Alternative Methods for Grouping Race and Ethnicity to Monitor COVID-19 Outcomes and Vaccination Coverage.

Population-based analyses of COVID-19 data, by race and ethnicity can identify and monitor disparities in COVID-19 outcomes and vaccination coverage. CDC recommends that information about race and ethnicity be collected to identify disparities and ensure equitable access to protective measures such as vaccines; however, this information is often missing in COVID-19 data reported to CDC. Baseline data collection requirements of the Office of Management and Budget's Standards for the Classification of Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15) include two ethnicity categories and a minimum of five race categories (1). Using available COVID-19 case and vaccination data, CDC compared the current method for grouping persons by race and ethnicity, which prioritizes ethnicity (in alignment with the policy directive), with two alternative methods (methods A and B) that used race information when ethnicity information was missing. Method A assumed non-Hispanic ethnicity when ethnicity data were unknown or missing and used the same population groupings (denominators) for rate calculations as the current method (Hispanic persons for the Hispanic group and race category and non-Hispanic persons for the different racial groups). Method B grouped persons into ethnicity and race categories that are not mutually exclusive, unlike the current method and method A. Denominators for rate calculations using method B were Hispanic persons for the Hispanic group and persons of Hispanic or non-Hispanic ethnicity for the different racial groups. Compared with the current method, the alternative methods resulted in higher counts of COVID-19 cases and fully vaccinated persons across race categories (American Indian or Alaska Native [AI/AN], Asian, Black or African American [Black], Native Hawaiian or Other Pacific Islander [NH/PI], and White persons). When method B was used, the largest relative increase in cases (58.5%) was among AI/AN persons and the largest relative increase in the number of those fully vaccinated persons was among NH/PI persons (51.6%). Compared with the current method, method A resulted in higher cumulative incidence and vaccination coverage rates for the five racial groups. Method B resulted in decreasing cumulative incidence rates for two groups (AI/AN and NH/PI persons) and decreasing cumulative vaccination coverage rates for AI/AN persons. The rate ratio for having a case of COVID-19 by racial and ethnic group compared with that for White persons varied by method but was <1 for Asian persons and >1 for other groups across all three methods. The likelihood of being fully vaccinated was highest among NH/PI persons across all three methods. This analysis demonstrates that alternative methods for analyzing race and ethnicity data when data are incomplete can lead to different conclusions about disparities. These methods have limitations, however, and warrant further examination of potential bias and consultation with experts to identify additional methods for analyzing and tracking disparities when race and ethnicity data are incomplete.

Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use.

OBJECTIVES: Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. METHODS: We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. RESULTS: Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. PRACTICE IMPLICATIONS: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.

Trends in Racial and Ethnic Disparities in COVID-19 Hospitalizations, by Region - United States, March-December 2020.

Persons from racial and ethnic minority groups are disproportionately affected by COVID-19, including experiencing increased risk for infection (1), hospitalization (2,3), and death (4,5). Using administrative discharge data, CDC assessed monthly trends in the proportion of hospitalized patients with COVID-19 among racial and ethnic groups in the United States during March-December 2020 by U.S. Census region. Cumulative and monthly age-adjusted COVID-19 proportionate hospitalization ratios (aPHRs) were calculated for racial and ethnic minority patients relative to non-Hispanic White patients. Within each of the four U.S. Census regions, the cumulative aPHR was highest for Hispanic or Latino patients (range = 2.7-3.9). Racial and ethnic disparities in COVID-19 hospitalization were largest during May-July 2020; the peak monthly aPHR among Hispanic or Latino patients was >9.0 in the West and Midwest, >6.0 in the South, and >3.0 in the Northeast. The aPHRs declined for most racial and ethnic groups during July-November 2020 but increased for some racial and ethnic groups in some regions during December. Disparities in COVID-19 hospitalization by race/ethnicity varied by region and became less pronounced over the course of the pandemic, as COVID-19 hospitalizations increased among non-Hispanic White persons. Identification of specific social determinants of health that contribute to geographic and temporal differences in racial and ethnic disparities at the local level can help guide tailored public health prevention strategies and equitable allocation of resources, including COVID-19 vaccination, to address COVID-19-related health disparities and can inform approaches to achieve greater health equity during future public health threats.

Counties with High COVID-19 Incidence and Relatively Large Racial and Ethnic Minority Populations - United States, April 1-December 22, 2020.

