Dynamics of racial disparities in all-cause mortality during the COVID-19 pandemic.

As research documenting disparate impacts of COVID-19 by race and ethnicity grows, little attention has been given to dynamics in mortality disparities during the pandemic and whether changes in disparities persist. We estimate age-standardized monthly all-cause mortality in the United States from January 2018 through February 2022 for seven racial/ethnic populations. Using joinpoint regression, we quantify trends in race-specific rate ratios relative to non-Hispanic White mortality to examine the magnitude of pandemic-related shifts in mortality disparities. Prepandemic disparities were stable from January 2018 through February 2020. With the start of the pandemic, relative mortality disadvantages increased for American Indian or Alaska Native (AIAN), Native Hawaiian or other Pacific Islander (NHOPI), and Black individuals, and relative mortality advantages decreased for Asian and Hispanic groups. Rate ratios generally increased during COVID-19 surges, with different patterns in the summer 2021 and winter 2021/2022 surges, when disparities approached prepandemic levels for Asian and Black individuals. However, two populations below age 65 fared worse than White individuals during these surges. For AIAN people, the observed rate ratio reached 2.25 (95% CI = 2.14, 2.37) in October 2021 vs. a prepandemic mean of 1.74 (95% CI = 1.62, 1.86), and for NHOPI people, the observed rate ratio reached 2.12 (95% CI = 1.92, 2.33) in August 2021 vs. a prepandemic mean of 1.31 (95% CI = 1.13, 1.49). Our results highlight the dynamic nature of racial/ethnic disparities in mortality and raise alarm about the exacerbation of mortality inequities for Indigenous groups due to the pandemic.

Provisional Mortality Data - United States, 2020.

CDC's National Vital Statistics System (NVSS) collects and reports annual mortality statistics using data from U.S. death certificates. Because of the time needed to investigate certain causes of death and to process and review data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Daily totals reported by CDC COVID-19 case surveillance are timely but can underestimate numbers of deaths because of incomplete or delayed reporting. As a result of improvements in timeliness and the pressing need for updated, quality data during the global COVID-19 pandemic, NVSS expanded provisional data releases to produce near real-time U.S. mortality data.* This report presents an overview of provisional U.S. mortality data for 2020, including the first ranking of leading causes of death. In 2020, approximately 3,358,814 deaths† occurred in the United States. From 2019 to 2020, the estimated age-adjusted death rate increased by 15.9%, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was reported as the underlying cause of death or a contributing cause of death for an estimated 377,883 (11.3%) of those deaths (91.5 deaths per 100,000). The highest age-adjusted death rates by age, race/ethnicity, and sex occurred among adults aged ≥85 years, non-Hispanic Black or African American (Black) and non-Hispanic American Indian or Alaska Native (AI/AN) persons, and males. COVID-19 death rates were highest among adults aged ≥85 years, AI/AN and Hispanic persons, and males. COVID-19 was the third leading cause of death in 2020, after heart disease and cancer. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic.

Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

Social and economic inequality in coronavirus disease 2019 vaccination coverage across Illinois counties.

Prior research has well established the association of ethno-racial and economic inequality with COVID-19 incidence and mortality rates across counties in the US. In this ecological study, a similar association was found between ethno-racial and economic inequality and COVID-19 full vaccination rates across the 102 counties in the American state of Illinois in the early months of vaccination. Among the counties with income inequality below the median, a county's poverty rate had a negative association with the proportion of population fully vaccinated. However, among the counties with income inequality above the median, a higher percentage of Black or Hispanic population was persistently associated with a lower proportion of fully vaccinated population over the two-month period from early February to early April of 2021.

Racial disparities in COVID-19 pandemic cases, hospitalisations, and deaths: A systematic review and meta-analysis.

