OBJECTIVE: Providing health care during the COVID-19 pandemic has been associated with a high mental health burden for health care providers. This study examined patterns of responses and correlates of class membership across commonly assessed mental health symptoms, psychosocial functioning, and moral injury for providers in the United States in Fall 2022. METHOD: A convenience sample of 1,504 primary care physicians, pediatricians, nurse practitioners, and physician assistants who had been in practice for three or more years (M(age) = 46.1 years, SD(age) = 11.3, 58% male) completed self-report measures in an online, opt-in panel survey from September to November 2022. RESULTS: Using latent class analysis, three classes were identified: No/Low Symptoms (64.8%), High Moral Injury (19.9%), and Elevated Symptoms (15.2%). Several factors were correlated with class membership including age, sex, social support, personal risk of COVID-19, pandemic-related work stressors, proportion of COVID-19 patients seen at the height of the pandemic, and death of a patient due to COVID-19. CONCLUSIONS: This study found high levels of mental health symptoms, and problems with psychosocial functioning and moral injury in health care providers well past the pandemic's peak. The results also demonstrated the importance of considering the unique contribution of moral injury to psychosocial functional difficulties experienced by health care providers during the pandemic given their defined role as essential workers. These findings have implications for preventing and managing mental health problems and burnout among providers postpandemic as well as for future pandemics at both the organizational and individual levels. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

BACKGROUND: Injection-equipment-sharing networks play an important role in hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Direct-acting antiviral (DAA) treatments for HCV infection and interventions to prevent HCV transmission are critical components of an overall hepatitis C elimination strategy, but how they contribute to the elimination outcomes in different PWID network settings are unclear. METHODS: We developed an agent-based network model of HCV transmission through the sharing of injection equipment among PWID and parameterized and calibrated the model with rural PWID data in the United States. We modeled curative and preventive interventions at annual coverage levels of 12.5 %, 25 %, or 37.5 % (cumulative percentage of eligible individuals engaged), and two allocation approaches: random vs targeting PWID with more injection partners (hereafter 'degree-based'). We compared the impact of these intervention strategies on prevalence and incidence of HCV infections. We conducted sensitivity analysis on key parameters governing the effects of curative and preventive interventions and PWID network characteristics. RESULTS: Combining curative and preventive interventions at 37.5 % annual coverage with degree-based allocation decreased prevalence and incidence of HCV infection by 67 % and 70 % over two years, respectively. Curative interventions decreased prevalence by six to 12 times more than preventive interventions, while curative and preventive interventions had comparable effectiveness on reducing incidence. Intervention impact increased with coverage almost linearly across all intervention strategies, and degree-based allocation was always more effective than random allocation, especially for preventive interventions. Results were sensitive to parameter values defining intervention effects and network mean degree. CONCLUSION: DAA treatments are effective in reducing both prevalence and incidence of HCV infection in PWID, but preventive interventions play a significant role in reducing incidence when intervention coverage is low. Increasing coverage, including efforts in reaching individuals with the most injection partners, preventing reinfection, and improving compliance and retention in preventive services can substantially improve the outcomes. PWID network characteristics should be considered when designing hepatitis C elimination programs.

IMPORTANCE: Hepatitis C can be cured with direct-acting antivirals (DAAs), but Medicaid programs have implemented fibrosis, sobriety, and prescriber restrictions to control costs. Although restrictions are easing, understanding their association with hepatitis C treatment rates is crucial to inform policies that increase access to lifesaving treatment. OBJECTIVE: To estimate the association of jurisdictional (50 states and Washington, DC) DAA restrictions and Medicaid expansion with the number of Medicaid recipients with filled prescriptions for DAAs. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used publicly available Medicaid documents and claims data from January 1, 2014, to December 31, 2021, to compare the number of unique Medicaid recipients treated with DAAs in each jurisdiction year with Medicaid expansion status and categories of fibrosis, sobriety, and prescriber restrictions. Medicaid recipients from all 50 states and Washington, DC, during the study period were included. Multilevel Poisson regression was used to estimate the association between Medicaid expansion and DAA restrictive policies on jurisdictional Medicaid DAA prescription fills. Data were analyzed initially from August 15 to November 15, 2023, and subsequently from April 15 to May 9, 2024. EXPOSURES: Jurisdictional Medicaid expansion status and fibrosis, sobriety, and prescriber DAA restrictions. MAIN OUTCOMES AND MEASURES: Number of people treated with DAAs per 100 000 Medicaid recipients per year. RESULTS: A total of 381 373 Medicaid recipients filled DAA prescriptions during the study period (57.3% aged 45-64 years; 58.7% men; 15.2% non-Hispanic Black and 52.2% non-Hispanic White). Medicaid nonexpansion jurisdictions had fewer filled DAA prescriptions per 100 000 Medicaid recipients per year than expansion jurisdictions (38.6 vs 86.6; adjusted relative risk [ARR], 0.56 [95% CI, 0.52-0.61]). Jurisdictions with F3 to F4 (34.0 per 100 000 Medicaid recipients per year; ARR, 0.39 [95% CI, 0.37-0.66]) or F1 to F2 fibrosis restrictions (61.9 per 100 000 Medicaid recipients per year; ARR, 0.62 [95% CI, 0.59-0.66]) had lower treatment rates than jurisdictions without fibrosis restrictions (94.8 per 100 000 Medicaid recipients per year). Compared with no sobriety restrictions (113.5 per 100 000 Medicaid recipients per year), 6 to 12 months of sobriety (38.3 per 100 000 Medicaid recipients per year; ARR, 0.65 [95% CI, 0.61-0.71]) and screening and counseling requirements (84.7 per 100 000 Medicaid recipients per year; ARR, 0.87 [95% CI, 0.83-0.92]) were associated with reduced treatment rates, while 1 to 5 months of sobriety was not statistically significantly different. Compared with no prescriber restrictions (97.8 per 100 000 Medicaid recipients per year), specialist consult restrictions was associated with increased treatment (66.2 per 100 000 Medicaid recipients per year; ARR, 1.05 [95% CI, 1.00-1.10]), while specialist required restrictions were not statistically significant. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, Medicaid nonexpansion status, fibrosis, and sobriety restrictions were associated with a reduction in the number of people with Medicaid who were treated for hepatitis C. Removing DAA restrictions might facilitate treatment of more people diagnosed with hepatitis C.

Background: Many underserved populations use Emergency Department (EDs) as primary sources of care, representing an important opportunity to provide infectious disease testing and linkage to care. We explored national ED testing trends and co-testing patterns for HIV, hepatitis C, and sexually transmitted infections (STIs). Methods: We used 2010–2019 Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample data to estimate ED visit testing rates for HIV, hepatitis C, chlamydia, gonorrhea, and syphilis infections, identified by Current Procedural Terminology codes. Trends and co-testing (visit with tests for > 1 infection) patterns were analyzed by sociodemographic, hospital, and visit characteristics. Trends were evaluated as the average annual percentage change (AAPC) using the Joinpoint Regression. Results: During 2010–2019, testing events per 1000 visits (AAPCs) increased for HIV from 1.3 to 4.2 (16.3 %), hepatitis C from 0.4 to 2.2 (25.1 %), chlamydia from 9.1 to 16.0 (6.6 %), gonorrhea from 8.4 to 15.7 (7.4 %), and syphilis from 0.7 to 2.0 (12.9 %). Rate increases varied by several characteristics across infections. The largest AAPC increases were among visits by groups with lower base rate testing in 2010, including persons aged ≥ 65 years (HIV: 36.4 %), with Medicaid (HIV: 43.8 %), in the lowest income quintile (hepatitis C: 36.9 %), living in the West (syphilis: 49.4 %) and with non-emergency diagnoses (hepatitis C: 44.1 %). Co-testing increased significantly for all infections except hepatitis C. Conclusions: HIV, hepatitis C, and STI testing increased in EDs during 2010–2019; however, co-testing patterns were inconsistent. Co-testing may improve diagnosis and linkage to care, especially in areas experiencing higher rates of infection. © 2024

OBJECTIVES: Hepatitis C virus (HCV) infection is the most common bloodborne infection in the United States. We assessed trends in HCV testing, infection, and surveillance cases among US adults. METHODS: We used Quest Diagnostics data from 2013-2021 to assess trends in the numbers tested for HCV antibody and proportion of positivity for HCV antibody and HCV RNA. We also assessed National Notifiable Diseases Surveillance System 2013-2020 data for trends in the number and proportion of hepatitis C cases. We applied joinpoint regression for trends testing. RESULTS: Annual HCV antibody testing increased from 1.7 million to 4.8 million from 2013 to 2021, and the positivity proportion declined (average, 0.2% per year) from 5.5% to 3.7%. The greatest percentage-point increase in HCV antibody testing occurred in hospitals and substance use disorder treatment facilities and among addiction medicine providers. HCV RNA positivity was stable at about 60% in 2013-2015 and declined to 41.0% in 2021 (2015-2021 average, -3.2% per year). Age-specific HCV RNA positivity was highest among people aged 40-59 years during 2013-2015 and among people aged 18-39 years during 2016-2021. The number of reported hepatitis C cases (acute and chronic) declined from 179 341 in 2015 to 105 504 in 2020 (average decline, -13 177 per year). The proportion of hepatitis C cases among those aged 18-39 years increased by an average of 1.4% per year during 2013-2020; among individuals aged 40-59 years, it decreased by an average of 2.3% per year during 2013-2018. CONCLUSIONS: HCV testing increased, suggesting improved universal screening. Various data sources are valuable for monitoring elimination progress.

BACKGROUND: The reported incidence of acute hepatitis C virus (HCV) infection is increasing among persons of childbearing age in the United States. Infants born to pregnant persons with HCV infection are at risk for perinatal HCV acquisition. In 2020, the United States Preventive Services Task Force and Centers for Disease Control and Prevention recommended that all pregnant persons be screened during each pregnancy for hepatitis C. However, there are limited data on trends in hepatitis C testing during pregnancy. OBJECTIVE: We estimated hepatitis C testing rates in a large cohort of patients with Medicaid and commercial insurance who gave birth during 2015-2019 and described demographic and risk-based factors associated with testing. METHODS: Medicaid and commercial insurance claims for patients aged 15-44 years and who gave birth between 2015 and 2019 were included. Birth claims were identified using procedure and diagnosis codes for vaginal or cesarean delivery. Hepatitis C testing was defined as an insurance claim during the 42 weeks before delivery. Testing rates were calculated among patients who delivered and among the subset of patients who were continuously enrolled for 42 weeks before delivery. We also compared the timing of testing relative to delivery among patients with commercial or Medicaid insurance. Multivariable logistic regression was used to identify factors associated with testing. RESULTS: Among 1,142,770 Medicaid patients and 1,207,132 commercially insured patients, 175,223 (15.3%) and 221,436 (18.3%) were tested for hepatitis C during pregnancy, respectively. Testing rates were 89,730 (21.8%) and 187,819 (21.9%) among continuously enrolled Medicaid and commercially insured patients, respectively. Rates increased from 2015 through 2019 among Medicaid (from 20,758/108,332, 19.2% to 13,971/52,330, 26.8%) and commercially insured patients (from 38,308/211,555, 18.1% to 39,152/139,972, 28%), respectively. Among Medicaid patients, non-Hispanic Black (odds ratio 0.73, 95% CI 0.71-0.74) and Hispanic (odds ratio 0.53, 95% CI 0.51-0.56) race or ethnicity were associated with lower odds of testing. Opioid use disorder, HIV infection, and high-risk pregnancy were associated with higher odds of testing in both Medicaid and commercially insured patients. CONCLUSIONS: Hepatitis C testing during pregnancy increased from 2015 through 2019 among patients with Medicaid and commercial insurance, although tremendous opportunity for improvement remains. Interventions to increase testing among pregnant persons are needed.

Poor social and economic circumstances affect the health of individuals throughout the life cycle. The purpose of the study was to examine whether state-level and individual-level socioeconomic factors are associated with mentally or physically unhealthy days in the general U.S. population of adults. The Behavioral Risk Factor Surveillance System and the American Community Survey in 2016 were used to examine state-level social determinants of health and the number of self-reported mentally unhealthy days in the last 30 days using Zero-Inflated Negative Binomial (ZINB) regression models. Men, older individuals, minorities, persons with higher educational attainment levels, persons who were employed, persons who were married, or with a partner, and persons with one or zero chronic condition were more likely to report excessive zeros for responses to the mentally, and physically unhealthy days. The negative binomial regression results indicated that higher state-level poverty rates, higher income inequity, lower median income, and higher unemployment rates were related to the higher number of reported mentally, and physically unhealthy days. Persons with higher educational attainment, and who were employed reported lower mentally, and physically unhealthy days. The findings show significant relationships between socioeconomic contexts and general health status. Health planners and policymakers may use the results to allocate resources and guide public policies and programs. © The Author(s) 2023.

Approximately 2.4 million adults were estimated to have hepatitis C virus (HCV) infection in the United States during 2013-2016 (1). Untreated, hepatitis C can lead to advanced liver disease, liver cancer, and death (2). The Viral Hepatitis National Strategic Plan for the United States calls for ≥80% of persons with hepatitis C to achieve viral clearance by 2030 (3). Characterizing the steps that follow a person's progression from testing to viral clearance and subsequent infection (clearance cascade) is critical for monitoring progress toward national elimination goals. Following CDC guidance (4), a simplified national laboratory results-based HCV five-step clearance cascade was developed using longitudinal data from a large national commercial laboratory throughout the decade since highly effective hepatitis C treatments became available. During January 1, 2013-December 31, 2021, a total of 1,719,493 persons were identified as ever having been infected with HCV. During January 1, 2013-December 31, 2022, 88% of those ever infected were classified as having received viral testing; among those who received viral testing, 69% were classified as having initial infection; among those with initial infection, 34% were classified as cured or cleared (treatment-induced or spontaneous); and among those persons, 7% were categorized as having persistent infection or reinfection. Among the 1.0 million persons with evidence of initial infection, approximately one third had evidence of viral clearance (cured or cleared). This simplified national HCV clearance cascade identifies substantial gaps in cure nearly a decade since highly effective direct-acting antiviral (DAA) agents became available and will facilitate the process of monitoring progress toward national elimination goals. It is essential that increased access to diagnosis, treatment, and prevention services for persons with hepatitis C be addressed to prevent progression of disease and ongoing transmission and achieve national hepatitis C elimination goals.

During 2013-2016, an estimated 2.4 million people in the United States were living with hepatitis C virus (HCV) infection.1 With the availability of curative treatment since 2013, the United States has established a goal of eliminating hepatitis C as a public health threat by 2030.2 HCV clearance cascades (hereinafter, HCV cascades) are an important tool to track progress toward elimination, across jurisdictions and at a national level, and to identify disparities in access to testing and treatment. HCV cascades are a sequence of steps that follow progression from testing and treatment to clearance and subsequent infection and can be used to inform public health interventions to facilitate progression along the cascade. | Many HCV cascades are developed in a single or regional health system in which both treatment and laboratory data are available. However, an important goal for health departments is to develop population-level cascades that capture data on HCV infection status for all people living in a jurisdiction who might seek care across various health settings. In the absence of treatment information, which is not always readily available in health department surveillance systems, HCV laboratory results can be used to develop HCV cascades. Here, we describe a standardized, laboratory result–based HCV cascade developed by the Centers for Disease Control and Prevention (CDC) as a guide for health departments (Figure 1, Supplemental Material).

INTRODUCTION: Over 2 million adults in the United States have hepatitis C virus (HCV) infection, and it contributes to approximately 14,000 deaths a year. Eight to 12 weeks of highly effective direct-acting antiviral (DAA) treatment, which can cure ≥95% of cases, is recommended for persons with hepatitis C. METHODS: Data from HealthVerity, an administrative claims and encounters database, were used to construct a cohort of adults aged 18-69 years with HCV infection diagnosed during January 30, 2019-October 31, 2020, who were continuously enrolled in insurance for ≥60 days before and ≥360 days after diagnosis (47,687). Multivariable logistic regression was used to assess the association between initiation of DAA treatment and sex, age, race, payor, and Medicaid restriction status; adjusted odds ratios (aORs) and 95% CIs were calculated. RESULTS: The prevalence of DAA treatment initiation within 360 days of the first positive HCV RNA test result among Medicaid, Medicare, and private insurance recipients was 23%, 28%, and 35%, respectively; among those treated, 75%, 77%, and 84%, respectively, initiated treatment within 180 days of diagnosis. Adjusted odds of treatment initiation were lower among those with Medicaid (aOR = 0.54; 95% CI = 0.51-0.57) and Medicare (aOR = 0.62; 95% CI = 0.56-0.68) than among those with private insurance. After adjusting for insurance type, treatment initiation was lowest among adults aged 18-29 and 30-39 years with Medicaid or private insurance, compared with those aged 50-59 years. Among Medicaid recipients, lower odds of treatment initiation were found among persons in states with Medicaid treatment restrictions (aOR = 0.77; 95% CI = 0.74-0.81) than among those in states without restrictions, and among persons whose race was coded as Black or African American (Black) (aOR = 0.93; 95% CI = 0.88-0.99) or other race (aOR = 0.73; 95% CI = 0.62-0.88) than those whose race was coded as White. CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Few insured persons with diagnosed hepatitis C receive timely DAA treatment, and disparities in treatment exist. Unrestricted access to timely DAA treatment is critical to reducing viral hepatitis-related mortality, disparities, and transmission. Treatment saves lives, prevents transmission, and is cost saving.

