Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity. | Seasonal influenza (flu) viruses cause outbreaks every winter. People infected with influenza typically develop mild respiratory symptoms. But flu infections can cause serious illness in young children, older adults and people with chronic medical conditions. Infected or vaccinated individuals develop some immunity, but the viruses evolve quickly to evade these defenses in a process called antigenic drift. As the viruses change, they can re-infect previously immune people. Scientists update the flu vaccine yearly to keep up with this antigenic drift. The immune system fights flu infections by recognizing two proteins, known as antigens, on the virus’s surface, called hemagglutinin (HA) and neuraminidase (NA). However, mutations in the genes encoding these proteins can make them unrecognizable, letting the virus slip past the immune system. Scientists would like to know how these changes affect the size, severity and timing of annual influenza outbreaks. Perofsky et al. show that tracking genetic changes in HA and NA may help improve flu season predictions. The experiments compared the severity of 22 flu seasons caused by the A(H3N2) subtype in the United States with how much HA and NA had evolved since the previous year. The A(H3N2) subtype experiences the fastest rates of antigenic drift and causes more cases and deaths than other seasonal flu viruses. Genetic changes in HA and NA were a better predictor of A(H3N2) outbreak severity than the blood tests for protective antibodies that epidemiologists traditionally use to track flu evolution. However, the prevalence of another subtype of influenza A circulating in the population, called A(H1N1), was an even better predictor of how severe A(H3N2) outbreaks would be. Perofsky et al. are the first to show that genetic changes in NA contribute to the severity of flu seasons. Previous studies suggested a link between genetic changes in HA and flu season severity, and flu vaccines include the HA protein to help the body recognize new influenza strains. The results suggest that adding the NA protein to flu vaccines may improve their effectiveness. In the future, flu forecasters may want to analyze genetic changes in both NA and HA to make their outbreak predictions. Tracking how much of the A(H1N1) subtype is circulating may also be useful for predicting the severity of A(H3N2) outbreaks. | eng

BACKGROUND: The 2022 mpox outbreak disproportionately affected gay, bisexual, and other men who have sex with men (GBMSM). Mpox cases continue to be reported nationally. Vaccination is a tool to prevent the spread of and serious disease from mpox. To understand mpox vaccine uptake and hesitancy, a virtual focus group with unvaccinated GBMSM was conducted. METHODS: In November 2022, a 60-minute, virtual focus group was conducted within an artificial intelligence (AI) platform that engages participants in chat-based conversation. The AI system uses machine learning and natural language processing to analyze and provide results immediately to the moderator. Descriptive frequencies, cross-tabulations and qualitative themes were analyzed. RESULTS: Fifty-one GBMSM ages 18-55 participated, of whom 12 had attempted to get the mpox vaccine. The top barriers in accessing the vaccine included challenges in scheduling appointments (4/12), available vaccine locations (3/12), and transportation (2/12). Nine participants reported not wanting the vaccine and 22 were undecided; Of these, 15 (4/9 and 11/22, respectively) said they did not think they needed the vaccine due to low perceived risk or monogamy.. Among the undecided, after receiving health messaging about mpox, 12/22 said the messaging made them reconsider getting the vaccine. CONCLUSION: During an outbreak, many unvaccinated GBMSM who may be at increased risk for mpox either wanted the vaccine or, with appropriate health messaging, may be open to getting the vaccine. Messaging about mpox vaccine efficacy, potential side effects, and how to access the vaccine may improve vaccine uptake especially as cases continue to occur.

BACKGROUND: Assessing variant-specific COVID-19 vaccine effectiveness (VE) and severity can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial divergence from co-circulating XBB lineages. METHODS: We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. RESULTS: 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. CONCLUSIONS: Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB.

BACKGROUND: The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022 to March 2023 among adults (aged ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test positive by molecular assay) and controls (influenza test negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS: The analysis included 85 389 ED/UC ARI encounters (17.0% influenza A positive; 37.8% vaccinated overall) and 19 751 hospitalizations (9.5% influenza A positive; 52.8% vaccinated overall). VE against influenza A-associated ED/UC encounters was 44% (95% confidence interval [CI], 40%-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza A-associated hospitalizations was 35% (95% CI, 27%-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS: VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Wildlife translocation and cross-species transmission can impede control and elimination of emerging zoonotic diseases. Tracking the geographic origin of both host and virus (i.e., translocation versus local infection) may help determine the most effective response when high-risk cases of emerging pathogens are identified in wildlife. In May 2022, a coyote (Canis latrans) infected with the raccoon (Procyon lotor) rabies virus variant (RRV) was collected in Lewis County, West Virginia, USA, an area free from RRV. We applied host population genomics and RRV phylogenetic analyses to determine the most likely geographic origin of the rabid coyote. Coyote genomic analyses included animals from multiple eastern states bordering West Virginia, with the probable origin of the rabid coyote being the county of collection. The RRV phylogenetic analyses included cases detected from West Virginia and neighboring states, with most similar RRV sequences collected in a county 80 km to the northeast, within the oral rabies vaccination zone. The combined results suggest that the coyote was infected in an RRV management area and carried the RRV to Lewis County, a pattern consistent with coyote local movement ecology. Distant cross-species transmission and subsequent host movement presents a low risk for onward transmission in raccoon populations. This information helped with emergency response decision-making, thereby saving time and resources.

CONTEXT: In 2021, the Centers for Disease Control and Prevention (CDC) launched CORE, an agency-wide strategy to embed health equity as a foundational component across all areas of the agency's work. The CDC established a definition of health equity science (HES) and principles to guide the development, implementation, dissemination, and use of the HES framework to move beyond documenting inequities to investigating root causes and promoting actionable approaches to eliminate health inequities. The HES framework may be used by state and local health departments to advance health equity efforts in their jurisdictions. OBJECTIVE: Identify implementation considerations and opportunities for providing technical assistance and support to state and local public health departments in advancing HES. DESIGN: A series of implementation consultations and multi-jurisdictional facilitated discussions were held with state and local health departments and community partners in 5 states to gather feedback on the current efforts, opportunities, and support needs to advance HES at the state and local levels. The information shared during these activities was analyzed using inductive and deductive methods, validated with partners, and summarized into themes and HES implementation considerations. RESULTS: Five themes emerged regarding current efforts, opportunities, and support needed to implement HES at state and local health departments. These themes included the following criteria: (1) enhancing the existing health equity evidence base; (2) addressing interdisciplinary public health practice and data needs; (3) recognizing the value of qualitative data; (4) evaluating health equity programs and policies; and (5) including impacted communities in the full life cycle of health equity efforts. Within these themes, we identified HES implementation considerations, which may be leveraged to inform future efforts to advance HES at the state and local levels. CONCLUSION: Health equity efforts at state and local health departments may be strengthened by leveraging the HES framework and implementation considerations.

BACKGROUND: Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown. METHODS: We conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre-coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods. RESULTS: Real-time alerts did not significantly reduce the number of additional outbreak cases (intervention period versus baseline: statistical surveillance relative rate [RR]=1.41, control RR=1.81; difference-in-differences, 0.78; 95% confidence interval [CI], 0.40 to 1.52; P=0.46). Comparing only the prepandemic intervention with baseline periods, the statistical outbreak surveillance group was associated with a 64.1% reduction in additional cases (statistical surveillance RR=0.78, control RR=2.19; difference-in-differences, 0.36; 95% CI, 0.13 to 0.99). There was no similarly observed association between the pandemic versus baseline periods (statistical surveillance RR=1.56, control RR=1.66; difference-in-differences, 0.94; 95% CI, 0.46 to 1.92). CONCLUSIONS: Automated detection of hospital outbreaks using statistical surveillance did not reduce overall outbreak size in the context of an ongoing pandemic. (Funded by the Centers for Disease Control and Prevention; ClinicalTrials.gov number, NCT04053075. Support for HCA Healthcare's participation in the study was provided in kind by HCA.).

BACKGROUND: Hospital-onset bacteraemia and fungaemia (HOB) is being explored as a surveillance and quality metric. The objectives of the current study were to determine sources and preventability of HOB in hospitalised patients in the USA and to identify factors associated with perceived preventability. METHODS: We conducted a cross-sectional study of HOB events at 10 academic and three community hospitals using structured chart review. HOB was defined as a blood culture on or after hospital day 4 with growth of one or more bacterial or fungal organisms. HOB events were stratified by commensal and non-commensal organisms. Medical resident physicians, infectious disease fellows or infection preventionists reviewed charts to determine HOB source, and infectious disease physicians with training in infection prevention/hospital epidemiology rated preventability from 1 to 6 (1=definitely preventable to 6=definitely not preventable) using a structured guide. Ratings of 1-3 were collectively considered 'potentially preventable' and 4-6 'potentially not preventable'. RESULTS: Among 1789 HOB events with non-commensal organisms, gastrointestinal (including neutropenic translocation) (35%) and endovascular (32%) were the most common sources. Overall, 636/1789 (36%) non-commensal and 238/320 (74%) commensal HOB events were rated potentially preventable. In logistic regression analysis among non-commensal HOB events, events attributed to intravascular catheter-related infection, indwelling urinary catheter-related infection and surgical site infection had higher odds of being rated preventable while events with neutropenia, immunosuppression, gastrointestinal sources, polymicrobial cultures and previous positive blood culture in the same admission had lower odds of being rated preventable, compared with events without those attributes. Of 636 potentially preventable non-commensal HOB events, 47% were endovascular in origin, followed by gastrointestinal, respiratory and urinary sources; approximately 40% of those events would not be captured through existing healthcare-associated infection surveillance. DISCUSSION: Factors identified as associated with higher or lower preventability should be used to guide inclusion, exclusion and risk adjustment for an HOB-related quality metric.

BACKGROUND AIMS: The National Health and Nutrition Examination Survey (NHANES) underestimates the true prevalence of hepatitis C virus (HCV) infection. By accounting for populations inadequately represented in NHANES, we created two models to estimate the national hepatitis C prevalence among US adults during 2017-2020. APPROACH RESULTS: The first approach (NHANES+) replicated previous methodology by supplementing hepatitis C prevalence estimates among the US noninstitutionalized civilian population with a literature review and meta-analysis of hepatitis C prevalence among populations not included in the NHANES sampling frame. In the second approach (persons who inject drugs [PWID] adjustment), we developed a model to account for underrepresentation of PWID in NHANES by incorporating the estimated number of adult PWID in the United States and applying PWID-specific hepatitis C prevalence estimates. Using the NHANES+ model, we estimated HCV RNA prevalence of 1.0% (95% confidence interval [CI]: 0.5%-1.4%) among US adults in 2017-2020, corresponding to 2,463,700 (95% CI: 1,321,700-3,629,400) current HCV infections. Using the PWID adjustment model, we estimated HCV RNA prevalence of 1.6% (95% CI: 0.9%-2.2%), corresponding to 4,043,200 (95% CI: 2,401,800-5,607,100) current HCV infections. CONCLUSIONS: Despite years of an effective cure, estimated prevalence of hepatitis C in 2017-2020 remains unchanged from 2013-2016 when using comparable methodology. When accounting for increased injection drug use, estimated prevalence of hepatitis C is substantially higher than previously reported. National action is urgently needed to expand testing, increase access to treatment, and improve surveillance, especially among medically underserved populations, to support hepatitis C elimination goals.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Monkeypox virus (MPXV) is a re-emerging zoonotic poxvirus responsible for producing skin lesions in humans. Endemic in sub-Saharan Africa, the 2022 outbreak with a clade IIb strain has resulted in ongoing sustained transmission of the virus worldwide. MPXV has a relatively wide host range, with infections reported in rodent and non-human primate species. However, the susceptibility of many domestic livestock species remains unknown. Here, we report on a susceptibility/transmission study in domestic pigs that were experimentally inoculated with a 2022 MPXV clade IIb isolate or served as sentinel contact control animals. Several principal-infected and sentinel contact control pigs developed minor lesions near the lips and nose starting at day 12 through 18 days post-challenge (DPC). No virus was isolated or viral DNA was detected from the lesions; however, MPXV antigen was detected by IHC in tissue from a pustule of a principal infected pig. Viral DNA and infectious virus were detected in nasal and oral swabs up to 14 DPC, with peak titers observed at 7 DPC. Viral DNA was also detected in nasal tissues or skin collected from two principal-infected animals at 7 DPC post-mortem. Furthermore, all principal-infected and sentinel control animals enrolled in the study seroconverted. In conclusion, we provide the first evidence that domestic pigs are susceptible to experimental MPXV infection and can transmit the virus to contact animals.