BACKGROUND: People from racial minority groups in western countries experience disproportionate socioeconomic and structural determinants of health disadvantages. These disadvantages have led to inequalities and inequities in health care access and poorer health outcomes. We report disproportionate disparities in prevalence, hospitalisation, and deaths from COVID-19 by racial minority populations. METHODS: We conducted a systematic literature search of relevant databases to identify studies reporting on prevalence, hospitalisations, and deaths from COVID-19 by race groups between 01 January 2020 - 15 April 2021. We grouped race categories into Blacks, Hispanics, Whites and Others. Random effects model using the method of DerSimonian and Laird were fitted, and forest plot with respective ratio estimates and 95% confidence interval (CI) for each race category, and subgroup meta-regression analyses and the overall pooled ratio estimates for prevalence, hospitalisation and mortality rate were presented. RESULTS: Blacks experienced significantly higher burden of COVID-19: prevalence ratio 1.79 (95% confidence interval (CI) = 1.59-1.99), hospitalisation ratio 1.87 (95% CI = 1.69-2.04), mortality ratio 1.68 (95% CI = 1.52-1.83), compared to Whites: prevalence ratio 0.70 (95% CI = 0.0.64-0.77), hospitalisation ratio 0.74 (95% CI = 0.65-0.82), mortality ratio 0.82 (95% CI = 0.78-0.87). Also, Hispanics experienced a higher burden: prevalence ratio 1.78 (95% CI = 1.63-1.94), hospitalisation ratio 1.32 (95% CI = 1.08-1.55), mortality ratio 0.94 (95% CI = 0.84-1.04) compared to Whites. A higher burden was also observed for Other race groups: prevalence ratio 1.43 (95% CI = 1.19-1.67), hospitalisation ratio 1.12 (95% CI = 0.89-1.35), mortality ratio 1.06 (95% CI = 0.89-1.23) compared to Whites. The disproportionate burden among Blacks and Hispanics remained following correction for publication bias. CONCLUSIONS: Blacks and Hispanics have been disproportionately affected by COVID-19. This is deeply concerning and highlights the systemically entrenched disadvantages (social, economic, and political) experienced by racial minorities in western countries; and this study underscores the need to address inequities in these communities to improve overall health outcomes.

Initial Effects of COVID-19 on Patients with ESKD.

BACKGROUND: Reports from around the world have indicated a fatality rate of patients with coronavirus disease 2019 (COVID-19) in the range of 20%-30% among patients with ESKD. Population-level effects of COVID-19 on patients with ESKD in the United States are uncertain. METHODS: We identified patients with ESKD from Centers for Medicare and Medicaid Services data during epidemiologic weeks 3-27 of 2017-2020 and corresponding weeks of 2017-2019, stratifying them by kidney replacement therapy. Outcomes comprised hospitalization for COVID-19, all-cause death, and hospitalization for reasons other than COVID-19. We estimated adjusted relative rates (ARRs) of death and non-COVID-19 hospitalization during epidemiologic weeks 13-27 of 2020 (March 22 to July 4) versus corresponding weeks in 2017-2019. RESULTS: Among patients on dialysis, the rate of COVID-19 hospitalization peaked between March 22 and April 25 2020. Non-Hispanic Black race and Hispanic ethnicity associated with higher rates of COVID-19 hospitalization, whereas peritoneal dialysis was associated with lower rates. During weeks 13-27, ARRs of death in 2020 versus 2017-2019 were 1.17 (95% confidence interval [95% CI], 1.16 to 1.19) and 1.30 (95% CI, 1.24 to 1.36) among patients undergoing dialysis or with a functioning transplant, respectively. Excess mortality was higher among non-Hispanic Black, Hispanic, and Asian patients. Among patients on dialysis, the rate of non-COVID-19 hospitalization during weeks 13-27 in 2020 was 17% lower versus hospitalization rates for corresponding weeks in 2017-2019. CONCLUSIONS: During the first half of 2020, the clinical outcomes of patients with ESKD were greatly affected by COVID-19, and racial and ethnic disparities were apparent. These findings should be considered in prioritizing administration of COVID-19 vaccination.

COVID-19 Incidence and Mortality Among American Indian/Alaska Native and White Persons - Montana, March 13-November 30, 2020.

