The impact of HCV therapy in a high HIV-HCV prevalence population: A modeling study on people who inject drugs in Ho Chi Minh City, Vietnam

Background Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) coinfection is a major global health problem especially among people who inject drugs (PWID), with significant clinical implications. Mathematical models have been used to great effect to shape HIV care, but few have been proposed for HIV/HCV. Methods We constructed a deterministic compartmental ODE model that incorporated layers for HIV disease progression, HCV disease progression and PWID demography. Antiretroviral therapy (ART) and Methadone Maintenance Therapy (MMT) scale-ups were modeled as from 2016 and projected forward 10 years. HCV treatment roll-out was modeled beginning in 2026, after a variety of MMT scale-up scenarios, and projected forward 10 years. Results Our results indicate that scale-up of ART has a major impact on HIV though not on HCV burden. MMT scale-up has an impact on incidence of both infections. HCV treatment roll-out has a measurable impact on reductions of deaths, increasing multifold the mortality reductions afforded by just ART/MMT scale-ups. Conclusion HCV treatment roll-out can have major and long-lasting effects on averting PWID deaths on top of those averted by ART/MMT scale-up. Efficient intervention scale-up of HCV alongside HIV interventions is critical in Vietnam

Increasing Skin Infections and Staphylococcus aureus Complications in Children, England, 1997-2006

During 1997-2006, general practitioner consultations for skin conditions for children <18 years of age in England increased 19%, from 128.5 to 152.9/1,000 child-years, and antistaphylococcal drug prescription rates increased 64%, from 17.8 to 29.1/1,000 child-years. During the same time period, hospital admissions for Staphylococcus aureus infections rose 49% from 53.4 to 79.3/100,000 child-years.link_to_subscribed_fulltex

Identification of patients with neuropathic pain using electronic primary care records

Background Chronic neuropathic pain is a common condition which is challenging to treat. Many people with neuropathic pain are managed in the community, so primary care records may allow more appropriate subjects to be recruited for clinical studies. Objective We investigated whether primary care records can be used to identify patients with diseases associated with neuropathic pain. Method We analysed demographic, diagnostic and prescribing data from over 100 000 primary care electronic patient records in one part of London, UK. Results The prevalence of diagnoses associated with chronic neuropathic pain was 13 per 1000, with the elderly, women and white patients experiencing the greatest burden of disease. Conclusion Computerised health records offer an excellent opportunity to improve the identification of patients for clinical research in complex conditions like chronic neuropathic pain. To make full use of data from these records, standardisation of clinical coding and consensus on diagnostic criteria are needed

Within-Host and Population-level Modeling of Human Immunodeficiency Virus and Hepatitis C Virus Dynamics

The Human Immunodeficiency Virus (HIV) pandemic is one of the largest events to impact global human health in the past 30 years. Epidemic and within-host infection dynamics are affected by co-infections, especially by Hepatitis C Virus (HCV). In this dissertation, I present mathematical modeling analyses across scales to answer the question of which strategies have the greatest impact on controlling the co-epidemics of HIV and HCV. I address this question from the perspective of public health policy and intervention (Chapters 1-2), discussing the epidemiological dynamics for HIV in Newark, NJ, a city with one of the most severe epidemics in the US. This research shows that for there to be significant impact on incidence, care-continuum interventions must be bundled; and Pre-Exposure Prophylaxis (PrEP) is most effective when targeted at specific high-risk populations. These results underscore the need for addressing the ``leaky'' care pipeline. I highlight the role of immune function in HCV clearance in a within-host model of HCV/HIV coinfection dynamics that incorporates treatment efficacy. Our analysis sheds light on the tradeoffs involved in choosing between treatment protocols, and how both duration and efficacy need to be taken into account carefully in coinfected patients, especially in light of new direct-acting antiviral treatments (DAAs) that are becoming available (Chapter 3). Focusing in on HCV mono-infection, I build on the methodology and framework discussed in Chapter 3 to explore HCV's unusual viral evolution dynamics. Testing various hypotheses including spatial-structure, latency, extra-hepatic replication and selective sweeps in a model of viral evolution can help elucidate HCV within-host dynamics, which can aid in effective treatment design (Chapter 4). Coinfection and epidemiological modeling are combined in a nested approach that I use to explore relative impacts of antiretroviral and methadone maintenance treatment scale-up, and HCV treatment rollout on HIV/HCV disease burden in Ho Chi Minh City, Vietnam (Chapter 5). These model results indicate that scale-up of antiretroviral therapy has a major impact on HIV, but a negligible impact on HCV. Methadone scale-up has an impact on both infections, and HCV treatment roll-out can increase multifold the reductions in death rates afforded by the other interventions

Modeling the effect of HIV coinfection on clearance and sustained virologic response during treatment for hepatitis C virus