Long-standing systemic social, economic, and environmental inequities in the United States have put many communities of color (racial and ethnic minority groups) at increased risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, as well as more severe COVID-19-related outcomes (1-3). Because race and ethnicity are missing for a proportion of reported COVID-19 cases, counties with substantial missing information often are excluded from analyses of disparities (4). Thus, as a complement to these case-based analyses, population-based studies can help direct public health interventions. Using data from the 50 states and the District of Columbia (DC), CDC identified counties where five racial and ethnic minority groups (Hispanic or Latino [Hispanic], non-Hispanic Black or African American [Black], non-Hispanic Asian [Asian], non-Hispanic American Indian or Alaska Native [AI/AN], and non-Hispanic Native Hawaiian or other Pacific Islander [NH/PI]) might have experienced high COVID-19 impact during April 1-December 22, 2020. These counties had high 2-week COVID-19 incidences (>100 new cases per 100,000 persons in the total population) and percentages of persons in five racial and ethnic groups that were larger than the national percentages (denoted as "large"). During April 1-14, a total of 359 (11.4%) of 3,142 U.S. counties reported high COVID-19 incidence, including 28.7% of counties with large percentages of Asian persons and 27.9% of counties with large percentages of Black persons. During August 5-18, high COVID-19 incidence was reported by 2,034 (64.7%) counties, including 92.4% of counties with large percentages of Black persons and 74.5% of counties with large percentages of Hispanic persons. During December 9-22, high COVID-19 incidence was reported by 3,114 (99.1%) counties, including >95% of those with large percentages of persons in each of the five racial and ethnic minority groups. The findings of this population-based analysis complement those of case-based analyses. In jurisdictions with substantial missing race and ethnicity information, this method could be applied to smaller geographic areas, to identify communities of color that might be experiencing high potential COVID-19 impact. As areas with high rates of new infection change over time, public health efforts can be tailored to the needs of communities of color as the pandemic evolves and integrated with longer-term plans to improve health equity.

CDC Deployments to State, Tribal, Local, and Territorial Health Departments for COVID-19 Emergency Public Health Response - United States, January 21-July 25, 2020.

Coronavirus disease 2019 (COVID-19) is a viral respiratory illness caused by SARS-CoV-2. During January 21-July 25, 2020, in response to official requests for assistance with COVID-19 emergency public health response activities, CDC deployed 208 teams to assist 55 state, tribal, local, and territorial health departments. CDC deployment data were analyzed to summarize activities by deployed CDC teams in assisting state, tribal, local, and territorial health departments to identify and implement measures to contain SARS-CoV-2 transmission (1). Deployed teams assisted with the investigation of transmission in high-risk congregate settings, such as long-term care facilities (53 deployments; 26% of total), food processing facilities (24; 12%), correctional facilities (12; 6%), and settings that provide services to persons experiencing homelessness (10; 5%). Among the 208 deployed teams, 178 (85%) provided assistance to state health departments, 12 (6%) to tribal health departments, 10 (5%) to local health departments, and eight (4%) to territorial health departments. CDC collaborations with health departments have strengthened local capacity and provided outbreak response support. Collaborations focused attention on health equity issues among disproportionately affected populations (e.g., racial and ethnic minority populations, essential frontline workers, and persons experiencing homelessness) and through a place-based focus (e.g., persons living in rural or frontier areas). These collaborations also facilitated enhanced characterization of COVID-19 epidemiology, directly contributing to CDC data-informed guidance, including guidance for serial testing as a containment strategy in high-risk congregate settings, targeted interventions and prevention efforts among workers at food processing facilities, and social distancing.

Race, Ethnicity, and Age Trends in Persons Who Died from COVID-19 - United States, May-August 2020.

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System† (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.

Disparities in Incidence of COVID-19 Among Underrepresented Racial/Ethnic Groups in Counties Identified as Hotspots During June 5-18, 2020 - 22 States, February-June 2020.

