Racial and Ethnic Disparities in Rates of COVID-19-Associated Hospitalization, Intensive Care Unit Admission, and In-Hospital Death in the United States From March 2020 to February 2021.

Importance: Racial and ethnic minority groups are disproportionately affected by COVID-19. Objectives: To evaluate whether rates of severe COVID-19, defined as hospitalization, intensive care unit (ICU) admission, or in-hospital death, are higher among racial and ethnic minority groups compared with non-Hispanic White persons. Design, Setting, and Participants: This cross-sectional study included 99 counties within 14 US states participating in the COVID-19-Associated Hospitalization Surveillance Network. Participants were persons of all ages hospitalized with COVID-19 from March 1, 2020, to February 28, 2021. Exposures: Laboratory-confirmed COVID-19-associated hospitalization, defined as a positive SARS-CoV-2 test within 14 days prior to or during hospitalization. Main Outcomes and Measures: Cumulative age-adjusted rates (per 100 000 population) of hospitalization, ICU admission, and death by race and ethnicity. Rate ratios (RR) were calculated for each racial and ethnic group compared with White persons. Results: Among 153 692 patients with COVID-19-associated hospitalizations, 143 342 (93.3%) with information on race and ethnicity were included in the analysis. Of these, 105 421 (73.5%) were 50 years or older, 72 159 (50.3%) were male, 28 762 (20.1%) were Hispanic or Latino, 2056 (1.4%) were non-Hispanic American Indian or Alaska Native, 7737 (5.4%) were non-Hispanic Asian or Pacific Islander, 40 806 (28.5%) were non-Hispanic Black, and 63 981 (44.6%) were White. Compared with White persons, American Indian or Alaska Native, Latino, Black, and Asian or Pacific Islander persons were more likely to have higher cumulative age-adjusted rates of hospitalization, ICU admission, and death as follows: American Indian or Alaska Native (hospitalization: RR, 3.70; 95% CI, 3.54-3.87; ICU admission: RR, 6.49; 95% CI, 6.01-7.01; death: RR, 7.19; 95% CI, 6.47-7.99); Latino (hospitalization: RR, 3.06; 95% CI, 3.01-3.10; ICU admission: RR, 4.20; 95% CI, 4.08-4.33; death: RR, 3.85; 95% CI, 3.68-4.01); Black (hospitalization: RR, 2.85; 95% CI, 2.81-2.89; ICU admission: RR, 3.17; 95% CI, 3.09-3.26; death: RR, 2.58; 95% CI, 2.48-2.69); and Asian or Pacific Islander (hospitalization: RR, 1.03; 95% CI, 1.01-1.06; ICU admission: RR, 1.91; 95% CI, 1.83-1.98; death: RR, 1.64; 95% CI, 1.55-1.74). Conclusions and Relevance: In this cross-sectional analysis, American Indian or Alaska Native, Latino, Black, and Asian or Pacific Islander persons were more likely than White persons to have a COVID-19-associated hospitalization, ICU admission, or in-hospital death during the first year of the US COVID-19 pandemic. Equitable access to COVID-19 preventive measures, including vaccination, is needed to minimize the gap in racial and ethnic disparities of severe COVID-19.

Census tract socioeconomic indicators and COVID-19-associated hospitalization rates-COVID-NET surveillance areas in 14 states, March 1-April 30, 2020.

OBJECTIVES: Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. METHODS: Using data from COVID-NET population-based surveillance reported during March 1-April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. RESULTS: Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1-156.1) in census tracts with >15.2%-83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9-78.1) in census tracts with 0%-4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3-128.2), 252.2 (95% CI: 241.4-263.0), and 341.1 (95% CI: 317.3-365.0), respectively, compared with 58.2 (95% CI: 55.4-61.1), 304.0 (95%: 282.4-325.6), and 540.3 (95% CI: 477.0-603.6), respectively, in low-poverty census tracts. CONCLUSIONS: Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.

Risk for In-Hospital Complications Associated with COVID-19 and Influenza - Veterans Health Administration, United States, October 1, 2018-May 31, 2020.