Geographic differences in infectious disease mortality rates have been observed among American Indian or Alaska Native (AI/AN) persons in the United States (1), and aggregate analyses of data from selected U.S. states indicate that COVID-19 incidence and mortality are higher among AI/AN persons than they are among White persons (2,3). State-level data could be used to identify disparities and guide local efforts to reduce COVID-19-associated incidence and mortality; however, such data are limited. Reports of laboratory-confirmed COVID-19 cases and COVID-19-associated deaths reported to the Montana Department of Public Health and Human Services (MDPHHS) were analyzed to describe COVID-19 incidence, mortality, and case-fatality rates among AI/AN persons compared with those among White persons. During March-November 2020 in Montana, the estimated cumulative COVID-19 incidence among AI/AN persons (9,064 cases per 100,000) was 2.2 times that among White persons (4,033 cases per 100,000).* During the same period, the cumulative COVID-19 mortality rate among AI/AN persons (267 deaths per 100,000) was 3.8 times that among White persons (71 deaths per 100,000). The AI/AN COVID-19 case-fatality rate (29.4 deaths per 1,000 COVID-19 cases) was 1.7 times the rate in White persons (17.0 deaths per 1,000). State-level surveillance findings can help in developing state and tribal COVID-19 vaccine allocation strategies and assist in local implementation of culturally appropriate public health measures that might help reduce COVID-19 incidence and mortality in AI/AN communities.

Ethnicity, household composition and COVID-19 mortality: a national linked data study.

OBJECTIVE: To estimate the proportion of ethnic inequalities explained by living in a multi-generational household. DESIGN: Causal mediation analysis. SETTING: Retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 30 November 2020). PARTICIPANTS: Adults aged 65 years or over living in private households in England from 2 March 2020 until 30 November 2020 (n=10,078,568). MAIN OUTCOME MEASURES: Hazard ratios were estimated for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographic factors, socioeconomic characteristics and pre-pandemic health. RESULTS: Living in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the hazard ratios for living in a multi-generational household with dependent children were 1.17 (95% confidence interval [CI] 1.06-1.30) and 1.21 (95% CI 1.06-1.38) for elderly men and women. The hazard ratios for living in a multi-generational household without dependent children were 1.07 (95% CI 1.01-1.13) for elderly men and 1.17 (95% CI 1.07-1.25) for elderly women. Living in a multi-generational household explained about 11% of the elevated risk of COVID-19 death among elderly women from South Asian background, but very little for South Asian men or people in other ethnic minority groups. CONCLUSION: Elderly adults living with younger people are at increased risk of COVID-19 mortality, and this is a contributing factor to the excess risk experienced by older South Asian women compared to White women. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.

Excess Deaths Among Blacks and Latinx Compared to Whites During Covid-19.

IMPORTANCE: Blacks and Latinx are disproportionately affected by Coronavirus disease 2019 (Covid-19) and experience higher mortality rates than Whites and Asians in the USA. Such racial disparities, in Covid-19 testing, cases, and mortality are visible in Connecticut too. Recently, excess deaths have become an important consideration in news reports and academic research. However, data on racial differences in excess death is limited. OBJECTIVE: This study examines racial/ethnic differences in excess deaths in the state of Connecticut during the Covid-19 pandemic. DESIGN: This is a cross-sectional epidemiological study to estimate excess deaths by racial/ethnic status utilizing mortality data during the peak months of Covid-19 infections from March 1 to June 30, 2020, in Connecticut. The following assumption is applied: expected non-Covid-19 deaths from March 1 to June 30, 2020, are equal to the number of deaths occurring during the period of March 1 to June 30, 2019. Race/ethnicity are defined as Non-Hispanic White, Non-Hispanic Black, and Latinx. Descriptive statistics and rates with 95% confidence intervals are presented. Chi-square analyses are performed where applicable. SETTING: Connecticut PARTICIPANTS: All deaths in Connecticut from March 1 to June 30, 2020. EXPOSURE: Covid-19 and race/ethnicity RESULTS: From March 1 to June 30, 2020, a total of 14,226 all-cause deaths occurred including 1514 Blacks (10.6%), 1095 Latinx (7.7%), and 11,617 Whites (81.7%). This represented a 74% increase in mortality for Blacks; 63% for Latinx, and 30% for Whites. In addition, 42.70% of the deaths in Blacks were attributed to Covid-19; 38.5% for Latinx, and 23.0% for Whites (p<0.001). Covid-19 deaths accounted for over 90% of the excess deaths in Blacks and Hispanics. In contrast, in Whites, Covid-19 deaths exceeded the number of excess deaths by 353 cases (113.2%), indicating that some Whites may have died from other underlined health conditions with a positive Covid-19 diagnosis. Furthermore, there was an increase in undetermined deaths in 2020, which accounted for 10.8% of deaths in Blacks, 13% in Latinx, and 6.2% of deaths in Whites. CONCLUSIONS AND RELEVANCE: Excess deaths in Blacks and Latinx were found above the numbers of deaths determined to have occurred due to Covid-19. The fact that a large number of undetermined deaths were found for Blacks and Latinx individuals, and testing rates for Blacks and Latinx individuals (as determined by positivity rates) were lacking during this period strongly suggests, these excess deaths were Covid-19-related deaths. The study findings indicate that Black and Latinx COVID-19-related deaths may be underreported in this pandemic. We advocate for targeted strategies that increase testing capacity, treatment, and vaccine availability in Black and Latinx communities.

