Mathematical Models of Early Hepatitis B Virus Dynamics in Humanized Mice.

Analyzing the impact of the adaptive immune response during acute hepatitis B virus (HBV) infection is essential for understanding disease progression and control. Here we developed mathematical models of HBV infection which either lack terms for adaptive immune responses, or assume adaptive immune responses in the form of cytolytic immune killing, non-cytolytic immune cure, or non-cytolytic-mediated block of viral production. We validated the model that does not include immune responses against temporal serum hepatitis B DNA (sHBV) and temporal serum hepatitis B surface-antigen (HBsAg) experimental data from mice engrafted with human hepatocytes (HEP). Moreover, we validated the immune models against sHBV and HBsAg experimental data from mice engrafted with HEP and human immune system (HEP/HIS). As expected, the model that does not include adaptive immune responses matches the observed high sHBV and HBsAg concentrations in all HEP mice. By contrast, while all immune response models predict reduction in sHBV and HBsAg concentrations in HEP/HIS mice, the Akaike Information Criterion cannot discriminate between non-cytolytic cure (resulting in a class of cells refractory to reinfection) and antiviral block functions (of up to 99 % viral production 1-3 weeks following peak viral load). We can, however, reject cytolytic killing, as it can only match the sHBV and HBsAg data when we predict unrealistic levels of hepatocyte loss.

Advances and Challenges in Managing Hepatitis D Virus: Evolving Strategies.

Purpose of Review: Hepatitis D Virus (HDV), although a small defective virus, poses a substantial public health challenge due to lack of awareness, underrecognized prevalence, and limited treatment options. Universal HDV screening within hepatitis B virus (HBV) cohorts is essential to address this issue. Despite its aggressive nature, effective HDV therapies have remained elusive for over four decades. Recent Findings: Advances in understanding HDV's biology and clinical behavior offer potential therapeutic breakthroughs, fostering optimism. As insights grow, effective and targeted therapies are being developed to improve HDV management. Summary: This review delves into HDV's intricate structure and biology, highlighting formidable hurdles in antiviral development. It emphasizes the importance of widespread screening, exploring noninvasive diagnostics, and examining current and emerging innovative therapeutic strategies. Moreover, the review explores models for monitoring treatment response. In essence, this review simplifies the complexities of effectively combating HDV.

Reducing Sample Size While Improving Equity in Vaccine Clinical Trials: A Machine Learning-Based Recruitment Methodology with Application to Improving Trials of Hepatitis C Virus Vaccines in People Who Inject Drugs.

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of optimal recruitment of PWID for HCV vaccine trials could reduce sample size, follow-up costs and disparities in enrollment. We investigate trial recruitment informed by machine learning and evaluate a strategy for HCV vaccine trials termed PREDICTEE-Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. PREDICTEE utilizes a survival analysis model applied to trial candidates, considering their demographic and injection characteristics to predict the candidate's probability of HCV infection during the trial. The decision to recruit considers both the candidate's predicted incidence and demographic characteristics such as age, sex, and race. We evaluated PREDICTEE using in silico methods, in which we first generated a synthetic candidate pool and their respective HCV infection events using HepCEP, a validated agent-based simulation model of HCV transmission among PWID in metropolitan Chicago. We then compared PREDICTEE to conventional recruitment of high-risk PWID who share drugs or injection equipment in terms of sample size and recruitment equity, with the latter measured by participation-to-prevalence ratio (PPR) across age, sex, and race. Comparing conventional recruitment to PREDICTEE found a reduction in sample size from 802 (95%: 642-1010) to 278 (95%: 264-294) with PREDICTEE, while also reducing screening requirements by 30%. Simultaneously, PPR increased from 0.475 (95%: 0.356-0.568) to 0.754 (95%: 0.685-0.834). Even when targeting a dissimilar maximally balanced population in which achieving recruitment equity would be more difficult, PREDICTEE is able to reduce sample size from 802 (95%: 642-1010) to 304 (95%: 288-322) while improving PPR to 0.807 (95%: 0.792-0.821). PREDICTEE presents a promising strategy for HCV clinical trial recruitment, achieving sample size reduction while improving recruitment equity.

