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

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          Abstract

          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. In NVSS data, confirmed or presumed COVID-19–associated deaths are assigned the International Classification of Diseases, Tenth Revision code U07.1 as a contributing or underlying cause of death on the death certificate. The underlying cause of death is the condition that began the chain of events ultimately leading to the person’s death. COVID-19 was the underlying cause for approximately 92% of COVID-19–associated deaths and was a contributing cause for approximately 8% during the investigation period ( 2 ). NVSS data in this report exclude deaths among residents of territories and foreign countries. Using NVSS data from May 1 through August 31, 2020, CDC tabulated the numbers and percentages of COVID-19–associated deaths by age, sex, race and ethnicity (categorized as Hispanic, White, Black, non-Hispanic Asian [Asian], non-Hispanic American Indian or Alaska Native [AI/AN], non-Hispanic Native Hawaiian or other Pacific Islander [NHPI], non-Hispanic multiracial [multiracial], and unknown), U.S. Census region, § and location of death (e.g., hospital, nursing home or long-term care facility, or residence). Because only 0.5% of COVID-19 decedents were either NHPI or multiracial, and counts <10 are suppressed in NVSS to maintain confidentiality, these groups were combined into one group for analyses. Age, race and ethnicity, and place of death were unknown for two (<0.01%), 465 (0.4%), and 46 (0.04%) deaths, respectively. To describe changes in demographic features over time, percentages of deaths among two age groups (≥65 years and <65 years), racial and ethnic groups, and U.S. Census region were calculated for each month. R statistical software (version 3.6.3; The R Foundation) was used to tabulate death counts and generate histograms. This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy. ¶ During May 1–August 31, 2020, a total of 114,411 COVID-19–associated deaths were reported to NVSS (Table). 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. Among decedents, the majority were male (53.3%), White (51.3%), aged ≥65 years (78.2%), and died in an inpatient health care setting (64.3%). Overall, 24.2% of decedents were Hispanic, 18.7% were Black, 3.5% were Asian, 1.3% were AI/AN, and 0.5% were either NHPI or multiracial. During the period studied, the largest percentage of COVID-19–associated deaths occurred in the South Census region (45.7%), followed by the Northeast (20.5%), the West (18.3%), and the Midwest (15.5%). Twenty-two percent of decedents died in a nursing home or long-term care facility. TABLE Demographic characteristics of persons who died because of COVID-19* (N = 114,411) — National Vital Statistics System (NVSS), United States, May 1–August 31, 2020 † Characteristic Deaths,§ % Age group, yrs <1 <0.1 1–4 <0.1 5–17 <0.1 18–29 0.5 30–39 1.4 40–49 3.5 50–64 16.4 65–74 21.7 75–84 26.0 ≥85 30.4 Unknown <0.1 Sex Male 53.3 Female 46.7 Other 0.0 Race/Ethnicity White, non-Hispanic 51.3 Hispanic or Latino 24.2 Black, non-Hispanic 18.7 Asian, non-Hispanic 3.5 American Indian or Alaska Native, non-Hispanic 1.3 Other, non-Hispanic¶ 0.5 Unknown race/ethnicity 0.4 U.S. Census region of residence South 45.7 Northeast 20.5 West 18.3 Midwest 15.5 Place of death Health care setting, inpatient 64.3 Nursing home or long-term care facility 21.5 Decedent's home 5.2 Hospice facility 3.7 Health care setting, outpatient or emergency department 3.1 Other 2.0 Health care setting, dead on arrival 0.1 Unknown <0.1 Abbreviation: COVID-19 = coronavirus disease 2019. * Deaths with confirmed or presumed COVID-19, coded to International Classification of Diseases, Tenth Revision code U07.1. These data exclude deaths among foreign residents and territories. † NVSS data from August are incomplete given reporting lags. § Percentages may not sum to 100 because of rounding. For two (<0.01%) COVID-19 deaths, age was unknown. Sex and region were known for all decedents. For 465 (0.4%) deaths, race or ethnicity were unknown. For 46 (0.04%) deaths, place of death was unknown. ¶ Other race/ethnicity includes persons who were non-Hispanic Native Hawaiian or other Pacific Islander or were non-Hispanic multiracial. During May–August 2020, the percentage of COVID-19–associated deaths occurring in the South increased from 23.4% in May to 62.7% in August, and in the West from 10.6% to 21.4%; the percentages occurring in the Northeast decreased from 44.2% in May to 4.0% in August, and in the Midwest declined from 21.8% to 11.8% (Figure 1). The percentage of decedents aged ≥65 years decreased from 81.8% to 77.6%, and the percentage of deaths occurring in nursing homes or long-term care facilities decreased from 29.8% to 16.6% (Figure 1). FIGURE 1 Monthly COVID-19–associated deaths* as a percentage of all deaths, by U.S. Census region, all ages (A), and for persons aged ≥65 years or persons of any age who died in a nursing home or long-term care facility (B) (N = 114,411) — National Vital Statistics System, United States, May 1–August 31, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * Age data were missing for two (<0.01%) COVID-19 deaths, and place of death data were missing for 46 (0.04%) deaths. Total numbers of deaths might vary because of suppression of counts with <10 deaths. The figure is a line chart showing monthly COVID-19–associated deaths as a percentage of all deaths, by U.S. Census region, all ages, and for persons aged ≥65 years or persons of any age who died in a nursing home or long-term care facility (N = 114,411), using data from the National Vital Statistics System, in the United States, during May 1–August 31, 2020. From May to August, the percentage of decedents who were White decreased from 56.9% to 51.5%, and the percentage who were Black decreased from 20.3% to 17.4%, whereas the percentage who were Hispanic increased from 16.3% to 26.4% (Figure 2). Hispanics were the only racial and ethnic group among whom the overall percentage of deaths increased. Among persons aged ≥65 years, the monthly percentage of Hispanic decedents increased in the South (from 10.3% to 21.7%) and West (from 29.6% to 35.4%) and decreased in the Northeast (from 11.3% to 9.3%) and Midwest (from 7.8% to 4.2%). The monthly percentage of Hispanic decedents aged <65 years increased in the South (from 29.2% to 38.1%) and West (from 51.8% to 62.3%) and decreased in the Northeast (from 34.9% to 30.7%) and Midwest (31.1% to 20.4%) (Supplementary Figure, https://stacks.cdc.gov/view/cdc/95229). FIGURE 2 Monthly deaths, by race/ethnicity* as a percentage of all COVID-19–associated deaths (N = 114,411) — National Vital Statistics System, United States, May 1–August 31, 2020 Abbreviations: AI/AN = American Indian or Alaska Native; COVID-19 = coronavirus disease 2019; NH = non-Hispanic; NHPI = Native Hawaiian or other Pacific Islander. * Race or ethnicity data were unknown for 465 (0.4%) deaths. Total numbers of deaths might vary because of suppression of counts with <10 deaths. The figure is a bar chart showing monthly deaths, by race/ethnicity as a percentage of all COVID-19–associated deaths (N = 114,411), using data from the National Vital Statistics System, in the United States, during May 1–August 31, 2020. Discussion Based on NVSS data on 114,411 persons who died from COVID-19 in the United States during May–August 2020, the predominant U.S. Census regions shifted from the Northeast to the South and West. The majority of COVID-19–associated deaths occurred among White persons (51.3%), but Black and Hispanic persons were disproportionately represented. Although a small decrease (2.9 percentage points between May and August) in decedents who were Black was observed, Black persons still accounted for 18.7% of overall deaths despite representing just 12.5% of the U.S. population ( 3 ). Similarly, Hispanic persons were disproportionately represented among decedents: 24.2% of decedents were Hispanic compared with 18.5% of the U.S. population. In addition, the percentage of decedents who were Hispanic increased 10.1 percentage points from May through August. Whereas Hispanic persons accounted for 14% of COVID-19–associated deaths in the United States during February 12–May 18, 2020 ( 1 ), that percentage increased to approximately 25% in August. Although there has been a geographic shift in COVID-19–associated deaths from the Northeast to the West and South, where Hispanic persons account for a higher percentage of the population, this analysis found that ethnic disparities among decedents in the West and South increased during May–August, 2020, suggesting that the geographic shift alone does not entirely account for the increase in percentage of Hispanic decedents nationwide. Disparities in COVID-19 incidence and deaths among Hispanic persons and other underrepresented racial and ethnic groups are well documented ( 4 – 6 ) and might be related to increased risk for exposure to SARS-CoV-2, the virus that causes COVID-19. Inequities in the social determinants of health can lead to increased risk for SARS-CoV-2 exposure among some racial and ethnic groups. For example, persons from underrepresented racial and ethnic groups might be more likely to live in multigenerational and multifamily households, reside in congregate living environments, hold jobs requiring in-person work (e.g., meatpacking, agriculture, service, and health care), have limited access to health care, or experience discrimination ( 5 , 6 ). Differences in the prevalence of underlying conditions (e.g., diabetes and obesity) among racial and ethnic groups might also be associated with increased susceptibility to COVID-19–associated complications and death ( 4 ). The shift in COVID-19–associated deaths during May–August 2020 from the Northeast (where 17.1% of the U.S. population resides) into the South and West (where 38.3% and 23.9% of the U.S. population resides, respectively)** is consistent with recent findings documenting the emergence of COVID-19 hotspots †† in these regions during June–July 2020 ( 7 ). The decreasing percentage of deaths occurring among persons aged ≥65 years and persons in nursing homes, which were important sites of COVID-19–associated deaths early in the pandemic, suggests a continued shift toward noninstitutionalized and younger populations. The observed geographic shifts in COVID-19–associated deaths might be related to differential implementation of community mitigation efforts throughout the nation, including earlier reopening efforts in selected jurisdictions. To prevent the spread of COVID-19, CDC continues to recommend the use of masks, frequent handwashing, and maintenance of social distancing, including avoidance of large gatherings ( 8 ). The findings in this report are subject to at least two limitations. First, NVSS provisional death data are continually updated and subject to delays. Therefore, this report likely underestimates the number of deaths that occurred, particularly during August 2020, for which data are less complete than previous months. Furthermore, in focusing only on COVID-19–associated deaths captured by NVSS, this report did not address long-term morbidity faced by some persons who survive COVID-19 infections, nor does it account for deaths and morbidity related to the indirect effects of interrupted health care and socioeconomic disruption caused by the pandemic ( 9 ). For example, one report indicated that by June 30, 2020, an estimated 41% of U.S. adults had delayed or avoided medical care because of concerns about the pandemic, including 12% who reported having avoided urgent or emergency care ( 10 ). Despite these limitations, this report provides information on how demographic and geographic factors have changed among COVID-19–associated deaths during May–August 2020. Racial and ethnic disparities among COVID-19 decedents have persisted over the course of the pandemic and continue to increase 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 so as to minimize subsequent mortality. Summary What is already known about this topic? Persons aged ≥65 years and members of minority racial and ethnic groups are disproportionately represented among COVID-19–associated deaths. What is added by this report? Analysis of 114,411 COVID-19–associated deaths reported to National Vital Statistics System during May–August 2020, found that 51.3% of decedents were non-Hispanic White, 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black. The percentage of Hispanic decedents increased from 16.3% in May to 26.4% in August. What are the implications for public health practice? These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups so as to minimize subsequent mortality.

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            Delay or Avoidance of Medical Care Because of COVID-19–Related Concerns — United States, June 2020

            Temporary disruptions in routine and nonemergency medical care access and delivery have been observed during periods of considerable community transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) ( 1 ). However, medical care delay or avoidance might increase morbidity and mortality risk associated with treatable and preventable health conditions and might contribute to reported excess deaths directly or indirectly related to COVID-19 ( 2 ). To assess delay or avoidance of urgent or emergency and routine medical care because of concerns about COVID-19, a web-based survey was administered by Qualtrics, LLC, during June 24–30, 2020, to a nationwide representative sample of U.S. adults aged ≥18 years. Overall, an estimated 40.9% of U.S. adults have avoided medical care during the pandemic because of concerns about COVID-19, including 12.0% who avoided urgent or emergency care and 31.5% who avoided routine care. The estimated prevalence of urgent or emergency care avoidance was significantly higher among the following groups: unpaid caregivers for adults* versus noncaregivers (adjusted prevalence ratio [aPR] = 2.9); persons with two or more selected underlying medical conditions † versus those without those conditions (aPR = 1.9); persons with health insurance versus those without health insurance (aPR = 1.8); non-Hispanic Black (Black) adults (aPR = 1.6) and Hispanic or Latino (Hispanic) adults (aPR = 1.5) versus non-Hispanic White (White) adults; young adults aged 18–24 years versus adults aged 25–44 years (aPR = 1.5); and persons with disabilities § versus those without disabilities (aPR = 1.3). Given this widespread reporting of medical care avoidance because of COVID-19 concerns, especially among persons at increased risk for severe COVID-19, urgent efforts are warranted to ensure delivery of services that, if deferred, could result in patient harm. Even during the COVID-19 pandemic, persons experiencing a medical emergency should seek and be provided care without delay ( 3 ). During June 24–30, 2020, a total of 5,412 (54.7%) of 9,896 eligible adults ¶ completed web-based COVID-19 Outbreak Public Evaluation Initiative surveys administered by Qualtrics, LLC.** The Human Research Ethics Committee of Monash University (Melbourne, Australia) reviewed and approved the study protocol on human subjects research. This activity was also reviewed by CDC and was conducted consistent with applicable federal law and CDC policy. †† Respondents were informed of the study purposes and provided electronic consent before commencement, and investigators received anonymized responses. The 5,412 participants included 3,683 (68.1%) first-time respondents and 1,729 (31.9%) persons who had completed a related survey §§ during April 2–8, 2020. Among the 5,412 participants, 4,975 (91.9%) provided complete data for all variables in this analysis. Quota sampling and survey weighting ¶¶ were employed to improve cohort representativeness of the U.S. population by gender, age, and race/ethnicity. Respondents were asked “Have you delayed or avoided medical care due to concerns related to COVID-19?” Delay or avoidance was evaluated for emergency (e.g., care for immediate life-threatening conditions), urgent (e.g., care for immediate non–life-threatening conditions), and routine (e.g., annual check-ups) medical care. Given the potential for variation in interpretation of whether conditions were life-threatening, responses for urgent and emergency care delay or avoidance were combined for analysis. Covariates included gender; age; race/ethnicity; disability status; presence of one or more selected underlying medical conditions known to increase risk for severe COVID-19; education; essential worker status***; unpaid adult caregiver status; U.S. census region; urban/rural classification ††† ; health insurance status; whether respondents knew someone who had received a positive SARS-CoV-2 test result or had died from COVID-19; and whether the respondents believed they were at high risk for severe COVID-19. Comparisons within all these subgroups were evaluated using multivariable Poisson regression models §§§ with robust standard errors to estimate prevalence ratios adjusted for all covariates, 95% confidence intervals, and p-values to evaluate statistical significance (α = 0.05) using the R survey package (version 3.29) and R software (version 4.0.2; The R Foundation). As of June 30, 2020, among 4,975 U.S. adult respondents, 40.9% reported having delayed or avoided any medical care, including urgent or emergency care (12.0%) and routine care (31.5%), because of concerns about COVID-19 (Table 1). Groups of persons among whom urgent or emergency care avoidance exceeded 20% and among whom any care avoidance exceeded 50% included adults aged 18–24 years (30.9% for urgent or emergency care; 57.2% for any care), unpaid caregivers for adults (29.8%; 64.3%), Hispanic adults (24.6%; 55.5%), persons with disabilities (22.8%; 60.3%), persons with two or more selected underlying medical conditions (22.7%; 54.7%), and students (22.7%; 50.3%). One in four unpaid caregivers reported caring for adults who were at increased risk for severe COVID-19. TABLE 1 Estimated prevalence of delay or avoidance of medical care because of concerns related to COVID-19, by type of care and respondent characteristics — United States, June 30, 2020 Characteristic No. (%)† Type of medical care delayed or avoided* Urgent or emergency Routine Any %† P-value§ %† P-value§ %† P-value§ All respondents 4,975 (100) 12.0 — 31.5 — 40.9 — Gender Female 2,528 (50.8) 11.7 0.598 35.8 <0.001 44.9 <0.001 Male 2,447 (49.2) 12.3 27.0 36.7 Age group, yrs 18–24 650 (13.1) 30.9 <0.001 29.6 0.072 57.2 <0.001 25–44 1,740 (35.0) 14.9 34.2 44.8 45–64 1,727 (34.7) 5.7 30.0 34.5 ≥65 858 (17.3) 4.4 30.3 33.5 Race/Ethnicity White, non-Hispanic 3,168 (63.7) 6.7 <0.001 30.9 0.020 36.2 <0.001 Black, non-Hispanic 607 (12.2) 23.3 29.7 48.1 Asian, non-Hispanic 238 (4.8) 8.6 31.3 37.7 Other race or multiple races, non-Hispanic¶ 150 (3.0) 15.5 23.9 37.3 Hispanic, any race or races 813 (16.3) 24.6 36.4 55.5 Disability** Yes 1,108 (22.3) 22.8 <0.001 42.9 <0.001 60.3 <0.001 No 3,867 (77.7) 8.9 28.2 35.3 Underlying medical condition†† No 2,537 (51.0) 8.2 <0.001 27.9 <0.001 34.7 <0.001 One 1,328 (26.7) 10.4 33.0 41.2 Two or more 1,110 (22.3) 22.7 37.7 54.7 2019 household income, USD <25,000 665 (13.4) 13.9 0.416 31.2 0.554 42.8 0.454 25,000–49,999 1,038 (20.9) 11.1 30.9 38.6 50,000–99,999 1,720 (34.6) 12.5 30.5 41.1 ≥100,000 1,552 (31.2) 11.2 33.0 41.4 Education Less than high school diploma 65 (1.3) 15.6 0.442 24.7 0.019 37.9 0.170 High school diploma 833 (16.7) 12.3 28.1 38.1 Some college 1,302 (26.2) 13.6 29.7 40.3 Bachelor's degree 1,755 (35.3) 11.2 34.8 43.6 Professional degree 1,020 (20.5) 10.9 31.2 39.5 Employment status Employed 3,049 (61.3) 14.6 <0.001 31.5 0.407 43.3 <0.001 Unemployed 630 (12.7) 8.7 34.4 39.5 Retired 1,129 (22.7) 5.3 29.9 33.8 Student 166 (3.3) 22.7 30.5 50.3 Essential worker status§§ Essential worker 1,707 (34.3) 19.5 <0.001 32.4 0.293 48.0 <0.001 Nonessential worker 1,342 (27.0) 8.4 30.3 37.3 Unpaid caregiver status¶¶ Unpaid caregiver for adults 1,344 (27.0) 29.8 <0.001 41.0 <0.001 64.3 <0.001 Not unpaid caregiver for adults 3,631 (73.0) 5.4 27.9 32.2 U.S. Census region*** Northeast 1,122 (22.6) 11.0 0.008 33.9 0.203 42.5 0.460 Midwest 936 (18.8) 8.5 32.0 38.7 South 1,736 (34.9) 13.9 29.6 40.7 West 1,181 (23.7) 13.0 31.5 41.5 Rural/Urban classification††† Urban 4,411 (88.7) 12.3 0.103 31.5 0.763 41.2 0.216 Rural 564 (11.3) 9.4 30.9 38.2 Health insurance status Yes 4,577 (92.0) 12.4 0.036 32.6 <0.001 42.3 <0.001 No 398 (8.0) 7.8 18.4 24.8 Know someone with positive test results for SARS-CoV-2§§§ Yes 989 (19.9) 8.8 0.004 40.7 <0.001 46.6 <0.001 No 3,986 (80.1) 12.8 29.2 39.5 Knew someone who died from COVID-19 Yes 364 (7.3) 10.1 0.348 41.4 <0.001 46.3 0.048 No 4,611 (92.7) 12.2 30.7 40.5 Believed to be in group at high risk for severe COVID-19 Yes 981 (19.7) 10.0 0.050 42.5 <0.001 49.4 <0.001 No 3,994 (80.3) 12.5 28.8 38.8 Abbreviations: CI = confidence interval; COVID-19 = coronavirus disease 2019; USD = U.S. dollars. * The types of medical care avoidance are not mutually exclusive; respondents had the option to indicate that they had delayed or avoided more than one type of medical care (i.e., routine medical care and urgent/emergency medical care). † Statistical raking and weight trimming were employed to improve the cross-sectional June cohort representativeness of the U.S. population by gender, age, and race/ethnicity according to the 2010 U.S. Census. § The Rao-Scott adjusted Pearson chi-squared test was used to test for differences in observed and expected frequencies among groups by characteristic for avoidance of each type of medical care (e.g., whether avoidance of routine medical care differs significantly by gender). Statistical significance was evaluated at a threshold of α = 0.05. ¶ “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ** Persons who had a disability were defined as such based on a qualifying response to either one of two questions: “Are you limited in any way in any activities because of physical, mental, or emotional condition?” and “Do you have any health conditions that require you to use special equipment, such as a cane, wheelchair, special bed, or special telephone?” https://www.cdc.gov/brfss/questionnaires/pdf-ques/2015-brfss-questionnaire-12-29-14.pdf. †† Selected underlying medical conditions known to increase the risk for severe COVID-19 included in this analysis were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. §§ Essential worker status was self-reported. ¶¶ Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years at any time in the last 3 months. Examples provided to survey respondents included helping with personal needs, household chores, health care tasks, managing a person’s finances, taking them to a doctor’s appointment, arranging for outside services, and visiting regularly to see how they are doing. *** Region classification was determined by using the U.S. Census Bureau’s Census Regions and Divisions. https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. ††† Rural-urban classification was determined by using self-reported ZIP codes according to the Federal Office of Rural Health Policy definition of rurality. https://www.hrsa.gov/rural-health/about-us/definition/datafiles.html. §§§ For this question, respondents were asked to select the following statement, if applicable: “I know someone who has tested positive for COVID-19.” In the multivariable Poisson regression models, differences within groups were observed for urgent or emergency care avoidance (Figure) and any care avoidance (Table 2). Adjusted prevalence of urgent or emergency care avoidance was significantly higher among unpaid caregivers for adults versus noncaregivers (2.9; 2.3–3.6); persons with two or more selected underlying medical conditions versus those without those conditions (1.9; 1.5–2.4); persons with health insurance versus those without health insurance (1.8; 1.2–2.8); Black adults (1.6; 1.3–2.1) and Hispanic adults (1.5; 1.2–2.0) versus White adults; young adults aged 18–24 years versus adults aged 25–44 years (1.5; 1.2–1.8); and persons with disabilities versus those without disabilities (1.3; 1.1–1.5). Avoidance of urgent or emergency care was significantly lower among adults aged ≥45 years than among younger adults. FIGURE Adjusted prevalence ratios* , † for characteristics § , ¶ , ** , †† associated with delay or avoidance of urgent or emergency medical care because of concerns related to COVID-19 — United States, June 30, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * Comparisons within subgroups were evaluated using Poisson regressions used to calculate a prevalence ratio adjusted for all characteristics shown in figure. † 95% confidence intervals indicated with error bars. § “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ¶ Selected underlying medical conditions known to increase the risk for severe COVID-19 were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. ** Essential worker status was self-reported. For the adjusted prevalence ratios, essential workers were compared with all other respondents (including those who were nonessential workers, retired, unemployed, and students). †† Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years to help them take care of themselves at any time in the last 3 months. The figure is a forest plot showing the adjusted prevalence ratios for characteristics associated with delay or avoidance of urgent or emergency medical care because of concerns related to COVID-19, in the United States, as of June 30, 2020. TABLE 2 Characteristics associated with delay or avoidance of any medical care because of concerns related to COVID-19 — United States, June 30, 2020 Characteristic