Assessment of Disparities Associated With a Crisis Standards of Care Resource Allocation Algorithm for Patients in 2 US Hospitals During the COVID-19 Pandemic.

Importance: Significant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity. Objective: To evaluate whether unanticipated disparities by race or ethnicity arise from a single institution's resource allocation policy. Design, Setting, and Participants: This cohort study included adults (aged ≥18 years) who were cared for on a coronavirus disease 2019 (COVID-19) ward or in a monitored unit requiring invasive or noninvasive ventilation or high-flow nasal cannula between May 26 and July 14, 2020, at 2 academic hospitals in Miami, Florida. Exposures: Race (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic). Main Outcomes and Measures: The primary outcome was based on a resource allocation priority score (range, 1-8, with 1 indicating highest and 8 indicating lowest priority) that was assigned daily based on both estimated short-term (using Sequential Organ Failure Assessment score) and longer-term (using comorbidities) mortality. There were 2 coprimary outcomes: maximum and minimum score for each patient over all eligible patient-days. Standard summary statistics were used to describe the cohort, and multivariable Poisson regression was used to identify associations of race and ethnicity with each outcome. Results: The cohort consisted of 5613 patient-days of data from 1127 patients (median [interquartile range {IQR}] age, 62.7 [51.7-73.7]; 607 [53.9%] men). Of these, 711 (63.1%) were White patients, 323 (28.7%) were Black patients, 8 (0.7%) were Asian patients, and 31 (2.8%) were multiracial patients; 480 (42.6%) were non-Hispanic patients, and 611 (54.2%) were Hispanic patients. The median (IQR) maximum priority score for the cohort was 3 (1-4); the median (IQR) minimum score was 2 (1-3). After adjustment, there was no association of race with maximum priority score using White patients as the reference group (Black patients: incidence rate ratio [IRR], 1.00; 95% CI, 0.89-1.12; Asian patients: IRR, 0.95; 95% CI. 0.62-1.45; multiracial patients: IRR, 0.93; 95% CI, 0.72-1.19) or of ethnicity using non-Hispanic patients as the reference group (Hispanic patients: IRR, 0.98; 95% CI, 0.88-1.10); similarly, no association was found with minimum score for race, again with White patients as the reference group (Black patients: IRR, 1.01; 95% CI, 0.90-1.14; Asian patients: IRR, 0.96; 95% CI, 0.62-1.49; multiracial patients: IRR, 0.81; 95% CI, 0.61-1.07) or ethnicity, again with non-Hispanic patients as the reference group (Hispanic patients: IRR, 1.00; 95% CI, 0.89-1.13). Conclusions and Relevance: In this cohort study of adult patients admitted to a COVID-19 unit at 2 US hospitals, there was no association of race or ethnicity with the priority score underpinning the resource allocation policy. Despite this finding, any policy to guide altered standards of care during a crisis should be monitored to ensure equitable distribution of resources.