Modelling HDV kinetics under the entry inhibitor bulevirtide suggests the existence of two HDV-infected cell populations.

Background & Aims: Bulevirtide (BLV) was approved for the treatment of compensated chronic hepatitis D virus (HDV) infection in Europe in 2020. However, research into the effects of the entry inhibitor BLV on HDV-host dynamics is in its infancy. Methods: Eighteen patients with HDV under nucleos(t)ide analogue treatment for hepatitis B, with compensated cirrhosis and clinically significant portal hypertension, received BLV 2 mg/day. HDV RNA, alanine aminotransferase (ALT), and hepatitis B surface antigen (HBsAg) were measured at baseline, weeks 4, 8 and every 8 weeks thereafter. A mathematical model was developed to account for HDV, HBsAg and ALT dynamics during BLV treatment. Results: Median baseline HDV RNA, HBsAg, and ALT were 4.9 log IU/ml [IQR: 4.4-5.8], 3.7 log IU/ml [IQR: 3.4-3.9] and 106 U/L [IQR: 81-142], respectively. During therapy, patients fit into four main HDV kinetic patterns: monophasic (n = 2), biphasic (n = 10), flat-partial response (n = 4), and non-responder (n = 2). ALT normalization was achieved in 14 (78%) patients at a median of 8 weeks (range: 4-16). HBsAg remained at pre-treatment levels. Assuming that BLV completely (∼100%) blocks HDV entry, modeling indicated that two HDV-infected cell populations exist: fast HDV clearing (median t1/2 = 13 days) and slow HDV clearing (median t1/2 = 44 days), where the slow HDV-clearing population consisted of ∼1% of total HDV-infected cells, which could explain why most patients exhibited a non-monophasic pattern of HDV decline. Moreover, modeling explained ALT normalization without a change in HBsAg based on a non-cytolytic loss of HDV from infected cells, resulting in HDV-free HBsAg-producing cells that release ALT upon death at a substantially lower rate compared to HDV-infected cells. Conclusion: The entry inhibitor BLV provides a unique opportunity to understand HDV, HBsAg, ALT, and host dynamics. Impact and implications: Mathematical modeling of hepatitis D virus (HDV) treatment with the entry inhibitor bulevirtide (BLV) provides a novel window into the dynamics of HDV RNA and alanine aminotransferase. Kinetic data from patients treated with BLV monotherapy can be explained by hepatocyte populations with different basal HDV clearance rates and non-cytolytic clearance of infected cells. While further studies are needed to test and refine the kinetic characterization described here, this study provides a new perspective on viral dynamics, which could inform evolving treatment strategies for HDV.

Hepatitis D Virus and HBsAg Dynamics in the era of new Antiviral Treatments.

PURPOSE OF REVIEW: Hepatitis D virus (HDV) infection is the most severe form of chronic viral hepatitis, with no FDA-approved therapy. Progress in the development of effective HDV treatments is accelerating. This review highlights how mathematical modeling is improving understanding of HDV-HBsAg-host dynamics during antiviral therapy and generating insights into the efficacy and modes of action (MOA) of new antiviral agents. RECENT FINDINGS: Clinical trials with pegylated-interferon-λ, bulevertide, nucleic acid polymers, and/or lonafarnib against various steps of the HDV-life cycle have revealed new viral-kinetic patterns that were not observed under standard treatment with pegylated-interferon-α. Modeling indicated that the half-lives of circulating HDV and HBsAg are ~ 1.7 d and ~ 1.3 d, respectively, estimated the relative response of HDV and HBsAg during different antiviral therapies, and provided insights into the efficacy and MOA of drugs in development for treating HDV, which can inform response-guided therapy to individualize treatment duration. Mathematical modeling of HDV and HBsAg kinetics provides a window into the HDV virus lifecycle, HDV-HBsAg-host dynamics during antiviral therapy, and the MOA of new drugs for HDV.

Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics.