Coronavirus disease 2019 (COVID-19) is primarily a respiratory illness, although increasing evidence indicates that infection with SARS-CoV-2, the virus that causes COVID-19, can affect multiple organ systems (1). Data that examine all in-hospital complications of COVID-19 and that compare these complications with those associated with other viral respiratory pathogens, such as influenza, are lacking. To assess complications of COVID-19 and influenza, electronic health records (EHRs) from 3,948 hospitalized patients with COVID-19 (March 1-May 31, 2020) and 5,453 hospitalized patients with influenza (October 1, 2018-February 1, 2020) from the national Veterans Health Administration (VHA), the largest integrated health care system in the United States,* were analyzed. Using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes, complications in patients with laboratory-confirmed COVID-19 were compared with those in patients with influenza. Risk ratios were calculated and adjusted for age, sex, race/ethnicity, and underlying medical conditions; proportions of complications were stratified among patients with COVID-19 by race/ethnicity. Patients with COVID-19 had almost 19 times the risk for acute respiratory distress syndrome (ARDS) than did patients with influenza, (adjusted risk ratio [aRR] = 18.60; 95% confidence interval [CI] = 12.40-28.00), and more than twice the risk for myocarditis (2.56; 1.17-5.59), deep vein thrombosis (2.81; 2.04-3.87), pulmonary embolism (2.10; 1.53-2.89), intracranial hemorrhage (2.85; 1.35-6.03), acute hepatitis/liver failure (3.13; 1.92-5.10), bacteremia (2.46; 1.91-3.18), and pressure ulcers (2.65; 2.14-3.27). The risks for exacerbations of asthma (0.27; 0.16-0.44) and chronic obstructive pulmonary disease (COPD) (0.37; 0.32-0.42) were lower among patients with COVID-19 than among those with influenza. The percentage of COVID-19 patients who died while hospitalized (21.0%) was more than five times that of influenza patients (3.8%), and the duration of hospitalization was almost three times longer for COVID-19 patients. Among patients with COVID-19, the risk for respiratory, neurologic, and renal complications, and sepsis was higher among non-Hispanic Black or African American (Black) patients, patients of other races, and Hispanic or Latino (Hispanic) patients compared with those in non-Hispanic White (White) patients, even after adjusting for age and underlying medical conditions. These findings highlight the higher risk for most complications associated with COVID-19 compared with influenza and might aid clinicians and researchers in recognizing, monitoring, and managing the spectrum of COVID-19 manifestations. The higher risk for certain complications among racial and ethnic minority patients provides further evidence that certain racial and ethnic minority groups are disproportionally affected by COVID-19 and that this disparity is not solely accounted for by age and underlying medical conditions.

Spatial and temporal clustering of patients hospitalized with laboratory-confirmed influenza in the United States.

BACKGROUND: Timing of influenza spread across the United States is dependent on factors including local and national travel patterns and climate. Local epidemic intensity may be influenced by social, economic and demographic patterns. Data are needed to better explain how local socioeconomic factors influence both the timing and intensity of influenza seasons to result in national patterns. METHODS: To determine the spatial and temporal impacts of socioeconomics on influenza hospitalization burden and timing, we used population-based laboratory-confirmed influenza hospitalization surveillance data from the CDC-sponsored Influenza Hospitalization Surveillance Network (FluSurv-NET) at up to 14 sites from the 2009/2010 through 2013/2014 seasons (n = 35,493 hospitalizations). We used a spatial scan statistic and spatiotemporal wavelet analysis, to compare temporal patterns of influenza spread between counties and across the country. RESULTS: There were 56 spatial clusters identified in the unadjusted scan statistic analysis using data from the 2010/2011 through the 2013/2014 seasons, with relative risks (RRs) ranging from 0.09 to 4.20. After adjustment for socioeconomic factors, there were five clusters identified with RRs ranging from 0.21 to 1.20. In the wavelet analysis, most sites were in phase synchrony with one another for most years, except for the H1N1 pandemic year (2009-2010), wherein most sites had differential epidemic timing from the referent site in Georgia. CONCLUSIONS: Socioeconomic factors strongly impact local influenza hospitalization burden. Influenza phase synchrony varies by year and by socioeconomics, but is less influenced by socioeconomics than is disease burden.

Update: Influenza Activity in the United States During the 2018-19 Season and Composition of the 2019-20 Influenza Vaccine.

Influenza activity* in the United States during the 2018-19 season (September 30, 2018-May 18, 2019) was of moderate severity (1). Nationally, influenza-like illness (ILI)† activity began increasing in November, peaked during mid-February, and returned to below baseline in mid-April; the season lasted 21 weeks,§ making it the longest season in 10 years. Illness attributed to influenza A viruses predominated, with very little influenza B activity. Two waves of influenza A were notable during this extended season: influenza A(H1N1)pdm09 viruses from October 2018 to mid-February 2019 and influenza A(H3N2) viruses from February through May 2019. Compared with the 2017-18 influenza season, rates of hospitalization this season were lower for adults, but were similar for children. Although influenza activity is currently below surveillance baselines, testing for seasonal influenza viruses and monitoring for novel influenza A virus infections should continue year-round. Receiving a seasonal influenza vaccine each year remains the best way to protect against seasonal influenza and its potentially severe consequences.

Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness.

BACKGROUND: Estimates of influenza disease burden are broadly useful for public health, helping national and local authorities monitor epidemiologic trends, plan and allocate resources, and promote influenza vaccination. Historically, estimates of the burden of seasonal influenza in the United States, focused mainly on influenza-related mortality and hospitalization, were generated every few years. Since the 2010-2011 influenza season, annual US influenza burden estimates have been generated and expanded to include estimates of influenza-related outpatient medical visits and symptomatic illness in the community. METHODS: We used routinely collected surveillance data, outbreak field investigations, and proportions of people seeking health care from survey results to estimate the number of illnesses, medical visits, hospitalizations, and deaths due to influenza during six influenza seasons (2010-2011 through 2015-2016). RESULTS: We estimate that the number of influenza-related illnesses that have occurred during influenza season has ranged from 9.2 million to 35.6 million, including 140 000 to 710 000 influenza-related hospitalizations. DISCUSSION: These annual efforts have strengthened public health communications products and supported timely assessment of the impact of vaccination through estimates of illness and hospitalizations averted. Additionally, annual estimates of influenza burden have highlighted areas where disease surveillance needs improvement to better support public health decision making for seasonal influenza epidemics as well as future pandemics.