The study evaluates the effect of the 2020 Centers for Disease Control and Prevention and U.S. Preventive Services Task Force recommendations on hepatitis C virus (HCV) screening among pregnant persons nationally and by health insurance type. The study included 5,048,428 pregnant persons aged 15-44 years with either Medicaid or commercial health insurance who had obstetric panel testing performed by Quest Diagnostics, January 2011-June 2021. Antibody screening for HCV infection increased before and accelerated after the updated recommendations in early 2020. Disparities in HCV testing by health insurance status were substantial over the entire study period. Despite substantial progress in the proportion of pregnant persons screened for HCV infection, current testing rates fall short of universal recommendations.

PURPOSE: Metamodels are simplified approximations of more complex models that can be used as surrogates for the original models. Challenges in using metamodels for policy analysis arise when there are multiple correlated outputs of interest. We develop a framework for metamodeling with policy simulations to accommodate multivariate outcomes. METHODS: We combine 2 algorithm adaptation methods-multitarget stacking and regression chain with maximum correlation-with different base learners including linear regression (LR), elastic net (EE) with second-order terms, Gaussian process regression (GPR), random forests (RFs), and neural networks. We optimize integrated models using variable selection and hyperparameter tuning. We compare the accuracy, efficiency, and interpretability of different approaches. As an example application, we develop metamodels to emulate a microsimulation model of testing and treatment strategies for hepatitis C in correctional settings. RESULTS: Output variables from the simulation model were correlated (average ρ = 0.58). Without multioutput algorithm adaptation methods, in-sample fit (measured by R(2)) ranged from 0.881 for LR to 0.987 for GPR. The multioutput algorithm adaptation method increased R(2) by an average 0.002 across base learners. Variable selection and hyperparameter tuning increased R(2) by 0.009. Simpler models such as LR, EE, and RF required minimal training and prediction time. LR and EE had advantages in model interpretability, and we considered methods for improving the interpretability of other models. CONCLUSIONS: In our example application, the choice of base learner had the largest impact on R(2); multioutput algorithm adaptation and variable selection and hyperparameter tuning had a modest impact. Although advantages and disadvantages of specific learning algorithms may vary across different modeling applications, our framework for metamodeling in policy analyses with multivariate outcomes has broad applicability to decision analysis in health and medicine.

BACKGROUND: Hepatitis C virus (HCV) infection has been increasing among people who inject drugs (PWID), younger than 30 years, and living in rural or suburban areas. We examined injection-related behaviors of young PWID to determine factors associated with HCV infection. METHODS: From September 2013-May 2015, respondent-driven and snowball sampling were used in 3 suburban areas of Wisconsin to recruit PWID 18-29 years who reported injection drug use in the previous 12 months. Participants were tested for HCV antibody (anti-HCV) and reported injection-related behaviors/practices via self-administered computer-based survey. We calculated anti-HCV prevalence and assessed associated factors using multivariable logistic regression. RESULTS: Forty-two percent (117/280) of participants were male, 83% (231/280) were white, and median age was 23 years. Overall HCV prevalence was 33%, but HCV prevalence among males was 39%. Adjusting for age, sex, race/ethnicity, education, relationship status, insurance status and income, anti-HCV positivity was associated with higher injection frequency (> 100 times in the past six months) (aOR = 3.07; 95% Confidence Interval (95% CI): 1.72-5.45), ever shared syringes (aOR = 5.15; 95% CI: 2.52-10.51), past week/last use receptive rinse water sharing (aOR = 1.88; 95% CI: 1.06-3.33), past week/last use receptive filter sharing (aOR = 3.25; 95% CI: 1.61-6.54), reusing syringes (aOR = 1.91, 95% CI: 1.08-3.37), history of overdose (aOR = 8.82; 95% CI: 2.26-3.95), and having ever injected another PWID (aOR = 8.82; 95%CI 3.94-19.76). DISCUSSION: Anti-HCV positivity is associated with high-risk injection practices. Young PWID would benefit from access to evidence-based interventions that reduce their risk of infection, link those infected to HCV treatment, and provide education to reduce further transmission.

Recent studies indicate an increase in the percentage of adults who reported clinically relevant symptoms of anxiety and depression during the COVID-19 pandemic (1-3). For example, based on U.S. Census Bureau Household Pulse Survey (HPS) data, CDC reported significant increases in symptoms of anxiety and depressive disorders among adults aged ≥18 years during August 19, 2020-February 1, 2021, with the largest increases among adults aged 18-29 years and among those with less than a high school education (1). To assess more recent national trends, as well as state-specific trends, CDC used HPS data (4) to assess trends in reported anxiety and depression among U.S. adults in all 50 states and the District of Columbia (DC) during August 19, 2020-June 7, 2021 (1). Nationally, the average anxiety severity score increased 13% from August 19-31, 2020, to December 9-21, 2020 (average percent change [APC] per survey wave = 1.5%) and then decreased 26.8% from December 9-21, 2020, to May 26-June 7, 2021 (APC = -3.1%). The average depression severity score increased 14.8% from August 19-31, 2020, to December 9-21, 2020 (APC = 1.7%) and then decreased 24.8% from December 9-21, 2020, to May 26-June 7, 2021 (APC = -2.8%). State-specific trends were generally similar to national trends, with both anxiety and depression scores for most states peaking during the December 9-21, 2020, or January 6-18, 2021, survey waves. Across the entire study period, the frequency of anxiety and depression symptoms was positively correlated with the average number of daily COVID-19 cases. Mental health services and resources, including telehealth behavioral services, are critical during the COVID-19 pandemic.