Hepatitis B virus (HBV) infection kinetics in immunodeficient mice reconstituted with humanized livers from inoculation to steady state is highly dynamic despite the absence of an adaptive immune response. To recapitulate the multiphasic viral kinetic patterns, we developed an agent-based model that includes intracellular virion production cycles reflecting the cyclic nature of each individual virus lifecycle. The model fits the data well predicting an increase in production cycles initially starting with a long production cycle of 1 virion per 20 hours that gradually reaches 1 virion per hour after approximately 3-4 days before virion production increases dramatically to reach to a steady state rate of 4 virions per hour per cell. Together, modeling suggests that it is the cyclic nature of the virus lifecycle combined with an initial slow but increasing rate of HBV production from each cell that plays a role in generating the observed multiphasic HBV kinetic patterns in humanized mice.

Herpes Simplex Virus, Human Papillomavirus, and Cervical Cancer: Overview, Relationship, and Treatment Implications.

There is a significant body of research examining the role of human papillomavirus (HPV) in the pathogenesis of cervical cancer, with a particular emphasis on the oncogenic proteins E5, E6, and E7. What is less well explored, however, is the relationship between cervical cancer and herpes simplex virus (HSV). To date, studies examining the role of HSV in cervical cancer pathogenesis have yielded mixed results. While several experiments have determined that HPV/HSV-2 coinfection results in a higher risk of developing cervical cancer, others have questioned the validity of this association. However, clarifying the potential role of HSV in the pathogenesis of cervical cancer may have significant implications for both the prevention and treatment of this disease. Should this relationship be clarified, treating and preventing HSV could open another avenue with which to prevent cervical cancer. The importance of this is highlighted by the fact that, despite the creation of an effective vaccine against HPV, cervical cancer still impacts 604,000 women and is responsible for 342,000 deaths annually. This review provides an overview of HSV and HPV infections and then delves into the possible links between HPV, HSV, and cervical cancer. It concludes with a summary of preventive measures against and recent treatment advances in cervical cancer.

Hepatitis delta virus RNA decline post-inoculation in human NTCP transgenic mice is biphasic.

Chronic infection with hepatitis B and delta viruses (HDV) is the most serious form of viral hepatitis due to more severe manifestations of an accelerated progression to liver fibrosis, cirrhosis, and hepatocellular carcinoma. We characterized early HDV kinetics post-inoculation and incorporated mathematical modeling to provide insights into host-HDV dynamics. We analyzed HDV RNA serum viremia in 192 immunocompetent (C57BL/6) and immunodeficient (NRG) mice that did or did not transgenically express the HDV receptor-human sodium taurocholate co-transporting polypeptide (hNTCP). Kinetic analysis indicates an unanticipated biphasic decline consisting of a sharp first-phase and slower second-phase decline regardless of immunocompetence. HDV decline after re-inoculation again followed a biphasic decline; however, a steeper second-phase HDV decline was observed in NRG-hNTCP mice compared to NRG mice. HDV-entry inhibitor bulevirtide administration and HDV re-inoculation indicated that viral entry and receptor saturation are not major contributors to clearance, respectively. The biphasic kinetics can be mathematically modeled by assuming the existence of a non-specific-binding compartment with a constant on/off-rate and the steeper second-phase decline by a loss of bound virus that cannot be returned as free virus to circulation. The model predicts that free HDV is cleared with a half-life of 35 minutes (standard error, SE: 6.3), binds to non-specific cells with a rate of 0.05 per hour (SE: 0.01), and returns as free virus with a rate of 0.11 per hour (SE: 0.02). Characterizing early HDV-host kinetics elucidates how quickly HDV is either cleared or bound depending on the immunological background and hNTCP presence. IMPORTANCE The persistence phase of HDV infection has been studied in some animal models; however, the early kinetics of HDV in vivo is incompletely understood. In this study, we characterize an unexpectedly HDV biphasic decline post-inoculation in immunocompetent and immunodeficient mouse models and use mathematical modeling to provide insights into HDV-host dynamics.

Rapid monophasic HBsAg decline during nucleic-acid polymer-based therapy predicts functional cure.

BACKGROUND AND AIMS: Analyzing the interplay among serum HBV DNA, HBsAg, anti-HBs, and alanine aminotransferase (ALT) during nucleic-acid polymer (NAP)-based therapy for chronic hepatitis B provides a unique opportunity to identify kinetic patterns associated with functional cure. METHODS: All participants with HBeAg-negative chronic HBV infection in the REP 401 study (NCT02565719) first received 24 weeks of tenofovir-disoproxil-fumarate (TDF) monotherapy. The early triple therapy group (n = 20) next received 48 weeks of TDF+pegylated interferon-α2a (pegIFN)+NAPs. In contrast, the delayed triple therapy group (n = 20) next received 24 weeks of TDF+pegIFN before 48 weeks of triple therapy. Three participants discontinued treatment and were excluded. Functional cure (HBsAg and HBV DNA not detectable with normal ALT) was assessed at 48 weeks post-treatment. Different kinetic phases were defined by at least a 2-fold change in slope. A single-phase decline was categorized as monophasic, and 2-phase declines were categorized as biphasic. RESULTS: Fourteen (35%) participants achieved a functional cure. HBV DNA remained below or near undetectable for all participants by the end of TDF monotherapy and during subsequent combination therapies. Three HBsAg kinetic patterns were found in both the early and delayed groups, nonresponders (n = 4 and n = 4), monophasic (n = 11 and n = 11), and biphasic (n = 4 and n = 3), respectively. All participants who achieved a functional cure had a monophasic HBsAg kinetic pattern during triple therapy. Among participants with a monophasic HBsAg decline, those who had a functional cure had a shorter median time to HBsAg loss of 21 (interquartile range=11) weeks compared with those who did not achieve functional cure [median: 27 (7) weeks] (p = 0.012). CONCLUSIONS: Functional cure was associated with a rapid monophasic HBsAg decline during NAP-based therapy. A nonmonophasic HBsAg kinetic pattern had a 100% negative predictive value (NPV) for a functional cure.

Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios.

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

Hepatitis delta virus RNA decline post inoculation in human NTCP transgenic mice is biphasic.

Background and Aims: Chronic infection with hepatitis B and hepatitis delta viruses (HDV) is considered the most serious form of viral hepatitis due to more severe manifestations of and accelerated progression to liver fibrosis, cirrhosis, and hepatocellular carcinoma. There is no FDA-approved treatment for HDV and current interferon-alpha treatment is suboptimal. We characterized early HDV kinetics post inoculation and incorporated mathematical modeling to provide insights into host-HDV dynamics. Methods: We analyzed HDV RNA serum viremia in 192 immunocompetent (C57BL/6) and immunodeficient (NRG) mice that did or did not transgenically express the HDV receptor - human sodium taurocholate co-transporting peptide (hNTCP). Results: Kinetic analysis indicates an unanticipated biphasic decline consisting of a sharp first-phase and slower second-phase decline regardless of immunocompetence. HDV decline after re-inoculation again followed a biphasic decline; however, a steeper second-phase HDV decline was observed in NRG-hNTCP mice compared to NRG mice. HDV-entry inhibitor bulevirtide administration and HDV re-inoculation indicated that viral entry and receptor saturation are not major contributors to clearance, respectively. The biphasic kinetics can be mathematically modeled by assuming the existence of a non-specific binding compartment with a constant on/off-rate and the steeper second-phase decline by a loss of bound virus that cannot be returned as free virus to circulation. The model predicts that free HDV is cleared with a half-life of 18 minutes (standard error, SE: 2.4), binds to non-specific cells with a rate of 0.06 hour -1 (SE: 0.03), and returns as free virus with a rate of 0.23 hour -1 (SE: 0.03). Conclusions: Understanding early HDV-host kinetics will inform pre-clinical therapeutic kinetic studies on how the efficacy of anti-HDV therapeutics can be affected by early kinetics of viral decline. LAY SUMMARY: The persistence phase of HDV infection has been studied in some animal models, however, the early kinetics of HDV in vivo is incompletely understood. In this study, we characterize an unexpectedly HDV biphasic decline post inoculation in immunocompetent and immunodeficient mouse models and use mathematical modeling to provide insights into HDV-host dynamics. Understanding the kinetics of viral clearance in the blood can aid pre-clinical development and testing models for anti-HDV therapeutics.