Systematic Assessment of Multiple Routine and Near Real-Time Indicators to Classify the Severity of Influenza Seasons and Pandemics in the United States, 2003-2004 Through 2015-2016.

Assessments of influenza season severity can guide public health action. We used the moving epidemic method to develop intensity thresholds (ITs) for 3 US surveillance indicators from the 2003-2004 through 2014-2015 influenza seasons (excluding the 2009 pandemic). The indicators were: 1) outpatient visits for influenza-like illness; 2) influenza-related hospitalizations; and 3) influenza- and pneumonia-related deaths. ITs were developed for the population overall and separately for children, adults, and older adults, and they were set at the upper limit of the 50% (IT50), 90% (IT90), and 98% (IT98) 1-sided confidence intervals of the geometric mean of each season's 3 highest values. Severity was classified as low if ≥2 systems peaked below IT50, moderate if ≥2 peaked between IT50 and IT90, high if ≥2 peaked between IT90 and IT98, and very high if ≥2 peaked above IT98. We pilot-tested this method with the 2015-2016 season and the 2009 pandemic. Overall, 4 seasons were classified as low severity, 7 as moderate, 2 as high, and none as very high. Among the age groups, older adults had the most seasons (n = 3) classified as high, and children were the only group to have seasons (n = 2) classified as very high. We will apply this method to classify the severity of future seasons and inform pandemic response.

Social determinants of influenza hospitalization in the United States.

BACKGROUND: Influenza hospitalizations result in substantial morbidity and mortality each year. Little is known about the association between influenza hospitalization and census tract-based socioeconomic determinants beyond the effect of individual factors. OBJECTIVE: To evaluate whether census tract-based determinants such as poverty and household crowding would contribute significantly to the risk of influenza hospitalization above and beyond individual-level determinants. METHODS: We analyzed 33 515 laboratory-confirmed influenza-associated hospitalizations that occurred during the 2009-2010 through 2013-2014 influenza seasons using a population-based surveillance system at 14 sites across the United States. RESULTS: Using a multilevel regression model, we found that individual factors were associated with influenza hospitalization with the highest adjusted odds ratio (AOR) of 9.20 (95% CI 8.72-9.70) for those ≥65 vs 5-17 years old. African Americans had an AOR of 1.67 (95% CI 1.60-1.73) compared to Whites, and Hispanics had an AOR of 1.21 (95% CI 1.16-1.26) compared to non-Hispanics. Among census tract-based determinants, those living in a tract with ≥20% vs <5% of persons living below poverty had an AOR of 1.31 (95% CI 1.16-1.47), those living in a tract with ≥5% vs <5% of persons living in crowded conditions had an AOR of 1.17 (95% CI 1.11-1.23), and those living in a tract with ≥40% vs <5% female heads of household had an AOR of 1.32 (95% CI 1.25-1.40). CONCLUSION: Census tract-based determinants account for 11% of the variability in influenza hospitalization.

Violence, health, and the 2030 agenda: Merging evidence and implementation.

The Guest Editors introduce the Special Issue for the Journal of Public Health Policy on violence, health, and the 2030 Agenda. Emphasizing the importance of collaboration between scholars and practitioners, they outline the process of jointly imagining and designing the next generation of violence prevention strategies. They include representative works of members of the World Health Organization (WHO) Violence Prevention Alliance (VPA), including the World Bank, the United States Centers for Disease Control and Prevention, Prevention Institute, the Danish Institute Against Torture, the University of Cambridge Institute of Criminology, the London School of Hygiene and Tropical Medicine Gender Violence and Health Centre, and the Yale University Law and Psychiatry Division, among others.

A case for studying country regimes in the public health model of violence.

Many national and international institutions advocate approaching violence as a problem in public health and preventive medicine, in a manner similar to the way we address other disabling and life-threatening pathologies such as cancer, diabetes, and heart disease. Prevention by a health model requires an ecological perspective. Previous work has found evidence that economic factors, including unemployment and relative poverty, as well as political culture and values, may affect violent death rates, including homicide and suicide. Nevertheless, wider political analyses of the effects that different regimes have on these variables have been notably absent, for understandable reasons given the sheer complexity of patterns of governance throughout the world. In view of the importance and scale of the problem, and implications of the United Nations' 2030 Agenda for Sustainable Development, we feel it is nevertheless important to bring regime types into the conversation of factors that can influence violent death.