Excess mortality during the COVID-19 pandemic in Israel, March-November 2020: when, where, and for whom?

BACKGROUND: Excess all-cause mortality has been used in many countries as an estimate of mortality effects from COVID-19. What was the excess mortality in Israel in 2020 and when, where and for whom was this excess? METHODS: Mortality rates between March to November 2020 for various demographic groups, cities, month and week were compared with the average rate during 2017-2019 for the same groups or periods. RESULTS: Total mortality rates for March-November were significantly higher by 6% in 2020, than the average of 2017-2019, 14% higher among the Arab population and 5% among Jews and Others. Significantly higher monthly mortality rates were found in August, September and October by 11%, 13% and 19%, respectively, among Jews and Others, and by 19%, 64% and 40% in the Arab population. Excess mortality was significant only at older ages, 7% higher rates at ages 65-74 and 75-84 and 8% at ages 85 and above, and greater for males than females in all ages and population groups. Interestingly, mortality rates decreased significantly among the younger population aged under 25. The cities with most significant excess mortality were Ramla (25% higher), Bene Beraq (24%), Bat Yam (15%) and Jerusalem (8%). CONCLUSION: Israel has seen significant excess mortality in August-October 2020, particularly in the Arab sector. The excess mortality in March-November was statistically significant only at older ages, over 65. It is very important to protect this susceptible population from exposure and prioritize them for inoculations. Lockdowns were successful in lowering the excess mortality. The excess mortality is similar to official data on COVID-19 deaths.

Racial Disparities In Excess All-Cause Mortality During The Early COVID-19 Pandemic Varied Substantially Across States.

The impact of the coronavirus disease 2019 (COVID-19) pandemic has been starkly unequal across race and ethnicity. We examined the geographic variation in excess all-cause mortality by race and ethnicity to better understand the impact of the pandemic. We used individual-level administrative data on the US population between January 2011 and April 2020 to estimate the geographic variation in excess all-cause mortality by race and Hispanic origin. All-cause mortality allows a better understanding of the overall impact of the pandemic than mortality attributable to COVID-19 directly. Nationwide, adjusted excess all-cause mortality during that period was 6.8 per 10,000 for Black people, 4.3 for Hispanic people, 2.7 for Asian people, and 1.5 for White people. Nationwide averages mask substantial geographic variation. For example, despite similar excess White mortality, Michigan and Louisiana had markedly different excess Black mortality, as did Pennsylvania compared with Rhode Island. Wisconsin experienced no significant White excess mortality but had significant Black excess mortality. Further work understanding the causes of geographic variation in racial and ethnic disparities-the relevant roles of social and environmental factors relative to comorbidities and of the direct and indirect health effects of the pandemic-is crucial for effective policy making.

The Epidemiology and Predictors of Outcomes Among Confirmed COVID-19 Cases in a Large Community Healthcare System in South Florida.

The novel coronavirus disease 2019 (COVID-19) continues to be a major public health concern. The aim of this study was to describe the presenting characteristics, epidemiology and predictors of outcomes among confirmed COVID-19 cases seen at a large community healthcare system which serves the epicenter and diverse region of Florida. We conducted a retrospective analysis of individuals with lab-confirmed SARS-CoV-2 infection who were seen, from March 2, 2020 to May 31, 2020, at Memorial Healthcare System in South Florida. Data was extracted from a COVID-19 registry of patients with lab-confirmed SARS-CoV-2 infection. Univariate and backward stepwise multivariate logistic regression models were used to determine predictors of key study outcomes. There were a total of 1692 confirmed COVID-19 patients included in this study. Increasing age was found to be a significant predictor of hospitalization, 30-day readmission and death. Having a temperature of 38 °C or more and increasing comorbidity score were also associated with an increased risk of hospitalization. Significant predictors of ICU admission included having a saturated oxygen level less than 90%, hypertension, dementia, rheumatologic disease, having a respiratory rate greater than 24 breaths per minute. Being of Hispanic ethnicity and immunosuppressant utilization greatly increased the risk of 30-day readmission. Having an oxygen saturation less than 90% and an underlying neurological disorder were associated with an increased likelihood of death. Results show that a patient's demographic, underlying condition and vitals at triage may increase or reduce their risk of hospitalization, ICU admission, 30-day readmission or death.