OBJECTIVE: Approximately 2.4 million people in the United States are living with hepatitis C virus (HCV) infection. The objective of our study was to describe demographic and socioeconomic characteristics, liver disease-related risk factors, and modifiable health behaviors associated with self-reported testing for HCV infection among adults. METHODS: Using data on adult respondents aged ≥18 from the 2013-2017 National Health Interview Survey, we summarized descriptive data on sociodemographic characteristics and liver disease-related risk factors and stratified data by educational attainment. We used weighted logistic regression to examine predictors of HCV testing. RESULTS: During the study period, 11.7% (95% CI, 11.5%-12.0%) of adults reported ever being tested for HCV infection. Testing was higher in 2017 than in 2013 (adjusted odds ratio [aOR] = 1.27; 95% CI, 1.18-1.36). Adults with ≥some college were significantly more likely to report being tested (aOR = 1.60; 95% CI, 1.52-1.69) than adults with ≤high school education. Among adults with ≤high school education (but not adults with ≥some college), those who did not have health insurance were less likely than those with private health insurance (aOR = 0.78; 95% CI, 0.68-0.89) to get tested, and non-US-born adults were less likely than US-born adults to get tested (aOR = 0.77; 95% CI, 0.68-0.87). CONCLUSIONS: Rates of self-reported HCV testing increased from 2013 to 2017, but testing rates remained low. Demographic characteristics, health behaviors, and liver disease-related risk factors may affect HCV testing rates among adults. HCV testing must increase to achieve hepatitis C elimination targets.

INTRODUCTION: The proportion of individuals infected with hepatitis C virus that receive direct-acting antiviral treatment is unclear. METHODS: The proportion of commercially or Medicaid-insured patients receiving hepatitis C virus treatment was estimated using administrative claims data obtained from MarketScan and Multi-State Medicaid obtained on January 6, 2020. Validated algorithms derived from standardized procedures and International Classification of Diseases diagnosis codes were used to identify enrollees with chronic hepatitis C; analysis (performed November 30, 2020) was restricted to adults continuously enrolled with prescription drug coverage for >6 months before and after their index hepatitis C viral load test claim date from January 2014 through December 2018. Prescription drug claims using National Drug Codes were used for hepatitis C virus drugs. The proportion of treated patients by demographic and clinical characteristics was described, and associations with treatment were modeled using multivariable-adjusted hazard ratios and 95% CIs by insurance status. RESULTS: Of patients with chronic hepatitis C, 12,090 of 17,562 (69%) with commercial insurance and 8,112 of 27,328 (30%) with Medicaid were treated. Commercially insured patients with opioid use disorder (hazard ratio=0.78, 95% CI=0.72, 0.85), alcohol use disorder (hazard ratio=0.85, 95% CI=0.79, 0.91), severe mental illness (hazard ratio=0.92, 95% CI=0.87, 0.98), chronic kidney disease (hazard ratio=0.75, 95% CI=0.69, 0.82), or HIV infection (hazard ratio=0.74, 95% CI=0.66, 0.82) were less likely to be treated. Medicaid patients with opioid (hazard ratio=0.64, 95% CI=0.61, 0.68) or alcohol use disorders (hazard ratio=0.83, 95% CI=0.79, 0.88) were less likely to be treated. CONCLUSIONS: Hepatitis C virus treatment gaps were identified using administrative claims data among patients with commercial and Medicaid insurance.

INTRODUCTION: The COVID-19 pandemic has disrupted healthcare services, reducing opportunities to conduct routine hepatitis C virus antibody screening, clinical care, and treatment. Therefore, people living with undiagnosed hepatitis C virus during the pandemic may later become identified at more advanced stages of the disease, leading to higher morbidity and mortality rates. Further, unidentified hepatitis C virus-infected individuals may continue to unknowingly transmit the virus to others. METHODS: To assess the impact of the COVID-19 pandemic, data were evaluated from a large national reference clinical laboratory and from national estimates of dispensed prescriptions for hepatitis C virus treatment. Investigators estimated the average number of hepatitis C virus antibody tests, hepatitis C virus antibody-positive test results, and hepatitis C virus RNA-positive test results by month in January-July for 2018 and 2019, compared with the same months in 2020. To assess the impact of hepatitis C virus treatment, dispensed hepatitis C virus direct-acting antiretroviral medications were examined for the same time periods. Statistical analyses of trends were performed using negative binomial models. RESULTS: Compared with the 2018 and 2019 months, hepatitis C virus antibody testing volume decreased 59% during April 2020 and rebounded to a 6% reduction in July 2020. The number of hepatitis C virus RNA-positive results fell by 62% in March 2020 and remained 39% below the baseline by July 2020. For hepatitis C virus treatment, prescriptions decreased 43% in May, 37% in June, and 38% in July relative to the corresponding months in 2018 and 2019. CONCLUSIONS: During the COVID-19 pandemic, continued public health messaging, interventions and outreach programs to restore hepatitis C virus testing and treatment to prepandemic levels, and maintenance of public health efforts to eliminate hepatitis C infections remain important.

OBJECTIVE: To investigate associations between adverse changes in employment status and physical and mental health among US adults (more than or equal to 18 years) during the COVID-19 pandemic. METHODS: Data from participants (N = 2565) of a national Internet panel (June 2020) were assessed using path analyses to test associations between changes in self-reported employment status and hours worked and physical and mental health outcomes. RESULTS: Respondents who lost a job after March 1, 2020 (vs those who did not) reported more than twice the number of mentally unhealthy days. Women and those lacking social support had significantly worse physical and mental health outcomes. Participants in the lowest, pre-pandemic household income groups reported experiencing worse mental health. CONCLUSIONS: Results demonstrate the importance of providing social and economic support services to US adults experiencing poor mental and physical health during the COVID-19 pandemic.

