The Effects of Hepatitis C Treatment Eligibility Criteria on All-cause Mortality among People with Human Immunodeficiency Virus

Background The cost of direct-acting antivirals (DAAs) for hepatitis C virus (HCV) prompted many payers to restrict treatment to patients who met non–evidence-based criteria. These restrictions have implications for survival of people with HCV, especially for people with human immunodeficiency virus (HIV)/HCV coinfection who are at high risk for liver disease progression. The goal of this work was to estimate the effects of DAA access policies on 10-year all-cause mortality among people with HIV. Methods The study population included 3056 adults with HIV in the Women’s Interagency HIV Study and Multicenter AIDS Cohort Study from 1 October 1994 through 30 September 2015. We used the parametric g-formula to estimate 10-year all-cause mortality under DAA access policies that included treating (i) all people with HCV; (ii) only people with suppressed HIV; (iii) only people with severe fibrosis; and (iv) only people with HIV suppression and severe fibrosis. Results The 10-year risk difference of treating all coinfected persons with DAAs compared with no treatment was –3.7% (95% confidence interval [CI], –9.1% to .6%). Treating only those with suppressed HIV and severe fibrosis yielded a risk difference of –1.1% (95% CI, –2.8% to .6%), with 51% (95% CI, 38%–59%) of coinfected persons receiving DAAs. Treating a random selection of 51% of coinfected persons at baseline decreased the risk by 1.9% (95% CI, –4.7% to .3%). Conclusions Restrictive DAA access policies may decrease survival compared to treating similar proportions of people with HIV/HCV coinfection with DAAs at random. These findings suggest that lives could be saved by thoughtfully revising access policies

Strong host phylogenetic and ecological effects on host competency for avian influenza in Australian wild birds

Host susceptibility to parasites is mediated by intrinsic and external factors such as genetics, ecology, age and season. While waterfowl are considered central to the reservoir community for low pathogenic avian influenza A viruses (LPAIV), the role of host phylogeny has received limited formal attention. Herein, we analysed 12 339 oropharyngeal and cloacal swabs and 10 826 serum samples collected over 11 years from wild birds in Australia. As well as describing age and species-level differences in prevalence and seroprevalence, we reveal that host phylogeny is a key driver in host range. Seasonality effects appear less pronounced than in the Northern Hemisphere, while annual variations are potentially linked to El Niño–Southern Oscillation. Our study provides a uniquely detailed insight into the evolutionary ecology of LPAIV in its avian reservoir community, defining distinctive processes on the continent of Australia and expanding our understanding of LPAIV globally.Michelle Wille, Simeon Lisovski, David Roshier, Marta Ferenczi, Bethany J. Hoye, Trent Leen, Simone Warner, Ron A. M. Fouchier, Aeron C. Hurt, Edward C. Holmes, and Marcel Klaasse

Chronic hepatitis C virus infection and subsequent HIV viral load among women with HIV initiating antiretroviral therapy

Objectives: One in four persons living with HIV is coinfected with hepatitis C virus (HCV). Biological and behavioral mechanisms may increase HIV viral load among coinfected persons. Therefore, we estimated the longitudinal effect of chronic HCV on HIV suppression after ART initiation among women with HIV (WWH). Design: HIV RNA was measured every 6 months among 441 WWH in the Women's Interagency HIV Study who initiated ART from 2000 to 2015. Methods: Log-binomial regression models were used to compare the proportion of study visits with detectable HIV RNA between women with and without chronic HCV. Robust sandwich variance estimators accounted for within-person correlation induced by repeated HIV RNA measurements during follow-up. We controlled for confounding and selection bias (because of loss to follow-up and death) using inverse probability-of-exposure-and-censoring weights. Results: One hundred and fourteen women (25%) had chronic HCV before ART initiation. Overall, the proportion of visits with detectable HIV RNA was similar among women with and without chronic HCV [relative risk (RR) 1.19 (95% CI 0.72, 1.95)]. Six months after ART initiation, the proportion of visits with detectable HIV RNA among women with chronic HCV was 1.88 (95% CI 1.41–2.51) times that among women without HCV, at 2 years, the ratio was 1.60 (95% CI 1.17–2.19), and by 6 years there was no difference (1.03; 95% CI 0.60–1.79). Conclusion: Chronic HCV may negatively impact early HIV viral response to ART. These findings reaffirm the need to test persons with HIV for HCV infection, and increase engagement in HIV care and access to HCV treatment among persons with HIV/HCV coinfection

Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub

Background AU Coronavirus Disease 2019 (COVID-19) continues to cause :significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). Methods and findings The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000–598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. Conclusions COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year

Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi-model study

Background: The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains. Methods: Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5–11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses. Findings: Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5–11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880–0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834–0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797–1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed. Interpretation: Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5–11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. Funding: Various (see acknowledgments)

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections