Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment

Telemedicine Improves HCV Elimination among Italian People Who Use Drugs: An Innovative Therapeutic Model to Increase the Adherence to Treatment into Addiction Care Centers Evaluated before and during the COVID-19 Pandemic

Simple Summary

People who use drugs represent a category of patients to be prioritized for antiviral treatment for the purpose of hepatitis C elimination, due to their younger age and the major risk of viral transmission, acting as a virus reservoir. The treatment challenges for hepatitis C in this population are related to an ineffective linkage to care, poor adherence to treatment, and follow-up and the risk of re-infection. The COVID-19 pandemic has further exacerbated these conditions, increasing the concerns among clinicians regarding the effectiveness of their treatment. In our study, we describe a novel “patient-tailored” model-of-care for people who use drugs. The antiviral therapy was adapted to the needs of the patient and monitored remotely by a hepatological specialist, in order to decentralize the point of care within the addiction center. The study was conducted before and during the COVID-19 pandemic, clearly demonstrating the model’s high effectiveness in the linkage to care, adherence, and response to antiviral therapy.

Abstract

People who use drugs (PWUDs) are generally considered “hard-to-treat” patients, due to adherence to HCV antiviral therapy or re-infection concerns. Linkage-to-care still remains a significant gap for HCV elimination, worsened by the COVID-19 pandemic. To reduce time-to-treat and improve treatment adherence, we have developed a patient-tailored model-of-care, decentralized within the addiction center and supervised remotely by hepatologists. From January 2017 to December 2020, patients were enrolled in one addiction care center in Southern Italy, where a complete hepatologic assessment, including blood chemistry, ultrasound, and transient elastography examination, was provided. DAAs treatment has been adapted on clinical features, also performing a daily administration during an outpatient visit, and monitored remotely by specialists via telemedicine interactions. Adherence was evaluated on the accomplishment of therapy or on the percentage of attended visits. From a total of 690 PWUDs, 135 had an active HCV infection and were enrolled in the study. All patients started the treatment within 3 weeks after HCV diagnosis. Six drop-outs were recorded, obtaining a sustained virological response at week 12 (SVR12) in 98.5% of PWUDs. There were only two cases of treatment failure, one of which is re-infection. No differences were found between the SVR12 rates before and during the COVID-19 pandemic. We obtained a high SVR12 rate, providing a comprehensive assessment within the addiction care center, tailoring the drug administration with a hepatologic remote stewardship. Our therapeutic model should improve the time-to-treat and treatment adherence in PWUDs.

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.

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models offer a tool to help us understand and address this complex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings. Further, we created a database of model parameters used for model calibration, and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and Agent-Based models (16%). Over a third evaluated intervention cost-effectiveness (40%), and another third (39%) focused on treatment and harm reduction services for people with opioid use disorder (OUD). More than half (61%) discussed calibrating their models to empirical data, and 31% discussed validation approaches used in their modeling process. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation/relapse, emergency medical services, and mortality parameters. This database offers a tool that future modelers can use to identify potential model inputs and evaluate comparability of their models to prior work. Future applications of simulation models to this field should actively tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

Modeling Combination Hepatitis C Virus Treatment and Prevention Strategies in a Network of People Who Inject Drugs in the United States

BACKGROUND

Hepatitis C virus (HCV) treatment as prevention (TasP) strategies can contribute to HCV microelimination, yet complimentary interventions such as opioid agonist therapies (OAT) with methadone or buprenorphine and syringe services programs (SSPs) may improve the prevention impact. This modeling study estimates the impact of scaling up the combination of OAT and SSPs with HCV TasP in a network of people who inject drugs (PWID) in the United States.

METHODS

Using empirical data from Hartford, Connecticut, we deployed a stochastic block model to simulate an injection network of 1574 PWID. We used a susceptible-infected model for HCV and human immunodeficiency virus to evaluate the effectiveness of several HCV TasP strategies, including in combination with OAT and SSP scale-up, over 20 years.

RESULTS

At the highest HCV prevalence (75%), when OAT coverage is increased from 10% to 40%, combined with HCV treatment of 10% per year and SSP scale up to 40%, the time to achieve microelimination is reduced from 18.4 to 11.6 years. At the current HCV prevalence (60%), HCV TasP strategies as low as 10% coverage per year may achieve HCV microelimination within 10 years, with minimal impact from additional OAT scale-up. Strategies based on mass initial HCV treatment (50 per 100 PWID the first year followed by 5 per 100 PWID thereafter) were most effective in settings with HCV prevalence of 60% or lower.

CONCLUSIONS

Scale-up of HCV TasP is the most effective strategy for microelimination of HCV. OAT scale-up, however, scale-up may be synergistic toward achieving microelimination goals when HCV prevalence exceeds 60% and when HCV treatment coverage is 10 per 100 PWID per year or lower.