BACKGROUND: Investigating antecedents of behaviors, such as wearing face coverings, is critical for developing strategies to prevent SARS-CoV-2 transmission. PURPOSE: The purpose of this study was to determine associations between theory-based behavioral predictors of intention to wear a face covering and actual wearing of a face covering in public. METHODS: Data from a cross-sectional panel survey of U.S. adults conducted in May and June 2020 (N = 1,004) were used to test a theory-based behavioral path model. We (a) examined predictors of intention to wear a face covering, (b) reported use of cloth face coverings, and (c) reported use of other face masks (e.g., a surgical mask or N95 respirator) in public. RESULTS: We found that being female, perceived importance of others wanting the respondent to wear a face covering, confidence to wear a face covering, and perceived importance of personal face covering use was positively associated with intention to wear a face covering in public. Intention to wear a face covering was positively associated with self-reported wearing of a cloth face covering if other people were observed wearing cloth face coverings in public at least "rarely" (aOR = 1.43), with stronger associations if they reported "sometimes" (aOR = 1.83), "often" (aOR = 2.32), or "always" (aOR = 2.96). For other types of face masks, a positive association between intention and behavior was only present when observing others wearing face masks "often" (aOR = 1.25) or "always" (aOR = 1.48). CONCLUSIONS: Intention to wear face coverings and observing other people wearing them are important behavioral predictors of adherence to the CDC recommendation to wear face coverings in public.

OBJECTIVES: Monitoring care and treatment for persons with chronic hepatitis B (CHB) is essential for demonstrating progress in achieving national elimination goals. We sought to evaluate insurance claims data as a source for monitoring progression along the CHB care cascade. STUDY DESIGN: Longitudinal evaluation from diagnosis to treatment among commercially insured enrollees with CHB. METHODS: We used standardized procedure and diagnosis codes to identify enrollees (≥ 18 years) with CHB in large insurance claims databases to describe the CHB care cascade from 2008 to 2016. Linkage to care was defined as procedure codes for liver fibrosis assessment (alanine aminotransferase in conjunction with either hepatitis B virus DNA or hepatitis B e-antigen) more than 12 months after CHB diagnosis. Treatment was defined as a claim for any CHB prescription. We analyzed factors associated with linkage to care and treatment using unadjusted logistic regression and evaluated rates of diagnosis, linkage to care, and treatment over time. RESULTS: Of 16,644 individuals with CHB, 6004 (36%) were linked to care and 2926 (18%) were treated. Persons coinfected with HIV (odds ratio [OR], 0.46; 95% CI, 0.36-0.59) or hepatitis C (OR, 0.50; 95% CI, 0.34-0.73) were less likely to be linked to care, and persons coinfected with HIV (OR, 0.29; 95% CI, 0.19-0.44) were less likely to be treated. From 2009 to 2015, there was a significant decrease in CHB diagnoses but no change in the proportion linked to care and treatment. CONCLUSIONS: We identified gaps in linkage to care and treatment in commercially insured adults with CHB.

On April 3, 2020, the White House Coronavirus Task Force and CDC announced a new behavioral recommendation to help slow the spread of coronavirus disease 2019 (COVID-19) by encouraging the use of a cloth face covering when out in public (1). Widespread use of cloth face coverings has not been studied among the U.S. population, and therefore, little is known about encouraging the public to adopt this behavior. Immediately following the recommendation, an Internet survey sampled 503 adults during April 7-9 to assess their use of cloth face coverings and the behavioral and sociodemographic factors that might influence adherence to this recommendation. The same survey was administered 1 month later, during May 11-13, to another sample of 502 adults to assess changes in the prevalence estimates of use of cloth face coverings from April to May. Within days of the release of the first national recommendation for use of cloth face coverings, a majority of persons who reported leaving their home in the previous week reported using a cloth face covering (61.9%). Prevalence of use increased to 76.4% 1 month later, primarily associated with increases in use among non-Hispanic white persons (54.3% to 75.1%), persons aged >/=65 years (36.6% to 79.2%), and persons residing in the Midwest (43.7% to 73.8%). High rates were observed in April and by May, increased further among non-Hispanic black persons (74.4% to 82.3%), Hispanic or Latino persons (77.3% to 76.2%), non-Hispanic persons of other race (70.8% to 77.3%), persons aged 18-29 years (70.1% to 74.9%) and 30-39 years (73.9% to 84.4%), and persons residing in the Northeast (76.9% to 87.0%). The use of a cloth face covering was associated with theory-derived constructs that indicate a favorable attitude toward them, intention to use them, ability to use them, social support for using them, and beliefs that they offered protection for self, others, and the community. Research is needed to understand possible barriers to using cloth face coverings and ways to promote their consistent and correct use among those who have yet to adopt this behavior.

BACKGROUND: The opioid epidemic has been associated with an increase in hepatitis C virus (HCV) infections. Federally qualified health centers (FQHCs) have a high burden of hepatitis C disease and could serve as venues to enhance testing and treatment. METHODS: We estimated clinical outcomes and the cost-effectiveness of hepatitis C testing and treatment at US FQHCs using individual-based simulation modeling. We used individual-level data from 57 FQHCs to model 9 strategies including permutations of HCV antibody testing modality, person initiating testing and testing approach. Outcomes included life expectancy, quality adjusted life years (QALY), hepatitis C cases identified, treated and cured, and incremental cost-effectiveness ratios (ICERs). RESULTS: Compared to current practice (risk-based with laboratory-based testing), routine rapid point-of-care testing initiated and performed by a counselor identified 68% more cases after (non-reflex) RNA testing in the first month of the intervention, led to a 17% reduction in cirrhosis cases, and a 22% reduction in liver deaths among those with cirrhosis over a lifetime. Routine rapid testing initiated by a counselor or a clinician provided better outcomes at either lower total cost or at lower cost per QALY gained, when compared to all other strategies. Findings were most influenced by the proportion of patients informed of their anti-HCV test results. CONCLUSIONS: Routine anti-HCV testing followed by prompt RNA testing for positives is recommended at FQHCs to identify infections. If using dedicated staff or point-of-care testing is not feasible, then measures to improve immediate patient knowledge of antibody status should be considered.