Ethnic-minority groups in England and Wales-factors associated with the size and timing of elevated COVID-19 mortality: a retrospective cohort study linking census and death records.

BACKGROUND: We estimated population-level associations between ethnicity and coronavirus disease 2019 (COVID-19) mortality using a newly linked census-based data set and investigated how ethnicity-specific mortality risk evolved during the pandemic. METHODS: We conducted a retrospective cohort study of respondents to the 2011 Census of England and Wales in private households, linked to death registrations and adjusted for emigration (n = 47 872 412). The outcome of interest was death involving COVID-19 between 2 March 2020 and 15 May 2020. We estimated hazard ratios (HRs) for ethnic-minority groups compared with the White population, controlling for individual, household and area characteristics. HRs were estimated on the full outcome period and separately for pre- and post-lockdown periods. RESULTS: In age-adjusted models, people from all ethnic-minority groups were at elevated risk of COVID-19 mortality; the HRs for Black males and females were 3.13 (95% confidence interval: 2.93 to 3.34) and 2.40 (2.20 to 2.61), respectively. However, in fully adjusted models for females, the HRs were close to unity for all ethnic groups except Black [1.29 (1.18 to 1.42)]. For males, the mortality risk remained elevated for the Black [1.76 (1.63 to 1.90)], Bangladeshi/Pakistani [1.35 (1.21 to 1.49)] and Indian [1.30 (1.19 to 1.43)] groups. The HRs decreased after lockdown for all ethnic groups, particularly Black and Bangladeshi/Pakistani females. CONCLUSION: Differences in COVID-19 mortality between ethnic groups were largely attenuated by geographical and socio-demographic factors, though some residual differences remained. Lockdown was associated with reductions in excess mortality risk in ethnic-minority populations, which has implications for a second wave of infection.

Racial, ethnic, and socioeconomic disparities in confirmed COVID-19 cases and deaths in the United States: a county-level analysis as of November 2020.

OBJECTIVES: The objective of this study was to investigate potential county-level disparities among racial/ethnic and socioeconomic groups in confirmed COVID-19 cases and deaths in the United States in 100,000 population. DESIGN: Secondary data analysis using county-level data for 3,142 US counties was conducted in 2020. Hierarchical linear regression and concentration curve analyses were performed. The combined association of COVID-19 cases and deaths was examined separately by the county population's socioeconomic characteristics. Data from the American Community Survey (ACS) 5-year estimates (2014-2018), Area Health Resources File (AHRF) 2018-2019, Kaiser Health News 2020, and 2020 COVID-19 data from Johns Hopkins University were used in this study. RESULTS: After adjusting for covariates, U.S. counties with a higher proportion of the Black population and a higher proportion of adults with less than a high school diploma had disproportionately higher COVID-19 cases and deaths (ß > 0, p<0.05 for all relations). A higher proportion of the Hispanic population was associated with higher confirmed cases (ß = 0.68, 95% CI = 0.48-0.87). The majority observed disparities in COVID-19 deaths persisted even after controlling for all-cause deaths in 2019 and COVID-19 cases per 100,000 county population. This can potentially aggravate the existing health disparities among these population groups. CONCLUSIONS: Identification of disproportionately impacted population groups can pave the way towards narrowing the disparity gaps and guide policymakers and stakeholders in designing and implementing population group-specific interventions to mitigate the negative consequences of the COVID-19 pandemic.

Estimating the Unknown: Greater Racial and Ethnic Disparities in COVID-19 Burden After Accounting for Missing Race and Ethnicity Data.

BACKGROUND: Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data. METHODS: We quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification. RESULTS: The ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons. CONCLUSIONS: These results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden.