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.

Estimating enhanced prevaccination measles transmission hotspots in the context of cross-scale dynamics.

A key question in clarifying human-environment interactions is how dynamic complexity develops across integrative scales from molecular to population and global levels. Apart from its public health importance, measles is an excellent test bed for such an analysis. Simple mechanistic models have successfully illuminated measles dynamics at the city and country levels, revealing seasonal forcing of transmission as a major driver of long-term epidemic behavior. Seasonal forcing ties closely to patterns of school aggregation at the individual and community levels, but there are few explicit estimates of school transmission due to the relative lack of epidemic data at this scale. Here, we use data from a 1904 measles outbreak in schools in Woolwich, London, coupled with a stochastic Susceptible-Infected-Recovered model to analyze measles incidence data. Our results indicate that transmission within schools and age classes is higher than previous population-level serological data would suggest. This analysis sheds quantitative light on the role of school-aged children in measles cross-scale dynamics, as we illustrate with references to the contemporary vaccination landscape.

The potential impact of coinfection on antimicrobial chemotherapy and drug resistance.

Across a range of pathogens, resistance to chemotherapy is a growing problem in both public health and animal health. Despite the ubiquity of coinfection, and its potential effects on within-host biology, the role played by coinfecting pathogens on the evolution of resistance and efficacy of antimicrobial chemotherapy is rarely considered. In this review, we provide an overview of the mechanisms of interaction of coinfecting pathogens, ranging from immune modulation and resource modulation, to drug interactions. We discuss their potential implications for the evolution of resistance, providing evidence in the rare cases where it is available. Overall, our review indicates that the impact of coinfection has the potential to be considerable, suggesting that this should be taken into account when designing antimicrobial drug treatments.

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 postintervention. 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 interventions.