Identifying persons with hepatitis C virus (HCV) infection has become an urgent public health challenge because of increasing HCV-related morbidity and mortality, low rates of awareness among infected persons, and the advent of curative therapies (1). Since 2012, CDC has recommended testing of all persons born during 1945-1965 (baby boomers) for identification of chronic HCV infection (1); urban emergency departments (EDs) are well positioned venues for detecting HCV infection among these persons. The United States has witnessed an unprecedented opioid overdose epidemic since 2013 that derives primarily from commonly injected illicit opioids (e.g., heroin and fentanyl) (2). This injection drug use behavior has led to an increase in HCV infections among persons who inject drugs and heightened concern about increases in human immunodeficiency virus (HIV) and HCV infection within communities disproportionately affected by the opioid crisis (3,4). However, targeted strategies for identifying HCV infection among persons who inject drugs is challenging (5,6). During 2015-2016, EDs at the University of Alabama at Birmingham; Highland Hospital, Oakland, California; Johns Hopkins Hospital, Baltimore, Maryland; and Boston University Medical Center, Massachusetts, adopted opt-out (i.e., patients can implicitly accept or explicitly decline testing), universal hepatitis C screening for all adult patients. ED staff members offered HCV antibody (anti-HCV) screening to patients who were unaware of their status.* During similar observation periods at each site, ED staff members tested 14,252 patients and identified an overall 9.2% prevalence of positive results for anti-HCV among the adult patient population. Among the 1945-1965 birth cohort, prevalence of positive results for anti-HCV (13.9%) was significantly higher among non-Hispanic blacks (blacks) (16.0%) than among non-Hispanic whites (whites) (12.2%) (p<0.001). Among persons born after 1965, overall prevalence of positive results for anti-HCV was 6.7% and was significantly higher among whites (15.3%) than among blacks (3.2%) (p<0.001). These findings highlight age-associated differences in racial/ethnic prevalences and the potential for ED venues and opt-out, universal testing strategies to improve HCV infection awareness and surveillance for hard-to-reach populations. This opt-out, universal testing approach is supported by new recommendations for hepatitis C screening at least once in a lifetime for all adults aged >/=18 years, except in settings where the prevalence of positive results for HCV infection is <0.1% (7).

Over 27,000 people were sickened by Ebola and over 11,000 people died between March of 2014 and June of 2016. The US Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) was one of many public health organizations that sought to stop this outbreak. This agency deployed almost 2,000 individuals to West Africa during that timeframe. Deployment to these countries exposed these individuals to a wide variety of dangers, stressors, and risks.Being concerned about the at-risk populations in Africa, and also the well-being of its professionals who willingly deployed, the CDC did several things to help safeguard the health, safety, and resilience of these team members before, during, and after deployment.The accompanying special report highlights innovative pre-deployment training initiatives, customized screening processes, and post-deployment outreach efforts intended to protect and support the public health professionals fighting Ebola. Before deploying, the CDC team members were expected to participate in both internally-created and externally-provided trainings. These ranged from pre-deployment briefings, to Preparing for Work Overseas (PFWO) and Public Health Readiness Certificate Program (PHRCP) courses, to Incident Command System (ICS) 100, 200, and 400 courses.A small subset of non-clinical deployers also participated in a three-day training designed in collaboration with the Center for the Study of Traumatic Stress (CSTS; Bethesda, Maryland USA) to train individuals to assess and address the well-being and resilience of themselves and their teammates in the field during a deployment. Participants in this unique training were immersed in a Virtual Reality Environment (VRE) that simulated deployment to one of seven different types of emergencies.The CDC leadership also requested a pre-deployment screening process that helped professionals in the CDC's Occupational Health Clinic (OHC) determine whether or not individuals were at an increased risk of negative outcomes by participating in a rigorous deployment at that time.When deployers returned from the field, they received personalized invitations to participate in a voluntary, confidential, post-deployment operational debriefing one-on-one or in a group.Implementing these approaches provided more information to clinical decision makers about the readiness of deployers. It provided deployers with a greater awareness of the kinds of challenges they were likely to face in the field. The post-deployment outreach efforts reminded staff that their contributions were appreciated and there were resources available if they needed help processing any of the potentially-traumatizing things they may have experienced.

Network modelling is a valuable tool for simulating hepatitis C virus (HCV) and HIV transmission among people who inject drugs (PWID) and assessing the potential impact of treatment and harm-reduction interventions. In this paper, we review literature on network simulation models, highlighting key structural considerations and questions that network models are well suited to address. We describe five approaches (Erdos-Renyi, Stochastic Block, Watts-Strogatz, Barabasi-Albert, and Exponential Random Graph Model) used to model partnership formation with emphasis on the strengths of each approach in simulating different features of real-world PWID networks. We also review two important structural considerations when designing or interpreting results from a network simulation study: (1) dynamic vs. static network and (2) injection only vs. both injection and sexual networks. Dynamic network simulations allow partnerships to evolve and disintegrate over time, capturing corresponding shifts in individual and population-level risk behaviour; however, their high level of complexity and reliance on difficult-to-observe data has driven others to develop static network models. Incorporating both sexual and injection partnerships increases model complexity and data demands, but more accurately represents HIV transmission between PWID and their sexual partners who may not also use drugs. Network models add the greatest value when used to investigate how leveraging network structure can maximize the effectiveness of health interventions and optimize investments. For example, network models have shown that features of a given network and epidemic influence whether the greatest community benefit would be achieved by allocating hepatitis C or HIV treatment randomly, versus to those with the most partners. They have also demonstrated the potential for syringe services and "buddy sharing" programs to reduce disease transmission.