In September 2022, deaths of pigs manifesting pox-like lesions caused by swinepox virus were reported in Tshuapa Province, Democratic Republic of the Congo. Two human mpox cases were found concurrently in the surrounding community. Specific diagnostics and robust sequencing are needed to characterize multiple poxviruses and prevent potential poxvirus transmission.

IMPORTANCE: On June 21, 2023, the Centers for Disease Control and Prevention recommended the first respiratory syncytial virus (RSV) vaccines for adults aged 60 years and older using shared clinical decision-making. Understanding the severity of RSV disease in adults can help guide this clinical decision-making. OBJECTIVE: To describe disease severity among adults hospitalized with RSV and compare it with the severity of COVID-19 and influenza disease by vaccination status. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, adults aged 18 years and older admitted to the hospital with acute respiratory illness and laboratory-confirmed RSV, SARS-CoV-2, or influenza infection were prospectively enrolled from 25 hospitals in 20 US states from February 1, 2022, to May 31, 2023. Clinical data during each patient's hospitalization were collected using standardized forms. Data were analyzed from August to October 2023. EXPOSURES: RSV, SARS-CoV-2, or influenza infection. MAIN OUTCOMES AND MEASURES: Using multivariable logistic regression, severity of RSV disease was compared with COVID-19 and influenza severity, by COVID-19 and influenza vaccination status, for a range of clinical outcomes, including the composite of invasive mechanical ventilation (IMV) and in-hospital death. RESULTS: Of 7998 adults (median [IQR] age, 67 [54-78] years; 4047 [50.6%] female) included, 484 (6.1%) were hospitalized with RSV, 6422 (80.3%) were hospitalized with COVID-19, and 1092 (13.7%) were hospitalized with influenza. Among patients with RSV, 58 (12.0%) experienced IMV or death, compared with 201 of 1422 unvaccinated patients with COVID-19 (14.1%) and 458 of 5000 vaccinated patients with COVID-19 (9.2%), as well as 72 of 699 unvaccinated patients with influenza (10.3%) and 20 of 393 vaccinated patients with influenza (5.1%). In adjusted analyses, the odds of IMV or in-hospital death were not significantly different among patients hospitalized with RSV and unvaccinated patients hospitalized with COVID-19 (adjusted odds ratio [aOR], 0.82; 95% CI, 0.59-1.13; P = .22) or influenza (aOR, 1.20; 95% CI, 0.82-1.76; P = .35); however, the odds of IMV or death were significantly higher among patients hospitalized with RSV compared with vaccinated patients hospitalized with COVID-19 (aOR, 1.38; 95% CI, 1.02-1.86; P = .03) or influenza disease (aOR, 2.81; 95% CI, 1.62-4.86; P < .001). CONCLUSIONS AND RELEVANCE: Among adults hospitalized in this US cohort during the 16 months before the first RSV vaccine recommendations, RSV disease was less common but similar in severity compared with COVID-19 or influenza disease among unvaccinated patients and more severe than COVID-19 or influenza disease among vaccinated patients for the most serious outcomes of IMV or death.

Many studies have examined behavioral and social drivers of COVID-19 vaccination initiation, but few have examined these drivers longitudinally. We sought to identify the drivers of COVID-19 vaccination initiation using the Behavioral and Social Drivers of Vaccination (BeSD) Framework. Participants were a nationally-representative sample of 1,563 US adults who had not received a COVID-19 vaccine by baseline. Participants took surveys online at baseline (spring 2021) and follow-up (fall 2021). The surveys assessed variables from BeSD Framework domains (i.e., thinking and feeling, social processes, and practical issues), COVID-19 vaccination initiation, and demographics at baseline and follow-up. Between baseline and follow-up, 65% of respondents reported initiating COVID-19 vaccination. Vaccination intent increased from baseline to follow-up (p < .01). Higher vaccine confidence, more positive social norms towards vaccination, and receiving vaccine recommendations at baseline predicted subsequent COVID-19 vaccine initiation (all p < .01). Among factors assessed at follow-up, social responsibility and vaccine requirements had the greatest associations with vaccine initiation (all p < .01). Baseline vaccine confidence, social norms, and vaccination recommendations were associated with subsequent vaccine initiation, all of which could be useful targets for behavioral interventions. Furthermore, interventions that highlight social responsibility to vaccinate or promote vaccination requirements could also be beneficial.

The California Department of Public Health (CDPH) reviewed 109 cases of healthcare personnel (HCP) with laboratory-confirmed mpox to understand transmission risk in healthcare settings. Overall, 90% of HCP with mpox had nonoccupational exposure risk factors. One occupationally acquired case was associated with sharps injury while unroofing a patient's lesion for diagnostic testing.

Transgender women experience discrimination in many settings, including in employment. Because employment and health insurance are intertwined in the United States, employment discrimination might be related to lower health insurance coverage and health care use, including gender-affirming care. This analysis used data from transgender women (N = 1,608) in seven urban areas in the United States collected during 2019-2020 to present the prevalence of six discrimination types (employment, housing, bathroom, businesses, health care, and abuse) and to measure the association between employment discrimination (defined as trouble getting a job or fired due to being transgender) and sociodemographic characteristics, health care access, and health care use. Log-linked Poisson regression models were conducted to estimate adjusted prevalence ratios and 95% CIs. Seven in 10 transgender women experienced at least one type of discrimination during the past 12 months. During the same period, 9.9% of transgender women were fired and 32.4% had trouble getting a job because of being transgender. Employment discrimination was associated with younger age and lower socioeconomic status. Having trouble getting a job was associated with health care access and health care use factors, including having no health insurance or having Medicaid only, having an unmet medical need because of cost, never having transgender-specific care, and having an unmet need for gender-affirming procedures. These findings suggest that employment discrimination contributes to transgender women's economic marginalization and their ability to obtain adequate health insurance coverage and achieve their transition goals. These findings might help guide efforts that protect transgender women's right to pursue their work, health, and life goals without discrimination.

In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. However, few estimates of updated vaccine effectiveness (VE) against medically attended illness are available. This analysis evaluated VE of an updated COVID-19 vaccine dose against COVID-19-associated emergency department (ED) or urgent care (UC) encounters and hospitalization among immunocompetent adults aged ≥18 years during September 2023-January 2024 using a test-negative, case-control design with data from two CDC VE networks. VE against COVID-19-associated ED/UC encounters was 51% (95% CI = 47%-54%) during the first 7-59 days after an updated dose and 39% (95% CI = 33%-45%) during the 60-119 days after an updated dose. VE estimates against COVID-19-associated hospitalization from two CDC VE networks were 52% (95% CI = 47%-57%) and 43% (95% CI = 27%-56%), with a median interval from updated dose of 42 and 47 days, respectively. Updated COVID-19 vaccine provided increased protection against COVID-19-associated ED/UC encounters and hospitalization among immunocompetent adults. These results support CDC recommendations for updated 2023-2024 COVID-19 vaccination. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccine.

In the United States, annual influenza vaccination is recommended for all persons aged ≥6 months. Using data from four vaccine effectiveness (VE) networks during the 2023-24 influenza season, interim influenza VE was estimated among patients aged ≥6 months with acute respiratory illness-associated medical encounters using a test-negative case-control study design. Among children and adolescents aged 6 months-17 years, VE against influenza-associated outpatient visits ranged from 59% to 67% and against influenza-associated hospitalization ranged from 52% to 61%. Among adults aged ≥18 years, VE against influenza-associated outpatient visits ranged from 33% to 49% and against hospitalization from 41% to 44%. VE against influenza A ranged from 46% to 59% for children and adolescents and from 27% to 46% for adults across settings. VE against influenza B ranged from 64% to 89% for pediatric patients in outpatient settings and from 60% to 78% for all adults across settings. These findings demonstrate that the 2023-24 seasonal influenza vaccine is effective at reducing the risk for medically attended influenza virus infection. CDC recommends that all persons aged ≥6 months who have not yet been vaccinated this season get vaccinated while influenza circulates locally.

Human papillomavirus (HPV) causes cervical as well as other cancers. Racial and ethnic disparities in cervical cancer incidence and mortality in the United States are well documented. HPV vaccination has been recommended in the United States since 2006 and is expected to prevent HPV-attributable cancers in all racial/ethnic groups. Quadrivalent HPV vaccine-type (HPV6/11/16/18) and nonvaccine-type cervicovaginal HPV prevalences were estimated from National Health and Nutrition Examination Surveys in 2015-2018 (vaccine era) and 2003-2006 (prevaccine era) data. Prevalence ratios comparing 2015-2018 to 2003-2006 were calculated among sexually experienced Non-Hispanic White (NHW), Non-Hispanic Black (NHB), and Mexican American (MA) females aged 14-24 years. Quadrivalent HPV vaccine-type prevalence declined 82% (CI: 60%-92%) among NHW, 86% (CI: 64%-95%) among NHB, and 100% among MA females, forecasting future reductions in cervical cancer across racial/ethnic groups.

Because of constrained personnel time, the Philadelphia Department of Public Health (Philadelphia, PA, USA) adjusted its COVID-19 contact tracing protocol in summer 2021 by prioritizing recent cases and limiting staff time per case. This action reduced required staff hours to prevent each case from 21-30 to 8-11 hours, while maintaining program effectiveness.

BACKGROUND: A 2-dose series of recombinant zoster vaccine (RZV) was 97% effective against herpes zoster (HZ) in a pivotal clinical trial. OBJECTIVE: To evaluate real-world effectiveness of RZV against HZ. DESIGN: Prospective cohort study. SETTING: Four health care systems in the Vaccine Safety Datalink. PARTICIPANTS: Persons aged 50 years or older. MEASUREMENTS: The outcome was incident HZ defined by a diagnosis with an antiviral prescription. Cox regression was used to estimate the hazard of HZ in vaccinated persons compared with unvaccinated persons, with adjustment for covariates. Vaccine effectiveness (VE) was calculated as 1 minus the adjusted hazard ratio and was estimated by time since the last RZV dose and by corticosteroid use. RESULTS: The study included nearly 2.0 million persons who contributed 7.6 million person-years of follow-up. After adjustment, VE of 1 dose was 64% and VE of 2 doses was 76%. After 1 dose only, VE was 70% during the first year, 45% during the second year, 48% during the third year, and 52% after the third year. After 2 doses, VE was 79% during the first year, 75% during the second year, and 73% during the third and fourth years. Vaccine effectiveness was 65% in persons who received corticosteroids before vaccination and 77% in those who did not. LIMITATION: Herpes zoster could not be identified as accurately in these observational data as in the previous clinical trials. CONCLUSION: Two doses of RZV were highly effective, although less effective than in the previous clinical trials. Two-dose effectiveness waned very little during the 4 years of follow-up. However, 1-dose effectiveness waned substantially after 1 year, underscoring the importance of the second dose. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

BACKGROUND: During the 2022 mpox outbreak, most cases were associated with sexual contact, and many people with mpox sought care from sexual health clinics and programs. The National Network of STD Clinical Prevention Training Centers, in partnership with the Centers for Disease Control and Prevention, conducted a survey of US sexual health clinics and programs to assess knowledge, practices, and experiences around mpox to inform a future public health response. METHODS: Between August 31 and September 13, 2022, the National Network of STD Clinical Prevention Training Centers facilitated a web-based survey. Descriptive statistics were generated in R. RESULTS: Among 168 responses by clinicians (n = 131, 78%) and program staff (n = 37, 22%), more than half (51%) reported at least somewhat significant mpox-related clinical disruptions including burdensome paperwork requirements for mpox testing (40%) and tecovirimat use (88%). Long clinic visits (51%) added additional burden, and the median mpox-related visit lasted 1 hour. Few clinicians felt comfortable with advanced pain management, and clinicians felt most uninformed about preexposure (19%) and postexposure (24%) prophylaxis. Of 89 respondents involved in vaccination, 61% reported using equity strategies; however, accounts of these strategies revealed a focus on guideline or risk factor-based screenings instead of equity activities. CONCLUSIONS: These findings highlight the substantial impact of the 2022 mpox outbreak on sexual health care in the United States. Critical gaps and barriers were identified that may inform additional mpox training and technical assistance, including challenges with testing, diagnosis, and management as well as a disconnect between programs' stated goal of equity and operationalization of strategies to achieve equity.

OBJECTIVE: To develop initial American College of Rheumatology (ACR) guidelines on the use of exercise, rehabilitation, diet, and additional interventions in conjunction with disease-modifying antirheumatic drugs (DMARDs) as part of an integrative management approach for people with rheumatoid arthritis (RA). METHODS: An interprofessional guideline development group constructed clinically relevant Population, Intervention, Comparator, and Outcome (PICO) questions. A literature review team then completed a systematic literature review and applied the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to rate the certainty of evidence. An interprofessional Voting Panel (n = 20 participants) that included 3 individuals with RA achieved consensus on the direction (for or against) and strength (strong or conditional) of recommendations. RESULTS: The Voting Panel achieved consensus on 28 recommendations for the use of integrative interventions in conjunction with DMARDs for the management of RA. Consistent engagement in exercise received a strong recommendation. Of 27 conditional recommendations, 4 pertained to exercise, 13 to rehabilitation, 3 to diet, and 7 to additional integrative interventions. These recommendations are specific to RA management, recognizing that other medical indications and general health benefits may exist for many of these interventions. CONCLUSION: This guideline provides initial ACR recommendations on integrative interventions for the management of RA to accompany DMARD treatments. The broad range of interventions included in these recommendations illustrates the importance of an interprofessional, team-based approach to RA management. The conditional nature of most recommendations requires clinicians to engage persons with RA in shared decision-making when applying these recommendations.

BACKGROUND AND AIMS: Impoverished people who inject drugs (PWID) are at the epicenter of US drug-related epidemics. Medicaid expansion is designed to reduce cost-related barriers to care by expanding Medicaid coverage to all US adults living at or below 138% of the federal poverty line. This study aimed to measure whether Medicaid expansion is (1) positively associated with the probability that participants are currently insured; (2) inversely related to the probability of reporting unmet need for medical care due to cost in the past year; and (3) positively associated with the probability that they report receiving substance use disorder (SUD) treatment in the past year, among PWID subsisting at ≤ 138% of the federal poverty line. DESIGN: A two-way fixed-effects model was used to analyze serial cross-sectional observational data. SETTING: Seventeen metro areas in 13 US states took part in the study. PARTICIPANTS: Participants were PWID who took part in any of the three waves (2012, 2015, 2018) of data gathered in the Center for Disease Control and Prevention's National HIV Behavioral Surveillance (NHBS), were aged ≤ 64 years and had incomes ≤ 138% of the federal poverty line. For SUD treatment analyses, the sample was further limited to PWID who used drugs daily, a proxy for SUD. MEASUREMENTS: State-level Medicaid expansion was measured using Kaiser Family Foundation data. Individual-level self-report measures were drawn from the NHBS surveys (e.g. health insurance coverage, unmet need for medical care because of its cost, SUD treatment program participation). FINDINGS: The sample for the insurance and unmet need analyses consisted of 19 946 impoverished PWID across 13 US states and 3 years. Approximately two-thirds were unhoused in the past year; 41.6% reported annual household incomes < $5000. In multivariable models, expansion was associated with a 19.0 [95% confidence interval (CI) = 9.0, 30.0] percentage-point increase in the probability of insurance coverage, and a 9.0 (95% CI = -15.0, -0.2) percentage-point reduction in the probability of unmet need. Expansion was unrelated to SUD treatment among PWID who used daily (n = 17 584). CONCLUSIONS: US Medicaid expansion may curb drug-related epidemics among impoverished people who inject drugs by increasing health insurance coverage and reducing unmet need for care. Persisting non-financial barriers may undermine expansion's impact upon substance use disorder treatment in this sample.