Background: HIV/hepatitis C (HCV) coinfection is a major concern in global health today. Each pathogen can exacerbate the effects of the other and affect treatment outcomes. Understanding the within-host dynamics of these coinfecting pathogens is crucial, particularly in light of new, direct-acting antiviral agents (DAAs) for HCV treatment that are becoming available. Methods and findings: In this study, we construct a within-host mathematical model of HCV/HIV coinfection by adapting a previously published model of HCV monoinfection to include an immune system component in infection clearance. We explore the effect of HIV-coinfection on spontaneous HCV clearance and sustained virologic response (SVR) by building in decreased immune function with increased HIV viral load. Treatment is modeled by modifying HCV burst-size, and we use clinically-relevant parameter estimates. Our model replicates real-world patient outcomes; it outputs infected and uninfected target cell counts, and HCV viral load for varying treatment and coinfection scenarios. Increased HIV viral load and reduced CD4+ count correlate with decreased spontaneous clearance and SVR chances. Treatment efficacy/duration combinations resulting in SVR are calculated for HIV-positive and negative patients, and crucially, we replicate the new findings that highly efficacious DAAs reduce treatment differences between HIV-positive and negative patients. However, we also find that if drug efficacy decays sufficiently over treatment course, SVR differences between HIV-positive and negative patients reappear. Conclusions: Our model shows theoretical evidence of the differing outcomes of HCV infection in cases where the immune system is compromised by HIV. Understanding what controls these outcomes is especially important with the advent of efficacious but often prohibitively expensive DAAs. Using a model to predict patient response can lend insight into optimal treatment design, both in helping to identify patients who might respond well to treatment and in helping to identify treatment pathways and pitfalls

The impact of HCV therapy in a high HIV-HCV prevalence population: a modeling study on people who inject drugs in Ho Chi Minh City, Vietnam

BACKGROUND: Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) coinfection is a major global health problem especially among people who inject drugs (PWID), with significant clinical implications. Mathematical models have been used to great effect to shape HIV care, but few have been proposed for HIV/HCV. METHODS: We constructed a deterministic compartmental ODE model that incorporated layers for HIV disease progression, HCV disease progression and PWID demography. Antiretroviral therapy (ART) and Methadone Maintenance Therapy (MMT) scale-ups were modeled as from 2016 and projected forward 10 years. HCV treatment roll-out was modeled beginning in 2026, after a variety of MMT scale-up scenarios, and projected forward 10 years. RESULTS: Our results indicate that scale-up of ART has a major impact on HIV though not on HCV burden. MMT scale-up has an impact on incidence of both infections. HCV treatment roll-out has a measurable impact on reductions of deaths, increasing multifold the mortality reductions afforded by just ART/MMT scale-ups. CONCLUSION: HCV treatment roll-out can have major and long-lasting effects on averting PWID deaths on top of those averted by ART/MMT scale-up. Efficient intervention scale-up of HCV alongside HIV interventions is critical in Vietnam

Modeling the Impact of Interventions Along the HIV Continuum of Care in Newark, New Jersey

Background. The human immunodeficiency virus (HIV) epidemic in Newark, New Jersey, is among the most severe in the United States. Prevalence ranges up to 3.3% in some groups. The aim of this study is to use a mathematical model of the epidemic in Newark to assess the impact of interventions along the continuum of care, leading to virologic suppression. Methods. A model was constructed of HIV infection including specific care-continuum steps. The model was calibrated to HIV/AIDS cases in Newark among different populations over a 10-year period. Interventions applied to model fits were increasing proportions tested, linked and retained in care, linked and adherent to treatment, and increasing testing frequency, high-risk-group testing, and adherence. Impacts were assessed by measuring incidence and death reductions 10 years post-intervention. Results. The most effective interventions for reducing incidence were improving treatment adherence and increasing testing frequency and coverage. No single intervention reduced incidence in 2023 by >5%, and the most effective combination of interventions reduced incidence by approximately 16% (2%-24%). The most efficacious interventions for reducing deaths were increasing retention, linkage to care, testing coverage, and adherence. Increasing retention reduced deaths by approximately 27% (24%-29%); the most efficacious combination of interventions reduced deaths in 2023 by approximately 52% (46%-57%). Conclusions. Reducing HIV deaths in Newark over a 10-year period may be a realizable goal, but reducing incidence is less likely. Our results highlight the importance of addressing leaks across the entire continuum of care and reinforcing efforts to prevention new HIV infections with additional intervention

MMT scale-up: Incidence and deaths changes over time.

<p>Each panel in this figure shows a plot of reductions in HIV and HCV incidence, prevalence or deaths with varying MMT scale-up with scale-up percentages representing the proportion of patients newly initiated on MMT each year (See Sections 5 and 7 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177195#pone.0177195.s001" target="_blank">S1 File</a> for details).</p

ART and MMT scale-up: Reductions in deaths from disease over time.

<p>Each bar in this figure shows a plot of reductions in deaths from disease 10 years after intervention scale-up with varying ART and MMT scale-up.</p