Differences in race and other state-level characteristics and associations with mortality from COVID-19 infection

Associations between mortality from COVID-19 and other causes: A state-level analysis

BACKGROUND

During the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states.

METHODS

We use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state's population.

RESULTS

We estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes.

CONCLUSIONS

States with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.

Examining longitudinal disparities in COVID-19 prevalence in the U.S.: a county level growth rate perspective

Background: The objectives of the present study are to understand the longitudinal variability in COVID-19 reported cases at the county level and to associate the observed rates of infection with the adoption and lifting of stay-home orders.Materials and Methods: The study uses the trajectory of the pandemic in a county and controls for social and economic risk factors, physical environment, and health behaviors to elucidate the social determinants contributing to the observed rates of infection.Results and conclusion: Results indicated that counties with higher percentages of young individuals, racial and ethnic minorities and, higher population densities experienced greater difficulty suppressing transmission.Except for Education and the Gini Index, all factors were influential on the rate of COVID-19 spread before and after stay-home orders. However, after lifting the orders, six of the factors were not influential on the rate of spread; these included: African-Americans, Population Density, Single Parent Households, Average Daily PM2.5, HIV Prevalence Rate, and Home Ownership. It was concluded that different factors from the ones controlling the initial spread of COVID-19 are at play after stay-home orders are lifted.KEY MESSAGESObserved rates of COVID-19 infection at the County level in the U.S. are not directly associated with adoption and lifting of stay-home orders.Disadvantages in sociodemographic determinants negatively influence the rate of COVID-19 spread.Counties with more young individuals, racial and ethnic minorities, and higher population densities have greater difficulty suppressing transmission.

The role of housing characteristics in racial and ethnic disparities in SARS-CoV-2 antibody seropositivity among New York City adults: A population representative study

Black and Latino populations have been disproportionately burdened by COVID-19 morbidity and mortality. Subsidized housing, crowding, and neighborhood poverty might be associated with increased COVID-19 transmission and play a role in observed racial and ethnic disparities, yet research is limited. Our study investigated whether these housing variables mediate the relationship between race and ethnicity and SARS-CoV-2 antibody seropositivity among New York City (NYC) adults. We analyzed data from a SARS-CoV-2 serosurvey (n = 1074), nested within the 2020 cross-sectional NYC Community Health Survey (June-October 2020). We defined SARS-CoV-2 seropositivity as either a positive blood test for SARS-CoV-2 antibodies or a self-reported positive test result. We used causal mediation analyses to test whether subsidized housing, crowding, and neighborhood poverty mediate a relationship between race and ethnicity and seropositivity. After controlling for potential confounding, we found elevated prevalence ratios of SARS-CoV-2 seropositivity among Black (APR = 1.74, 95% CI = 1.10-2.73) and Latino (APR = 1.58, 95% CI = 1.05-2.37) residents compared with White residents and for those living in crowded housing (APR = 1.48, 95% CI = 1.03-2.12) and high-poverty neighborhoods (APR = 1.54, 95% CI = 1.12-2.11) but not for subsidized housing. We observed statistically significant natural direct effects for all three mediators. While living in crowded housing and high-poverty neighborhoods contributed to racial and ethnic disparities in seropositivity the estimated contribution from living in subsidized housing was -9% (Black) and - 14% (Latino). Our findings revealed racial and ethnic disparities in seropositivity of SARS-CoV-2 antibodies among NYC adults. Unlike crowding and neighborhood poverty, living in subsidized housing did not explain racial and ethnic disparities in COVID-19.

The risks and opportunities of the COVID-19 crisis for building longitudinal evidence on today's early childhood education programs

In the United States, the long-term effects of early childhood programs have been given particular weight in research on early childhood education and in policy debates about the value of prekindergarten. Many research teams were building the evidence base on U.S. early childhood programs to inform that discussion when studies were upended by the COVID-19 pandemic. In this article, we describe the theoretical and practical risks the COVID-19 pandemic poses for longitudinal studies of preschool intervention programs. We also discuss the potential opportunities the crisis offers by introducing new variation in postprogram experiences for addressing new questions. The article intersects the resilience and disaster literatures with theoretical frameworks for the persistence of preschool effects. We conclude with recommendations for how longitudinal studies of cohorts affected by COVID-19 can enhance our understanding of the mechanisms behind the persistence of preschool effects.