During January 1, 2020-August 10, 2020, an estimated 5 million cases of coronavirus disease 2019 (COVID-19) were reported in the United States.* Published state and national data indicate that persons of color might be more likely to become infected with SARS-CoV-2, the virus that causes COVID-19, experience more severe COVID-19-associated illness, including that requiring hospitalization, and have higher risk for death from COVID-19 (1-5). CDC examined county-level disparities in COVID-19 cases among underrepresented racial/ethnic groups in counties identified as hotspots, which are defined using algorithmic thresholds related to the number of new cases and the changes in incidence.† Disparities were defined as difference of ≥5% between the proportion of cases and the proportion of the population or a ratio ≥1.5 for the proportion of cases to the proportion of the population for underrepresented racial/ethnic groups in each county. During June 5-18, 205 counties in 33 states were identified as hotspots; among these counties, race was reported for ≥50% of cumulative cases in 79 (38.5%) counties in 22 states; 96.2% of these counties had disparities in COVID-19 cases in one or more underrepresented racial/ethnic groups. Hispanic/Latino (Hispanic) persons were the largest group by population size (3.5 million persons) living in hotspot counties where a disproportionate number of cases among that group was identified, followed by black/African American (black) persons (2 million), American Indian/Alaska Native (AI/AN) persons (61,000), Asian persons (36,000), and Native Hawaiian/other Pacific Islander (NHPI) persons (31,000). Examining county-level data disaggregated by race/ethnicity can help identify health disparities in COVID-19 cases and inform strategies for preventing and slowing SARS-CoV-2 transmission. More complete race/ethnicity data are needed to fully inform public health decision-making. Addressing the pandemic's disproportionate incidence of COVID-19 in communities of color can reduce the community-wide impact of COVID-19 and improve health outcomes.

Potential Indirect Effects of the COVID-19 Pandemic on Use of Emergency Departments for Acute Life-Threatening Conditions - United States, January-May 2020.

On March 13, 2020, the United States declared a national emergency in response to the coronavirus disease 2019 (COVID-19) pandemic. Subsequently, states enacted stay-at-home orders to slow the spread of SARS-CoV-2, the virus that causes COVID-19, and reduce the burden on the U.S. health care system. CDC* and the Centers for Medicare & Medicaid Services (CMS)† recommended that health care systems prioritize urgent visits and delay elective care to mitigate the spread of COVID-19 in health care settings. By May 2020, national syndromic surveillance data found that emergency department (ED) visits had declined 42% during the early months of the pandemic (1). This report describes trends in ED visits for three acute life-threatening health conditions (myocardial infarction [MI, also known as heart attack], stroke, and hyperglycemic crisis), immediately before and after declaration of the COVID-19 pandemic as a national emergency. These conditions represent acute events that always necessitate immediate emergency care, even during a public health emergency such as the COVID-19 pandemic. In the 10 weeks following the emergency declaration (March 15-May 23, 2020), ED visits declined 23% for MI, 20% for stroke, and 10% for hyperglycemic crisis, compared with the preceding 10-week period (January 5-March 14, 2020). EDs play a critical role in diagnosing and treating life-threatening conditions that might result in serious disability or death. Persons experiencing signs or symptoms of serious illness, such as severe chest pain, sudden or partial loss of motor function, altered mental state, signs of extreme hyperglycemia, or other life-threatening issues, should seek immediate emergency care, regardless of the pandemic. Clear, frequent, highly visible communication from public health and health care professionals is needed to reinforce the importance of timely care for medical emergencies and to assure the public that EDs are implementing infection prevention and control guidelines that help ensure the safety of their patients and health care personnel.

Diabetes Among People With Tuberculosis, HIV Infection, Viral Hepatitis B and C, and STDs in New York City, 2006-2010.

Matching infectious disease surveillance data has become a routine activity for many health departments. With the increasing focus on chronic disease, it is also useful to explore opportunities to match infectious and chronic disease surveillance data. To understand the burden of diabetes in New York City (NYC), adults with select infectious diseases (tuberculosis, HIV infection, hepatitis B, hepatitis C, chlamydial infection, gonorrhea, and syphilis) reported between 2006 and 2010 were matched with hemoglobin A1c results reported in the same period. Persons were considered to have diabetes with 2 or more hemoglobin A1c test results of 6.5% or higher. The analysis was restricted to persons who were 18 years or older at the time of first report, either A1c or infectious disease. Overall age-adjusted diabetes prevalence was 8.1%, and diabetes prevalence was associated with increasing age; among NYC residents, prevalence ranged from 0.6% among 18- to 29-year-olds to 22.4% among those 65 years and older. This association was also observed in each infectious disease. Diabetes prevalence was significantly higher among persons with tuberculosis born in Mexico, Jamaica, Honduras, Guyana, Bangladesh, Dominican Republic, the Philippines, and Haiti compared with those born in the United States after adjusting for age and sex. Hepatitis C virus-infected women had higher age-adjusted prevalence of diabetes compared with the NYC population as a whole. Recognizing associations between diabetes and infectious diseases can assist early diagnosis and management of these conditions. Matching chronic disease and infectious disease surveillance data has important implications for local health departments and large health system practices, including increasing opportunities for integrated work both internal to systems and with the local community. Large health systems may consider opportunities for increased collaboration across infectious and chronic disease programs facilitated through data linkages of routinely collected surveillance data.