Weighted* no. Avoided or delayed any medical care aPR† (95% CI†) P-value† All respondents 4,975 — — — Gender Female 2,528 Referent — — Male 2,447 0.81 (0.75–0.87)§ <0.001 Age group, yrs 18–24 650 1.12 (1.01–1.25)§ 0.035 25–44 1,740 Referent — — 45–64 1,727 0.80 (0.72–0.88)§ <0.001 ≥65 858 0.72 (0.64–0.81)§ <0.001 Race/Ethnicity White, non-Hispanic 3,168 Referent — — Black, non-Hispanic 607 1.07 (0.96–1.19) 0.235 Asian, non-Hispanic 238 1.04 (0.91–1.18) 0.567 Other race or multiple races, non-Hispanic¶ 150 0.87 (0.71–1.07) 0.196 Hispanic, any race or races 813 1.15 (1.03–1.27)§ 0.012 Disability** Yes 1,108 1.33 (1.23–1.43)§ <0.001 No 3,867 Referent — — Underlying medical condition†† No 2,537 Referent — — One 1,328 1.15 (1.05–1.25)§ 0.004 Two or more 1,110 1.31 (1.20–1.42)§ <0.001 Education Less than high school diploma 65 0.72 (0.53–0.98)§ 0.037 High school diploma 833 0.79 (0.71–0.89)§ <0.001 Some college 1,302 0.85 (0.78–0.93)§ 0.001 Bachelor's degree 1,755 Referent — — Professional degree 1,020 0.90 (0.82–0.98)§ 0.019 Essential workers vs others§§ Essential workers 1,707 1.00 (0.92–1.09) 0.960 Other respondents (nonessential workers, retired persons, unemployed persons, and students) 3,268 Referent — — Unpaid caregiver status¶¶ Unpaid caregiver for adults 1,344 1.64 (1.52–1.78)§ <0.001 Not unpaid caregiver for adults 3,631 Referent — — U.S. Census region*** Northeast 1,122 Referent — — Midwest 936 0.93 (0.83–1.04) 0.214 South 1,736 0.90 (0.82–0.99)§ 0.028 West 1,181 0.99 (0.89–1.09) 0.808 Rural/Urban classification††† Urban 4,411 1.00 (0.89–1.12) 0.993 Rural 564 Referent — — Health insurance status Yes 4,577 1.61 (1.31–1.98)§ <0.001 No 398 Referent — — Know someone with positive test results for SARS-CoV-2§§§ Yes 989 1.22 (1.12–1.33)§ <0.001 No 3,986 Referent — — Knew someone who died from COVID-19 Yes 364 0.99 (0.88–1.12) 0.860 No 4,611 Referent — — Believed to be in a group at high risk for severe COVID-19 Yes 981 1.33 (1.23–1.44)§ <0.001 No 3,994 Referent — — Abbreviations: aPR = adjusted prevalence ratio; CI = confidence interval; COVID-19 = coronavirus disease 2019. * Statistical raking and weight trimming were employed to improve the cross-sectional June cohort representativeness of the U.S. population by gender, age, and race/ethnicity according to the 2010 U.S. Census. † Comparisons within subgroups were evaluated using Poisson regressions used to calculate a prevalence ratio adjusted for all characteristics listed, as well as a 95% CI and p-value. Statistical significance was evaluated at a threshold of α = 0.05. § P-value calculated using Poisson regression among respondents within a characteristic is statistically significant at levels of p<0.05. ¶ “Other” race includes American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or Other. ** Persons who had a disability were defined based on a qualifying response to either one of two questions: “Are you limited in any way in any activities because of physical, mental, or emotional condition?” and “Do you have any health conditions that require you to use special equipment, such as a cane, wheelchair, special bed, or special telephone?” https://www.cdc.gov/brfss/questionnaires/pdf-ques/2015-brfss-questionnaire-12-29-14.pdf. †† Selected underlying medical conditions known to increase the risk for severe COVID-19 were obesity, diabetes, high blood pressure, cardiovascular disease, and any type of cancer. Obesity is defined as body mass index ≥30 kg/m2 and was calculated from self-reported height and weight (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html). The remaining conditions were assessed using the question “Have you ever been diagnosed with any of the following conditions?” with response options of 1) “Never”; 2) “Yes, I have in the past, but don’t have it now”; 3) “Yes I have, but I do not regularly take medications or receive treatment”; and 4) “Yes I have, and I am regularly taking medications or receiving treatment.” Respondents who answered that they have been diagnosed and chose either response 3 or 4 were considered as having the specified medical condition. §§ Essential worker status was self-reported. For the adjusted prevalence ratios, essential workers were compared with all other respondents (including those who were nonessential workers, retired, unemployed, and students). ¶¶ Unpaid caregiver status was self-reported. Unpaid caregivers for adults were defined as having provided unpaid care to a relative or friend aged ≥18 years at any time in the last 3 months. Examples provided to survey respondents included helping with personal needs, household chores, health care tasks, managing a person’s finances, taking them to a doctor’s appointment, arranging for outside services, and visiting regularly to see how they are doing. *** Region classification was determined by using the U.S. Census Bureau’s Census Regions and Divisions. https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. ††† Rural/urban classification was determined by using self-reported ZIP codes according to the Federal Office of Rural Health Policy definition of rurality. https://www.hrsa.gov/rural-health/about-us/definition/datafiles.html. §§§ For this question, respondents were asked to select the following statement, if applicable: “I know someone who has tested positive for COVID-19.” Discussion As of June 30, 2020, an estimated 41% of U.S. adults reported having delayed or avoided medical care during the pandemic because of concerns about COVID-19, including 12% who reported having avoided urgent or emergency care. These findings align with recent reports that hospital admissions, overall emergency department (ED) visits, and the number of ED visits for heart attack, stroke, and hyperglycemic crisis have declined since the start of the pandemic ( 3 – 5 ), and that excess deaths directly or indirectly related to COVID-19 have increased in 2020 versus prior years ( 2 ). Nearly one third of adult respondents reported having delayed or avoided routine medical care, which might reflect adherence to community mitigation efforts such as stay-at-home orders, temporary closures of health facilities, or additional factors. However, if routine care avoidance were to be sustained, adults could miss opportunities for management of chronic conditions, receipt of routine vaccinations, or early detection of new conditions, which might worsen outcomes. Avoidance of both urgent or emergency and routine medical care because of COVID-19 concerns was highly prevalent among unpaid caregivers for adults, respondents with two or more underlying medical conditions, and persons with disabilities. For caregivers who reported caring for adults at increased risk for severe COVID-19, concern about exposure of care recipients might contribute to care avoidance. Persons with underlying medical conditions that increase their risk for severe COVID-19 ( 6 ) are more likely to require care to monitor and treat these conditions, potentially contributing to their more frequent report of avoidance. Moreover, persons at increased risk for severe COVID-19 might have avoided health care facilities because of perceived or actual increased risk of exposure to SARS-CoV-2, particularly at the onset of the pandemic. However, health care facilities are implementing important safety precautions to reduce the risk of SARS-CoV-2 infection among patients and personnel. In contrast, delay or avoidance of care might increase risk for life-threatening medical emergencies. In a recent study, states with large numbers of COVID-19–associated deaths also experienced large proportional increases in deaths from other underlying causes, including diabetes and cardiovascular disease ( 7 ). For persons with disabilities, accessing medical services might be challenging because of disruptions in essential support services, which can result in adverse health outcomes. Medical services for persons with disabilities might also be disrupted because of reduced availability of accessible transportation, reduced communication in accessible formats, perceptions of SARS-CoV-2 exposure risk, and specialized needs that are difficult to address with routine telehealth delivery during the pandemic response. Increasing accessibility of medical and telehealth services ¶¶¶ might help prevent delay of needed care. Increased prevalences of reported urgent or emergency care avoidance among Black adults and Hispanic adults compared with White adults are especially concerning given increased COVID-19-associated mortality among Black adults and Hispanic adults ( 8 ). In the United States, the age-adjusted COVID-19 hospitalization rates are approximately five times higher among Black persons and four times higher among Hispanic persons than are those among White persons ( 9 ). Factors contributing to racial and ethnic disparities in SARS-CoV-2 exposure, illness, and mortality might include long-standing structural inequities that influence life expectancy, including prevalence and underlying medical conditions, health insurance status, and health care access and utilization, as well as work and living circumstances, including use of public transportation and essential worker status. Communities, health care systems, and public health agencies can foster equity by working together to ensure access to information, testing, and care to assure maintenance and management of physical and mental health. The higher prevalence of medical care delay or avoidance among respondents with health insurance versus those without insurance might reflect differences in medical care-seeking behaviors. Before the pandemic, persons without insurance sought medical care much less frequently than did those with insurance ( 10 ), resulting in fewer opportunities for medical care delay or avoidance. The findings in this report are subject to at least five limitations. First, self-reported data are subject to recall, response, and social desirability biases. Second, the survey did not assess reasons for COVID-19–associated care avoidance, such as adherence to public health recommendations; closure of health care provider facilities; reduced availability of public transportation; fear of exposure to infection with SARS-CoV-2; or availability, accessibility, and acceptance or recognition of telemedicine as a means of providing care in lieu of in-person services. Third, the survey did not assess baseline patterns of care-seeking or timing or duration of care avoidance. Fourth, perceptions of whether a condition was life-threatening might vary among respondents. Finally, although quota sampling methods and survey weighting were employed to improve cohort representativeness, this web-based survey might not be fully representative of the U.S. population for income, educational attainment, and access to technology. However, the findings are consistent with reported declines in hospital admissions and ED visits during the pandemic ( 3 – 5 ). CDC has issued guidance to assist persons at increased risk for severe COVID-19 in staying healthy and safely following treatment plans**** and to prepare health care facilities to safely deliver care during the pandemic. †††† Additional public outreach in accessible formats tailored for diverse audiences might encourage these persons to seek necessary care. Messages could highlight the risks of delaying needed care, especially among persons with underlying medical conditions, and the importance of timely emergency care. Patient concerns related to potential exposure to SARS-CoV-2 in health care settings could be addressed by describing facilities’ precautions to reduce exposure risk. Further exploration of underlying reasons for medical care avoidance is needed, including among persons with disabilities, persons with underlying health conditions, unpaid caregivers for adults, and those who face structural inequities. If care were avoided because of concern about SARS-CoV-2 exposure or if there were closures or limited options for in-person services, providing accessible telehealth or in-home health care could address some care needs. Even during the COVID-19 pandemic, persons experiencing a medical emergency should seek and be provided care without delay ( 3 ). Summary What is already known about this topic? Delayed or avoided medical care might increase morbidity and mortality associated with both chronic and acute health conditions. What is added by this report? By June 30, 2020, because of concerns about COVID-19, an estimated 41% of U.S. adults had delayed or avoided medical care including urgent or emergency care (12%) and routine care (32%). Avoidance of urgent or emergency care was more prevalent among unpaid caregivers for adults, persons with underlying medical conditions, Black adults, Hispanic adults, young adults, and persons with disabilities. What are the implications for public health practice? Understanding factors associated with medical care avoidance can inform targeted care delivery approaches and communication efforts encouraging persons to safely seek timely routine, urgent, and emergency care.
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              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. This analysis used cumulative county-level data during February–June 2020, reported to CDC by jurisdictions or extracted from state and county websites and disaggregated by race/ethnicity. Case counts, which included both probable and laboratory-confirmed cases, were cross-referenced with counts from the HHS Protect database (https://protect-public.hhs.gov/). Counties missing race data for more than half of reported cases (126) were excluded from the analysis. § The proportion of the population for each county by race/ethnicity was calculated using data obtained from CDC WONDER ( 6 ). For each underrepresented racial/ethnic group, disparities were defined as a difference of ≥5% between the proportion of cases and the proportion of the population consisting of that group or a ratio of ≥1.5 for the proportion of cases to the proportion of the population in that racial/ethnic group. The county-level differences and ratios between proportion of cases and the proportion of population were used as a base for a simulation accounting for missing data using different assumptions of racial/ethnic distribution of cases with unknown race/ethnicity. An intercept-only logistic regression model was estimated for each race/ethnicity category and county to obtain the intercept regression coefficient and standard error. The simulation used the logistic regression-estimated coefficient and standard error to produce an estimated mean and confidence interval (CI) for the percentage difference between and ratio of proportions of cases and population. This simulation was done for each racial/ethnic group within each county. The lower bound of the CI was used to identify counties with disparities (as defined by percentage differences or ratio). The mean of the estimated differences and mean of the estimated ratios were calculated for all counties with disparities. Analyses were conducted using SAS software (version 9.4; SAS Institute). During June 5–18, a total of 205 counties in 33 states were identified as hotspots. These counties have a combined total population of 93.5 million persons, and approximately 535,000 cumulative probable and confirmed COVID-19 cases. Among the 205 identified hotspot counties, 79 (38.5%) counties in 22 states, with a combined population of 27.5 million persons and approximately 162,000 COVID-19 cases, had race data available for ≥50% of cumulative cases and were included in the analysis (range = 51.3%–97.4%). Disparities in cases were identified among underrepresented racial/ethnic groups in 76 (96.2%) analyzed counties (Table 1). Disparities among Hispanic populations were identified in approximately three quarters of hotspot counties (59 of 79, 74.7%) with approximately 3.5 million Hispanic residents (Table 2). Approximately 2.0 million black persons reside in 22 (27.8%) hotspot counties where black residents were disproportionately affected by COVID-19, approximately 61,000 AI/AN persons live in three (3.8%) hotspot counties where AI/AN residents were disproportionately affected by COVID-19, nearly 36,000 Asian persons live in four (5.1%) hotspot counties where Asian residents were disproportionately affected by COVID-19, and approximately 31,000 NHPI persons live in 19 (24.1%) hotspot counties where NHPI populations were disproportionately affected by COVID-19. TABLE 1 Total population and racial/ethnic disparities* in cumulative COVID-19 cases among 79 counties identified as hotspots during June 5–18, 2020, with any disparity identified — 22 states, February–June 2020 State No. of persons living in analyzed hotspot counties* No. of (col %) hotspot counties analyzed† No. of counties with disparities in COVID-19 cases among each racial/ethnic group§ Hispanic Black NHPI Asian AI/AN Alabama 500,000–1,000,000 1 (1.3) — 1 — — — Arizona 1,000,000–3,000,000 5 (6.3) 3 — — — 3 Arkansas 500,000–1,000,000 4 (5.1) 4 — 2 — — California 1,000,000–3,000,000 1 (1.3) 1 — — — — Colorado 100,000–500,000 1 (1.3) 1 — 1 — — Florida >3,000,000 6 (7.6) 3 2 — — — Georgia 100,000–500,000 1 (1.3) 1 — — — — Iowa 50,000–100,000 1 (1.3) 1 — — — — Kansas 500,000–1,000,000 2 (2.5) 2 — 2 — — Massachusetts 500,000–1,000,000 2 (2.5) — 2 — — — Michigan 1,000,000–3,000,000 5 (6.3) — 5 1 — — Minnesota 3,000,000 18 (22.8) 18 — 3 1 — Ohio 1,000,000–3,000,000 3 (3.8) 3 2 — 1 — Oregon 1,000,000–3,000,000 6 (7.6) 6 1 4 1 — South Carolina 1,000,000–3,000,000 9 (11.4) 6 4 2 — — Tennessee 500,000–1,000,000 3 (3.8) 3 — — — — Texas 500,000–1,000,000 2 (2.5) — 1 — — — Utah 1,000,000–3,000,000 4 (5.1) 4 1 3 — — Virginia <50,000 1 (1.3) — — — — — Wisconsin 100,000–500,000 1 (1.3) 1 — — — — Total (approximate) 27,500,000 79 (100) 59 22 19 4 3 Abbreviations: AI/AN = American Indian/Alaska Native; COVID-19 = coronavirus disease 2019; NHPI = Native Hawaiian/other Pacific Islanders. * Disparities were defined as percentage 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. † Counties with race/ethnicity data available for ≥50% of cases. § Racial/ethnic groups are not mutually exclusive in a given county. TABLE 2 Number of persons in each racial/ethnic group living in 79 counties identified as hotspots during June 5–18, 2020 with disparities* — 22 states, February–June 2020 Racial/Ethnic group No. (%)† of counties with disparities§ identified Approximate no. of persons living in hotspot counties with disparities Hispanic/Latino 59 (74.7) 3,500,000 Black/African American 22 (27.8) 2,000,000 American Indian/Alaska Native 3 (3.8) 61,000 Asian 4 (5.1) 36,000 Native Hawaiian/Other Pacific Islander 19 (24.1) 31,000 Total — 5,628,000 Abbreviation: COVID-19 = coronavirus disease 2019. * Disparities were defined as percentage 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. † Percentage of the 79 counties. § Disparities are in respective racial/ethnic groups and are not mutually exclusive; some counties had disparities in more than one racial/ethnic group. The mean of the estimated differences between the proportion of cases and proportion of the population consisting of each underrepresented racial/ethnic group in all counties with disparities ranged from 4.5% (NHPI) to 39.3% (AI/AN) (Table 3). The mean of the estimated ratio of the proportion of cases to the proportions of population were also generated for each underrepresented racial/ethnic group and ranged from 2.3 (black) to 8.5 (NHPI). TABLE 3 Proportion of cumulative COVID-19 cases compared with proportion of population in 79 counties identified as hotspots during June 5–18, 2020 with racial/ethnic disparities* — 22 states February–June 2020 Racial/Ethnic group Mean of estimated differences, † % (range) Mean of estimated ratios of proportion of cases to proportion of population§ (range) Hispanic/Latino 30.2 (8.0–68.2) 4.4 (1.2–14.6) Black/African American 14.5 (2.3–31.7) 2.3 (1.2–7.0) American Indian/Alaska Native 39.3 (16.4–57.9) 4.2 (1.9–6.4) Asian 4.7 (2.7–6.8) 2.9 (2.0–4.7) Native Hawaiian/Other Pacific Islander 4.5 (0.1–31.5) 8.5 (2.7–18.4) Abbreviation: COVID-19 = coronavirus disease 2019.
* Disparities were defined as percentage 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. † The mean of the estimated differences between the proportion of cases in a given racial/ethnic group and the proportion of persons in that racial/ethnic group in the overall population among all counties with disparities identified by the analysis. For example, if Hispanic/Latino persons make up 20% of the population in a given county and 30% of the cases in that county, then the difference would be 10% and the county is considered to have a disparity. § The ratio of the estimated proportion of cases to the proportion of population for each racial/ethnic group among all counties with disparities identified by the analysis. For example, if American Indian/Alaskan Native persons made up 0.5% of the population in a given county and 1.5% of the cases in that county, then the ratio of proportions would be 3.0, and the county is considered to have a disparity. Discussion These findings illustrate the disproportionate incidence of COVID-19 among communities of color, as has been shown by other studies, and suggest that a high percentage of cases in hotspot counties are among persons of color ( 1 – 5 , 7 ). Among all underrepresented racial/ethnic groups in these hotspot counties, Hispanic persons were the largest group living in hotspot counties with a disparity in cases identified within that population (3.5 million persons). This finding is consistent with other evidence highlighting the disproportionate incidence of COVID-19 among the Hispanic population ( 2 , 7 ). The disproportionate incidence of COVID-19 among black populations is well documented ( 1 – 3 ). The findings from this analysis align with other data indicating that black persons are overrepresented among COVID-19 cases, associated hospitalizations, and deaths in the United States. The analysis found few counties with disparities among AI/AN populations. This finding is likely attributable to the smaller proportions of cases and populations of AI/AN identified in hotspot counties, as well as challenges with data for this group, including a lack of surveillance data and misclassification problems in large data sets. ¶ Asian populations were disproportionately affected by COVID-19 in a small number of hotspot counties. Few studies have assessed COVID-19 disparities among Asian populations in the United States.** The Asian racial category is broad, and further subgroup analyses might provide additional insights regarding the incidence of COVID-19 in this population. Disparities in COVID-19 cases in NHPI populations were identified in nearly one quarter of hotspot counties. For some hotspot counties with small NHPI populations, this finding might be related, in part, to the analytic methodology used. Using a ratio of ≥1.5 in the proportion of population and proportion of cases to indicate disparities is sensitive to small differences in these groups. More complete county-level race/ethnicity data are needed to fully evaluate the disproportionate incidence of COVID-19 among communities of color. Disparities in COVID-19–associated mortality in hotspot counties were not assessed because the available county-level mortality data disaggregated by race/ethnicity were not sufficient to generate reliable estimates. Existing national analyses highlight disparities in mortality associated with COVID-19; similar patterns are likely to exist at the county level ( 5 ). As more complete data are made available in the future, county-level analyses examining disparities in mortality might be possible. COVID-19 disparities among underrepresented racial/ethnic groups likely result from a multitude of conditions that lead to increased risk for exposure to SARS-CoV-2, including structural factors, such as economic and housing policies and the built environment, †† and social factors such as essential worker employment status requiring in-person work (e.g., meatpacking, agriculture, service, and health care), residence in multigenerational and multifamily households, and overrepresentation in congregate living environments with an increased risk for transmission ( 4 , 7 – 9 ). Further, long-standing discrimination and social inequities might contribute to factors that increase risk for severe disease and death, such as limited access to health care, underlying medical conditions, and higher levels of exposure to pollution and environmental hazards §§ ( 4 ). The conditions contributing to disparities likely vary widely within and among groups, depending on location and other contextual factors. Rates of SARS-CoV-2 transmission vary by region and time, resulting in nonuniform disease outbreak patterns across the United States. Therefore, using epidemiologic indicators to identify hotspot counties currently affected by SARS-CoV-2 transmission can inform a data-driven emergency response. Tailoring strategies to control SARS-CoV-2 transmission could reduce the overall incidence of COVID-19 in communities. Using these data to identify disproportionately affected groups at the county level can guide the allocation of resources, development of culturally and linguistically tailored prevention activities, and implementation of focused testing efforts. The findings in this report are subject to at least five limitations. First, more than half of the hotspot counties did not report sufficient race data and were therefore excluded from the analysis. In addition, many hotspot counties included in the analyses were missing data on race for a significant proportion of cases (mean = 28.3%; range = 2.6%–48.7%). These data gaps might result from jurisdictions having to reconcile data from multiple sources for a large volume of cases while data collection and management processes are rapidly evolving. ¶¶ Second, health departments differ in the way race/ethnicity are reported, making comparisons across counties and states more difficult. Third, differences in how race/ethnicity data are collected (e.g., self-report versus observation) likely varies by setting and could lead to miscategorization. Fourth, differences in access to COVID-19 testing could lead to underestimates of prevalence in some underrepresented racial/ethnic populations. Finally, the number of cases that had available race/ethnicity data for the period of study of hotspots (June 5–18) was too small to generate reliable estimates, so cumulative case counts by county during February–June 2020 were used to identify disparities. This approach describes the racial/ethnic breakdown of cumulative cases only. Therefore, these data might not provide an accurate estimate of disparities during June 5–18, which could be under- or overestimated, or change over time. Developing culturally responsive, targeted interventions in partnership with trusted leaders and community-based organizations within communities of color might reduce disparities in COVID-19 incidence. Increasing the proportion of cases for which race/ethnicity data are collected and reported can help inform efforts in the short-term to better understand patterns of incidence and mortality. Existing health inequities amplified by COVID-19 highlight the need for continued investment in communities of color to address social determinants of health*** and structural racism that affect health beyond this pandemic ( 4 , 8 ). Long-term efforts should focus on addressing societal factors that contribute to broader health disparities across communities of color. Summary What is already known about this topic? Long-standing health and social inequities have resulted in increased risk for infection, severe illness, and death from COVID-19 among communities of color. What is added by this report? Among 79 counties identified as hotspots during June 5–18, 2020 that also had sufficient data on race, a disproportionate number of COVID-19 cases among underrepresented racial/ethnic groups occurred in almost all areas during February–June 2020. What are the implications for public health practice? Identifying health disparities in COVID-19 hotspot counties can inform testing and prevention efforts. Addressing the pandemic’s disproportionate incidence among communities of color can improve community-wide health outcomes related to COVID-19.
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                Author and article information

                Journal
                MMWR Morb Mortal Wkly Rep
                MMWR Morb Mortal Wkly Rep
                WR
                Morbidity and Mortality Weekly Report
                Centers for Disease Control and Prevention
                0149-2195
                1545-861X
                23 October 2020
                23 October 2020
                : 69
                : 42
                : 1517-1521
                Affiliations
                CDC COVID-19 Emergency Response; Epidemic Intelligence Service, CDC; National Center for Health Statistics, CDC; NYC Health + Hospitals, New York, New York.
                Author notes
                Corresponding author: Jeremy Gold, jgold@ 123456cdc.gov .
                Article
                mm6942e1
                10.15585/mmwr.mm6942e1
                7583501
                33090984

                All material in the MMWR Series is in the public domain and may be used and reprinted without permission; citation as to source, however, is appreciated.

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