This study assesses the prevalence of falls, factors predicting future falls, and health impacts of falls and balance or walking problems for U.S. older adults. Data were participants >/=65years in the Medicare Health Outcomes Survey Cohort 15 (baseline survey in 2012; follow-up survey in 2014; n=164,597). We examined baseline factors predicting falls at follow-up and estimated the impact of falls and balance/walking problems on health-related quality of life (HRQOL), mortality, and quality-adjusted life years (QALYs). About 23% reported falls and 34% reported balance/walking problems in the past 12months. The strongest predictors of falls were previous falls [adjusted odds ratio (OR)=2.9] and balance/walking problems (OR=1.7). Many self-reported chronic conditions (e.g., depression, stroke, and diabetes), geriatric symptoms (e.g., urine leakage), and limitations of activities of daily living (e.g., transferring and walking) also predicted falls, but at a smaller magnitude (ORs=1.1-1.3). Having balance/walking problems was associated with a greater decrease in HRQOL scores (0.195 points) than falls (0.077 points), while falls were associated with a greater increase in mortality [adjusted hazard ratio (HR)=1.5] than balance/walking problems (HR=1.1). Falls were associated with a 4.6-year (48%) decrease in QALYs, while balance/walking problems was associated with a 7.3-year (62%) decrease in QALYs. Falls are a major problem for U.S. elderly and will continue to have an even greater impact as the population ages. The nearly 50% decrease in QALYs for falls and >60% decrease for balance or walking problems demonstrates the substantial burden associated with these problems among older Americans.

BACKGROUND: The staging method for activities of daily living (ADLs) limitations developed by Stineman and colleagues that classifies people into five stages can reflect severity of activity limitations. OBJECTIVE: To assess the impact of stages of limitations in ADLs on quality-adjusted life years (QALYs) and the relative severity of each ADL limitation for a large, nationally-representative sample of the U.S. community-dwelling older population. METHODS: Data were obtained from the Limited Dataset of the Medicare Health Outcomes Survey Cohort 15 (2012 baseline survey, 2014 follow-up survey). We included respondents aged >/=65 years (n=105,473). We estimated expected QALYs throughout the remaining lifetime of participants stratified by the ADL limitation status and stages of ADL limitations. RESULTS: Overall, the expected QALYs was 5.6 years. QALYs decreased with increasing stages of ADL limitations. The adjusted QALYs for Stage 0 (no limitation) participants were 6.8; for Stage I (mild) participants, 3.9; for Stage II (moderate) participants, 2.2; for Stage III (severe) participants, 1.8; and for Stage IV (complete limitations) participants, 1.5. Differences in QALYs occurred between individual ADL items within an ADL stage. In Stage I, for example, participants who reported only problems with getting in or out of chairs had 6.7 QALYs which was markedly higher than participants who reported only problems with walking (3.8 QALYs). CONCLUSIONS: Our findings provide additional evidence that Stineman's ADL stages serve as valid estimates of the overall health of elderly Americans. Self-reported ADL status should be routinely collected as a patient-reported outcome in the elderly population.

BACKGROUND: The Medicare Health Outcomes Survey (HOS), a nationwide annual survey of Medicare beneficiaries, includes the Centers for Disease Control and Prevention's HRQOL-4 questionnaire and Veterans RAND 12-item Health Survey (VR-12). This study compared EQ-5D scores derived from the HRQOL-4 (dEQ-5D) to SF-6D scores derived from VR-12. METHODS: Data were from Medicare HOS Cohort 15 (2012 baseline; 2014 follow-up). We included participants aged 65+ ( n = 105,473). We compared score distributions, evaluated known-groups validity, assessed each index as a predictor for mortality, and estimated quality-adjusted life years (QALYs) using the dEQ-5D and SF-6D. RESULTS: Compared to the SF-6D, the dEQ-5D had a higher mean score (0.787 v. 0.691) and larger standard deviation (0.310 v. 0.101). The decreases in estimated scores associated with chronic conditions were greater for the dEQ-5D than for the SF-6D. For example, dEQ-5D scores for persons with depression decreased 0.456 points compared to 0.141 points for the SF-6D. The dEQ-5D strongly predicted mortality, as adjusted hazard ratios for the first to fourth quintiles, relative to the fifth quintile, were 2.2, 1.7, 1.8, and 1.5, respectively, while the association between SF-6D and mortality was weaker or nonexistent (adjusted hazard ratios were 1.3, 1.1, 1.0, and 0.6, respectively). Compared to the SF-6D, QALYs estimated using the dEQ-5D were higher overall (5.6 v. 4.9 years), higher for persons with less debilitating conditions (e.g., hypertension, 5.0 v. 4.4 years), and lower for more debilitating conditions (e.g. depression, 2.5 v. 2.8 years). CONCLUSIONS: Compared to the SF-6D, the dEQ-5D was better able to measure individuals' overall health; detect the differential impact of chronic conditions, particularly among persons in poorer health; and predict mortality. The HRQOL-4 questionnaire may be valuable for monitoring and improving health outcomes for the Medical HOS data set.

Despite significant declines in the use of cigarettes, a significant proportion of adults smoke. This study explores the association between smoking and health-related quality of life (HRQoL) by age. The 2016 Behavioral Risk Factor Surveillance System survey was administered to adults in 50 states and District of Columbia (n = 437,195). Physically unhealthy days (PUDs) and mentally unhealthy days (MUDs)) were regressed on age strata (18-24, 25-34, 35-44, 45-54, 55-64, ≥ 65 years) and smoking status (never, former, someday, and everyday) using negative binomial regression models with adjustment for sociodemographic covariates. For each age group, everyday smoking highly predicted PUDs and MUDs. Predicted PUDs increased with age; predicted MUDs decreased with age. Among adults aged 45-54 and 55-64 years, 3-day difference in PUDs was observed between never smokers and everyday smokers. Among young adults (18-24 years), a 4.3-day difference in MUDs was observed between everyday and never smokers. The discrepancies were nonlinear with age. The observed relationship between smoking and HRQoL provides novel information about the need to consider age when designing community-based interventions. Additional research can provide needed depth to understanding the relationship between smoking and HRQoL in specific age groups.