Strengthening Screening for HIV, Hepatitis C, and STIs: An Innovative Partnership Between the Health Department and Community Health Centers in New York City.

In New York City, federally qualified health centers (FQHCs) are ideal partners for health departments because of their location in neighborhoods with high rates of HIV, hepatitis C virus (HCV) infection, and gonorrhea. Providers have experienced many barriers to following screening and treatment recommendations. In 2013, the New York City Department of Health and Mental Hygiene partnered with six FQHCs, representing 14 clinics, to make screening for HIV and HCV routine and increase adherence to gonorrhea treatment guidelines through education, electronic health record modification, and progress tracking. After one year, 12 of 14 clinics documented improvement in their HIV offer rate, and 11 clinics documented improvement in their HIV screening rate. Patients who were offered HIV screening increased from 26% at baseline to 56% at follow-up, and patients screened for HIV increased from 25% at baseline to 38% at follow-up. Most clinics improved their HIV screening rate, and progress suggests that local health departments can help FQHCs increase their HIV screening rates.

Factors Associated With Hepatitis C Infection Among HIV-Infected Men Who Have Sex With Men With No Reported Injection Drug Use in New York City, 2000-2010.

BACKGROUND: Hepatitis C (HCV) infection is a major source of morbidity and mortality among HIV-infected patients. Despite decreasing HCV incidence in the United States, the proportion of cases among men who have sex with men (MSM) without history of injection drug use (IDU) in New York City has more than tripled between 2000 and 2010. METHODS: Using matched surveillance data, we identified non-IDU HIV-infected MSM with and without diagnosed HCV. Differences in continuous variables were assessed with Mann-Whitney U tests, and Pearson χ tests were used for categorical variables. Poisson regression was used to compare HCV diagnosis rates by race/ethnicity and sexual transmitted disease history. RESULTS: There were 41,303 non-IDU MSM diagnosed as having HIV before 2010 alive as of 2000, of whom 2016 (4.9%) were diagnosed as having HCV after HIV diagnosis. The HCV diagnosis rate was 605/100,000 person-years. Adjusting for birth year and age at HIV diagnosis, Hispanics (rate ratio [RR], 1.4; 95% confidence interval [CI], 1.2-1.5) and non-Hispanic blacks (RR, 1.6; 95% CI, 1.4-1.8) had higher HCV diagnosis rates than did non-Hispanic whites. Adjusting for race/ethnicity, birth year, and age at HIV diagnosis, MSM diagnosed as having syphilis (RR, 2.5; 95% CI, 2.3-2.8) had higher HCV diagnosis rates than did those without syphilis. CONCLUSIONS: We found a racial/ethnic disparity in HCV diagnosis rates and an association between HCV and syphilis, which is consistent with sexual transmission of HCV. With curative HCV treatment available, emphasis should be placed on adherence to guidelines recommending annual HCV screening for HIV-infected MSM, and education and outreach to MSM to prevent sexually transmitted HCV infections.

Legal and policy barriers to sharing data between public health programs in New York City: a case study.

Integration of public health surveillance data within health departments is important for public health activities and cost-efficient coordination of care. Access to and use of surveillance data are governed by public health law and by agency confidentiality and security policies. In New York City, we examined public health laws and agency policies for data sharing across HIV, sexually transmitted disease, tuberculosis, and viral hepatitis surveillance programs. We found that recent changes to state laws provide greater opportunities for data sharing but that agency policies must be updated because they limit increased data integration. Our case study can help other health departments conduct similar reviews of laws and policies to increase data sharing and integration of surveillance data.

Deaths among people with hepatitis C in New York City, 2000-2011.

