting and thus provided no compelling evidence in support of an increased or decreased risk of acute infection amongst IDUs who have spontaneously resolved compared to those previously uninfected. Limited evidence was found from two studies to support a reduced risk of subsequent chronic HCV infection in those who have previously spontaneously resolved an infection. Further, two studies found IDUs who spontaneously resolved an infection can be re-infected (with comparable proportions) with either the same or a different HCV genotype.

CONCLUSION

The limited, and sometimes contradictory, evidence published in the worldwide literature highlights the need for more longitudinal studies of IDUs to fully understand the dynamics of the disease in this population.

Diagnosis of hepatitis C virus infection in Scotland's injecting drug user population

We estimated the extent of undiagnosed hepatitis C virus (HCV) infection in injecting drug users (IDUs) in Scotland. We used record-linkage to determine HCV diagnosis status for 41 062 current/former IDUs attending drug treatment and support services between 1 April 1995 and 31 March 2006; the extent of undiagnosed HCV infection was estimated by comparing the number HCV-diagnosed to the number HCV-infected (estimated from an unlinked anonymous testing survey of 2141 current/former IDUs). In all, 9145 IDUs (22%) were diagnosed HCV antibody-positive since first attendance at drug services (diagnosis rate of 33.6/1000 person-years, 95% CI 32.7-34.4). By 31 March 2006, of the 19 632 current/former IDUs who had attended drug services and were determined to be living with HCV, an estimated 58% (95% CI 45-62) had not been HCV-diagnosed. It is essential that the deployment of resources for identifying at-risk IDUs with a view to offering antiviral therapy is guided by evidence.

Potential impact of vaccination on the hepatitis C virus epidemic in injection drug users

BACKGROUND

Hepatitis C virus (HCV) causes significant morbidity and mortality in injecting drug users (IDU) worldwide. HCV vaccine candidates have shown promise for reducing the infectivity of acute infection and averting chronic infection, yet the impact of varying levels of vaccine efficacy and vaccine delivery strategies on the HCV epidemic in IDU have not been explored.

METHODS

We utilized extensive data on injecting behavior collected in the UFO Study of young IDU in San Francisco to construct a stochastic individual-based model that reflects heterogeneous injecting risk behavior, historical HCV trends, and existing information on viral dynamics and vaccine characteristics.

RESULTS

Our modeled HCV rate closely paralleled observed HCV incidence in San Francisco, with estimated incidence of 59% per person year (ppy) early in the epidemic, and 27% ppy after risk reduction was introduced. Chronic HCV infection, the clinically relevant state of HCV infection that leads to liver disease and hepatocellular cancer, was estimated at 22% ppy (± 3%) early in the epidemic and 14% ppy (± 2%) after risk reduction was introduced. We considered several scenarios, and highlight that a vaccine with 50% to 80% efficacy targeted to high-risk or sero-negative IDU at a high vaccination rate could further reduce chronic HCV incidence in IDU to 2-7% ppy 30 years after its introduction.

CONCLUSIONS

Our results underscore the importance of further efforts to develop both HCV vaccines and optimal systems of delivery to IDU populations.

New challenges for mathematical and statistical modeling of HIV and hepatitis C virus in injecting drug users

Injecting drug users are not only driving blood-borne transmission of HIV and hepatitis C virus but also likely drive sexual transmission of HIV in large parts of the world. Mathematical and statistical modeling can provide important insights in these epidemiological processes and on the potential impact of interventions but have been little used to date. This review aims to discuss the potential areas of application of modeling in the field of viral infections in injecting drug users. After reviewing key examples of published modeling work on HIV and hepatitis C virus in injecting drug users, we discuss recent developments in the epidemiology, diagnosis, treatment and prevention of these infections. In particular, new methods for the diagnosis of early HIV infection, new antivirals for a more effective treatment of HIV, hepatitis B and hepatitis C virus infections, new concepts in design and surveillance of interventions for drug users and increasing possibilities of molecular typing of pathogens are changing the questions and decisions for public health policy makers who deal with drug-related infectious diseases. Research including mathematical modeling is needed to understand the impact of new diagnostic tools, new treatment options and combined intervention strategies on the epidemiology of viral infections in injecting drug users. Methodological advances in mathematical modeling are required to adequately approach some of the ensuing research questions. Modeling has much to offer for solving urgent policy questions, but current levels of funding in modeling research are insufficient and need to be scaled up to make better use of these possibilities.

Modelling the impact on Hepatitis C transmission of reducing syringe sharing: London case study

BACKGROUND

Hepatitis C virus (HCV) prevalence and incidence among injecting drug users (IDUs) has increased in London and rest of UK. To inform public health action, mathematical modelling is used to explore the possible impact of strategies to decrease syringe sharing.

METHODS

A mathematical model was developed to simulate HCV transmission amongst IDUs in London. Because of parameter uncertainty, numerical search algorithms were used to obtain different model fits to HCV seroprevalence data from London for 2002-03. These simulations were used to explore the likely impact of HCV prevention activities that reduce syringe sharing amongst all IDUs, IDUs that have injected for greater than one year, or IDUs with lower or higher frequencies of syringe sharing.

RESULTS

Key differences between model fits centred on how they simulated the high HCV incidence amongst new injectors, either through assuming increased HCV infectivity during acute infection, a large sub-group of high frequency syringe sharers, or increased sharing among new IDUs. Despite parameter uncertainty, the model projections suggest that modest reductions in syringe sharing frequency (<25%) will reduce the HCV seroprevalence in newly initiated IDUs (injecting less than four years) but much larger and sustained reductions (>50%) are required to reduce the HCV seroprevalence in long-term IDUs (injecting more than 8 years). Critically the model also suggested that large reductions in HCV seroprevalence will be achieved only if interventions target all IDUs and reach IDUs within 12 months of injecting.

DISCUSSION

Public health interventions must reduce syringe sharing amongst all IDUs, including newly initiated IDUs, and be sustained for many years to reduce HCV infection. More accurate data on key behavioural (sharing frequency) and biological (percentage of infected IDUs that clear infection) parameters is required to improve model projections.