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.

Cost-effectiveness of Direct Antiviral Agents for Hepatitis C Virus Infection and a Combined Intervention of Syringe Access and Medication-assisted Therapy for Opioid Use Disorders in an Injection Drug Use Population

BACKGROUND

There are too many plausible permutations and scale-up scenarios of combination hepatitis C virus (HCV) interventions for exhaustive testing in experimental trials. Therefore, we used a computer simulation to project the health and economic impacts of alternative combination intervention scenarios for people who inject drugs (PWID), focusing on direct antiviral agents (DAA) and medication-assisted treatment combined with syringe access programs (MAT+).

METHODS

We performed an allocative efficiency study, using a mathematical model to simulate the progression of HCV in PWID and its related consequences. We combined 2 previously validated simulations to estimate the cost-effectiveness of intervention strategies that included a range of coverage levels. Analyses were performed from a health-sector and societal perspective, with a 15-year time horizon and a discount rate of 3%.

RESULTS

From a health-sector perspective (excluding criminal justice system-related costs), 4 potential strategies fell on the cost-efficiency frontier. At 20% coverage, DAAs had an incremental cost-effectiveness ratio (ICER) of $27 251/quality-adjusted life-year (QALY). Combinations of DAA at 20% with MAT+ at 20%, 40%, and 80% coverage had ICERs of $165 985/QALY, $325 860/QALY, and $399 189/QALY, respectively. When analyzed from a societal perspective (including criminal justice system-related costs), DAA at 20% with MAT+ at 80% was the most effective intervention and was cost saving. While DAA at 20% with MAT+ at 80% was more expensive (eg, less cost saving) than MAT+ at 80% alone without DAA, it offered a favorable value compared to MAT+ at 80% alone ($23 932/QALY).

CONCLUSIONS

When considering health-sector costs alone, DAA alone was the most cost-effective intervention. However, with criminal justice system-related costs, DAA and MAT+ implemented together became the most cost-effective intervention.

Availability, Accessibility, and Coverage of Needle and Syringe Programs in Prisons in the European Union

Needle and syringe programs (NSPs) are among the most effective interventions for controlling the transmission of infection among people who inject drugs in prisons. We evaluated the availability, accessibility, and coverage of NSPs in prisons in European Union (EU) countries. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, we systematically searched 4 databases of peer-reviewed publications (MEDLINE (PubMed), ISI Web of Science, EBSCO, and ScienceDirect) and 53 databases containing gray literature to collect data published from January 2008 to August 2018. A total of 23,969 documents (17,297 papers and 6,672 gray documents) were identified, of which 26 were included in the study. In 2018, imprisonment rates in 28 EU countries ranged between 51 per 100,000 population in Finland and 235 per 100,000 population in Lithuania. Only 4 countries were found to have NSPs in prisons: Germany (in 1 prison), Luxembourg (no coverage data were found), Romania (available in more than 50% of prisons), and Spain (in all prisons). Portugal stopped an NSP after a 6-month pilot phase. Despite the protective impact of prison-based NSPs on infection transmission, only 4 EU countries distribute sterile syringes among people who inject drugs in prisons, and coverage of the programs within these countries is very low. Since most prisoners will eventually return to the community, lack of NSPs in EU prisons not only is a threat to the health of prisoners but also endangers public health.

We know DAAs work, so now what? Simplifying models of care to enhance the hepatitis C cascade

Globally, some 71 million people are chronically infected with hepatitis C virus (HCV). Marginalized populations, particularly people who inject drugs (PWID), have low testing, linkage to care and treatment rates for HCV. Several models of care (MoCs) and service delivery interventions have the potential to improve outcomes across the HCV cascade of care, but much of the relevant research was carried out when interferon-based treatment was the standard of care. Often it was not practical to scale-up these earlier models and interventions because the clinical care needs of patients taking interferon-based regimens imposed too much of a financial and human resource burden on health systems. Despite the adoption of highly effective, all-oral direct-acting antiviral (DAA) therapies in recent years, approaches to HCV testing and treatment have evolved slowly and often remain rooted in earlier paradigms. The effectiveness of DAAs allows for simpler approaches and has encouraged countries where the drugs are widely available to set their sights on the ambitious World Health Organization (WHO) HCV elimination targets. Since a large proportion of chronically HCV-infected people are not currently accessing treatment, there is an urgent need to identify and implement existing simplified MoCs that speak to specific populations' needs. This article aims to: (i) review the evidence on MoCs for HCV; and (ii) distil the findings into recommendations for how stakeholders can simplify the path taken by chronically HCV-infected individuals from testing to cure and subsequent care and monitoring.