BACKGROUND: Influenza circulation during the 2022-2023 season in the United States largely returned to pre-coronavirus disease 2019 (COVID-19)-pandemic patterns and levels. Influenza A(H3N2) viruses were detected most frequently this season, predominately clade 3C.2a1b.2a, a close antigenic match to the vaccine strain. METHODS: To understand effectiveness of the 2022-2023 influenza vaccine against influenza-associated hospitalization, organ failure, and death, a multicenter sentinel surveillance network in the United States prospectively enrolled adults hospitalized with acute respiratory illness between 1 October 2022, and 28 February 2023. Using the test-negative design, vaccine effectiveness (VE) estimates against influenza-associated hospitalization, organ failures, and death were measured by comparing the odds of current-season influenza vaccination in influenza-positive case-patients and influenza-negative, SARS-CoV-2-negative control-patients. RESULTS: A total of 3707 patients, including 714 influenza cases (33% vaccinated) and 2993 influenza- and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-negative controls (49% vaccinated) were analyzed. VE against influenza-associated hospitalization was 37% (95% confidence interval [CI]: 27%-46%) and varied by age (18-64 years: 47% [30%-60%]; ≥65 years: 28% [10%-43%]), and virus (A[H3N2]: 29% [6%-46%], A[H1N1]: 47% [23%-64%]). VE against more severe influenza-associated outcomes included: 41% (29%-50%) against influenza with hypoxemia treated with supplemental oxygen; 65% (56%-72%) against influenza with respiratory, cardiovascular, or renal failure treated with organ support; and 66% (40%-81%) against influenza with respiratory failure treated with invasive mechanical ventilation. CONCLUSIONS: During an early 2022-2023 influenza season with a well-matched influenza vaccine, vaccination was associated with reduced risk of influenza-associated hospitalization and organ failure.

BACKGROUND: The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza-A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022-March 2023 among adults (age ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test-positive by molecular assay) and controls (influenza test-negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS: The analysis included 85,389 ED/UC ARI encounters (17.0% influenza-A-positive; 37.8% vaccinated overall) and 19,751 hospitalizations (9.5% influenza-A-positive; 52.8% vaccinated overall). VE against influenza-A-associated ED/UC encounters was 44% (95% confidence interval [95%CI]: 40-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza-A-associated hospitalizations was 35% (95%CI: 27-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS: VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources.

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.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

As the first scientists on the American continents, American Indian and Alaska Native people followed various methodologies in the pursuit of knowledge to understand and respond to complex environmental situations.1 Examples include data necessary to guide access to safe food and medicine as well as community roles, kinship, travel, housing, and healing for the well-being of the community. These Tribal data have been transmitted through specific practices with strict protocols such as storytelling, songs, and ceremony. Colonialism and attempts to eradicate Tribal cultures have stolen or at the very least hidden most of the original Tribal data practices in all current public health systems.2 Current methodologies fail to accurately capture data on American Indian and Alaska Native populations, resulting in inaccurate and even harmful data outcomes. Efforts to improve public health data systems should begin with the reclamation of Tribal knowledge systems and the reconstruction of these systems to fit our modern context and Tribal data sovereignty, with intentionality toward future generations.