Modeling-Based Response-Guided Hepatitis C Treatment During Pregnancy and Postpartum.

Treating hepatitis C virus (HCV) in pregnancy would address HCV during prenatal care and potentially reduce the risk of vertical transmission. Response-guided therapy could provide a means to individualize and the reduce duration of HCV treatment during pregnancy. Data from a 27-year-old woman indicated that, pretreatment, HCV was stable and that it dropped in a biphasic manner during sofosbuvir/velpatasvir therapy, reaching target not detected at time of delivery-16 days post-initiation of therapy. Mathematical modeling of measured HCV at days 0, 7, and 14 predicted that cure could have been achieved after 7 weeks of sofosbuvir/velpatasvir, reducing the duration of therapy by 5 weeks.

Treatment of chronic hepatitis D with peginterferon lambda-the phase 2 LIMT-1 clinical trial.

BACKGROUND AND AIMS: HDV infection leads to the most aggressive form of human viral hepatitis for which there is no FDA-approved therapy. PEG IFN-lambda-1a (Lambda) has previously demonstrated a good tolerability profile in HBV and HCV patients compared to PEG IFN-alfa. The goal of Phase 2 LIMT-1 trial was to evaluate the safety and efficacy of Lambda monotherapy in patients with HDV. APPROACH AND RESULTS: An open-label study of Lambda 120 or 180 mcg, administered once weekly by subcutaneous injections for 48 weeks, followed by 24 weeks of posttreatment follow-up. Thirty-three patients were allocated to Lambda 180 mcg (n=14) or 120 mcg (n=19). Baseline mean values: HDV RNA 4.1 log10 IU/mL (SD±1.4); ALT 106 IU/L (35-364); and bilirubin 0.5 mg/dL (0.2-1.2). Intention-to-treat rates of virologic response to Lambda 180 mcg and 120 mcg, 24 weeks following treatment cessation were 5 of 14(36%) and 3 of 19 (16%), respectively. The posttreatment response rate of 50% was seen in low BL viral load (≤4 log10) on 180 mcg. Common on-treatment adverse events included flu-like symptoms and elevated transaminase levels. Eight (24%) cases of hyperbilirubinemia with or without liver enzyme elevation, leading to drug discontinuation, were mainly observed in the Pakistani cohort. The clinical course was uneventful, and all responded favorably to dose reduction or discontinuation. CONCLUSIONS: Treatment with Lambda in patients with chronic HDV may result in virologic response during and following treatment cessation. Clinical phase 3 development of Lambda for this rare and serious disease is ongoing.

Hepatitis B and Hepatitis D Viruses: A Comprehensive Update with an Immunological Focus.

Hepatitis B virus (HBV) and hepatitis delta virus (HDV) are highly prevalent viruses estimated to infect approximately 300 million people and 12-72 million people worldwide, respectively. HDV requires the HBV envelope to establish a successful infection. Concurrent infection with HBV and HDV can result in more severe disease outcomes than infection with HBV alone. These viruses can cause significant hepatic disease, including cirrhosis, fulminant hepatitis, and hepatocellular carcinoma, and represent a significant cause of global mortality. Therefore, a thorough understanding of these viruses and the immune response they generate is essential to enhance disease management. This review includes an overview of the HBV and HDV viruses, including life cycle, structure, natural course of infection, and histopathology. A discussion of the interplay between HDV RNA and HBV DNA during chronic infection is also included. It then discusses characteristics of the immune response with a focus on reactions to the antigenic hepatitis B surface antigen, including small, middle, and large surface antigens. This paper also reviews characteristics of the immune response to the hepatitis D antigen (including small and large antigens), the only protein expressed by hepatitis D. Lastly, we conclude with a discussion of recent therapeutic advances pertaining to these viruses.

Modeling the Interplay between HDV and HBV in Chronic HDV/HBV Patients.

Hepatitis D virus is an infectious subviral agent that can only propagate in people infected with hepatitis B virus. In this study, we modified and further developed a recent model for early hepatitis D virus and hepatitis B virus kinetics to better reproduce hepatitis D virus and hepatitis B virus kinetics measured in infected patients during anti-hepatitis D virus treatment. The analytical solutions were provided to highlight the new features of the modified model. The improved model offered significantly better prospects for modeling hepatitis D virus and hepatitis B virus interactions.

Epstein-Barr Virus (EBV) Epithelial Associated Malignancies: Exploring Pathologies and Current Treatments.

Epstein-Barr virus (EBV) is one of eight known herpesviruses with the potential to infect humans. Globally, it is estimated that between 90-95% of the population has been infected with EBV. EBV is an oncogenic virus that has been strongly linked to various epithelial malignancies such as nasopharyngeal and gastric cancer. Recent evidence suggests a link between EBV and breast cancer. Additionally, there are other, rarer cancers with weaker evidence linking them to EBV. In this review, we discuss the currently known epithelial malignancies associated with EBV. Additionally, we discuss and establish which treatments and therapies are most recommended for each cancer associated with EBV.

Advances in Parameter Estimation and Learning from Data for Mathematical Models of Hepatitis C Viral Kinetics.

Mathematical models, some of which incorporate both intracellular and extracellular hepatitis C viral kinetics, have been advanced in recent years for studying HCV-host dynamics, antivirals mode of action, and their efficacy. The standard ordinary differential equation (ODE) hepatitis C virus (HCV) kinetic model keeps track of uninfected cells, infected cells, and free virus. In multiscale models, a fourth partial differential equation (PDE) accounts for the intracellular viral RNA (vRNA) kinetics in an infected cell. The PDE multiscale model is substantially more difficult to solve compared to the standard ODE model, with governing differential equations that are stiff. In previous contributions, we developed and implemented stable and efficient numerical methods for the multiscale model for both the solution of the model equations and parameter estimation. In this contribution, we perform sensitivity analysis on model parameters to gain insight into important properties and to ensure our numerical methods can be safely used for HCV viral dynamic simulations. Furthermore, we generate in-silico patients using the multiscale models to perform machine learning from the data, which enables us to remove HCV measurements on certain days and still be able to estimate meaningful observations with a sufficiently small error.

Modeling-Based Response-Guided DAA Therapy for Chronic Hepatitis C to Identify Individuals for Shortening Treatment Duration.

Shortening duration of direct-acting antiviral therapy for chronic hepatitis C could provide cost savings, reduce medication exposure, and foster adherence and treatment completion in special populations. The current analysis indicates that measuring hepatitis C virus at baseline and on days 7 and 14 of therapy can identify patients for shortening therapy duration.

Modeling hepatitis C micro-elimination among people who inject drugs with direct-acting antivirals in metropolitan Chicago.

Hepatitis C virus (HCV) infection is a leading cause of chronic liver disease and mortality worldwide. Direct-acting antiviral (DAA) therapy leads to high cure rates. However, persons who inject drugs (PWID) are at risk for reinfection after cure and may require multiple DAA treatments to reach the World Health Organization's (WHO) goal of HCV elimination by 2030. Using an agent-based model (ABM) that accounts for the complex interplay of demographic factors, risk behaviors, social networks, and geographic location for HCV transmission among PWID, we examined the combination(s) of DAA enrollment (2.5%, 5%, 7.5%, 10%), adherence (60%, 70%, 80%, 90%) and frequency of DAA treatment courses needed to achieve the WHO's goal of reducing incident chronic infections by 90% by 2030 among a large population of PWID from Chicago, IL and surrounding suburbs. We also estimated the economic DAA costs associated with each scenario. Our results indicate that a DAA treatment rate of >7.5% per year with 90% adherence results in 75% of enrolled PWID requiring only a single DAA course; however 19% would require 2 courses, 5%, 3 courses and <2%, 4 courses, with an overall DAA cost of $325 million to achieve the WHO goal in metropolitan Chicago. We estimate a 28% increase in the overall DAA cost under low adherence (70%) compared to high adherence (90%). Our modeling results have important public health implications for HCV elimination among U.S. PWID. Using a range of feasible treatment enrollment and adherence rates, we report robust findings supporting the need to address re-exposure and reinfection among PWID to reduce HCV incidence.

People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination.

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.