BACKGROUND: Infection with hepatitis C virus (HCV) increases the risk of death from liver and nonliver-related diseases. Coinfection with human immunodeficiency virus (HIV) further increases this risk. METHODS: Surveillance data (2000-2010) and mortality data (2000-2011) maintained by the New York City Department of Health and Mental Hygiene (DOHMH) were deterministically cross-matched. Factors associated with and causes of death among HCV-infected adult decedents were analyzed. RESULTS: Between 2000 and 2011, 13 307 HCV-monoinfected adults died, and 5475 adults coinfected with HCV/HIV died. Decedents with HCV monoinfection were more likely to have died of liver cancer (odds ratio [OR] = 9.2), drug-related causes (OR = 4.3), and cirrhosis (OR = 3.7), compared with persons with neither infection. HCV/HIV-coinfected decedents were more likely to have died of liver cancer (OR = 2.2) and drug-related causes (OR = 3.1), compared with persons with neither infection. Among coinfected decedents, 53.6% of deaths were attributed to HIV/AIDS, and 94% of deaths occurred prematurely (before age 65). Among persons with HCV who died, more than half died within 3 years of an HCV report to DOHMH. CONCLUSIONS: HCV-infected adults were at increased risk of dying and of dying prematurely, particularly from conditions associated with HCV, such as HIV/AIDS or drug use. The short interval between HCV report and death suggests a need for earlier testing and improved treatment.

Matching HIV, tuberculosis, viral hepatitis, and sexually transmitted diseases surveillance data, 2000-2010: identification of infectious disease syndemics in New York City.

CONTEXT: In 2012, the New York City Department of Health and Mental Hygiene matched HIV, tuberculosis, viral hepatitis, and sexually transmitted disease surveillance data to identify the burden of infection with multiple diseases. METHODS: HIV, tuberculosis, hepatitis B, hepatitis C, chlamydia, gonorrhea, and syphilis surveillance data from 2000 to 2010 were matched using a deterministic method. Data on deaths from the Department of Health and Mental Hygiene's Office of Vital Statistics were also matched. RESULTS: The final data set contained 840,248 people; 13% had 2 or more diseases. People with a report of syphilis had the highest proportion of matches with other diseases (64%), followed by gonorrhea (52%), HIV (31%), tuberculosis (23%), hepatitis C (20%), chlamydia (16%), and hepatitis B (11%). CONCLUSIONS: The findings indicate several possible infectious disease syndemics in New York City and highlight the need to integrate surveillance data from different infectious disease programs. Conducting the match brought surveillance programs together to work collaboratively and has resulted in ongoing partnerships on programmatic activities that address multiple diseases.

Enrolling and retaining uninsured and underinsured populations in public health insurance through a service integration model in New York City.

Innovative strategies to identify uninsured and underinsured populations are critical to successful enrollment and retention in public health insurance. The New York City Department of Health and Mental Hygiene's Office of Health Insurance Services has partnered with the department's Early Intervention Program to implement a Service Integration Model to enroll special needs children, aged 0 to 3 years, into public health insurance. This model uses data from program databases and staff from children's programs to proactively identify uninsured and underinsured children and facilitate their enrollment into public health insurance. The model overcomes enrollment barriers by using consumer-friendly enrollment materials and one-on-one assistance, and shows the benefits of a comprehensive and collaborative approach to assisting families with enrollment into public health insurance.

Factors that influence adolescent reports of counseling by physicians on risky behavior.

PURPOSE: To determine factors that affect whether low-income adolescents report that their doctor talked with them about risky behavior. METHODS: Random digit-dial survey of low-income adolescents in New York City asking about depression, smoking, alcohol use, and sexual activity and the screening and counseling they received on these risk factors and risks during health visits. RESULTS: Prevalence of counseling by physicians was low, according to adolescent reports, ranging from 17% of adolescents counseled about depression to 52% about sexually transmitted diseases. Older adolescents were more likely than younger to receive counseling about all topics. In bivariate and multivariate models, having the risk factor was strongly associated with physicians counseling for depression (adjusted [adj.] OR = 4.42; p < 0.001); for sexual activity and counseling about condom use (adj. OR = 4.06; p < 0.01), and birth control (adj. OR = 2.76; p < 0.03). Still, many adolescents at risk had not received counseling. Many adolescents have not had a private and confidential visit with their provider. Having a private and confidential visit was also associated with receipt of counseling. CONCLUSIONS: Adolescents are not receiving sufficient counseling about risks and risky behavior, according to their own reports. There is need to improve delivery of counseling and ensure that private and confidential visits are provided to youth.