Historical Redlining and Resident Exposure to COVID-19: A Study of New York City

The Coronavirus Disease 2019 (COVID-19) has been reported to disproportionately impact racial/ethnic minorities in the USA, both in terms of infections and deaths. This racial disparity in the COVID-19 outcomes may result from the segregation of minorities in neighborhoods with health-compromising conditions. We, thus, anticipate that neighborhoods would be especially vulnerable to COVID-19 if they are of present-day economic and racial disadvantage and were redlined historically. To test this expectation, we examined the change of both confirmed COVID-19 cases and deaths from April to July, 2020, in zip code tabulation areas (ZCTAs) in the New York City using multilevel regression analysis. The results indicate that ZCTAs with a higher proportion of black and Hispanic populations are associated with a higher percentage of COVID-19 infection. Historically low-graded neighborhoods show a higher risk for COVID-19 infection, even for ZCTAs with present-day economic and racial privilege. These associations change over time as the pandemic unfolds. Racial/ethnic minorities are bearing the brunt of the COVID-19 pandemic's health impact. The current evidence shows that the pre-existing social structure in the form of racial residential segregation could be partially responsible for the disparities observed, highlighting an urgent need to stress historical segregation and to build a less segregated and more equal society.

Changes in Depressive Symptoms, Physical Symptoms, and Sleep-Wake Problems from before to during the COVID-19 Pandemic among Emerging Adults: Inequalities by Gender, Socioeconomic Position, and Race

The impact of the COVID-19 pandemic on emerging adults is of global concern. We examine changes in depressive symptoms, physical symptoms, and sleep-wake problems from before to during the pandemic among college students, and examine inequalities by gender, socioeconomic status (SES), and race (N=263, 52% Black, 48% White, 53% female). As compared to pre-pandemic levels, increases were evident in depressive symptoms, physical symptoms, and sleep problems. Females had greater increases than males in depressive symptoms, sleep problems, and physical symptoms. Students from disadvantaged SES backgrounds had greater increases in physical symptoms. Among White students, those from disadvantaged backgrounds also had greater increases in sleep problems. Lastly, daytime sleepiness increased more among Black male than White male students. Overall, findings suggest notable shifts in sleep and health during the early phase of the pandemic among emerging adults, and that attention to inequality by gender, SES, and race is warranted.

Changes in COVID-19-Associated Deaths During a Year Among Blacks and Hispanics Compared to Whites in the State of Connecticut

Background

With recent COVID-19 vaccination rates relatively high in the USA, the USA still maintains the most documented cases globally,[1] even though COVID-19 cases, hospitalization, and mortality have been declining. However, the health burden has been largely felt in communities involving racial and ethnic minorities. Thus, in order to provide a clearer picture of what is happening in Black, Indigenous, and people of color communities, we examined the racial/ethnic differences of monthly COVID-19 deaths in Connecticut.

Methods

This is an epidemiological study analyzing mortality data from March 1, 2020, to February 28, 2021, obtained from the Connecticut State Department of Public Health. The data include cause of death (COVID-19 death identified by ICD-10 code U071), race/ethnicity (non-Hispanic White (White), non-Hispanic Black (Black), and Hispanic), sex, and age. Both crude and age-adjusted rates were reported by racial/ethnic groups. To compare age-adjusted rates between racial groups, with estimated age-adjusted death counts as outcomes, between-racial group rate ratios, 95% confidence intervals, and p values significant at < 0.05 were derived from the Poisson regression model.

Results

From March 2020 to May 2020 (wave 1) of COVID-19 cases, the COVID-19-related mortality rates were the highest for all three race groups (Whites, Blacks, and Hispanics) with statistical group differences (p < 0.05). Blacks had the highest rates of deaths followed by Hispanics and then Whites. Further, more Whites died in a nursing home when compared to Blacks and Hispanics. From June 2010 to October 2020 (wave 2), COVID-19 mortality declined significantly for all three race groups with no statistical differences between groups. COVID-19 deaths in nursing homes declined for all three racial/ethnic groups. From November 2020 to February 2021 (wave 3), COVID-19 mortality rates were significantly higher compared to wave 2 but lower than wave 1 for all three race groups. The mortality rates for Blacks and Hispanics were higher than Whites. Hispanics had the highest rates of deaths, followed by Blacks, and then Whites (p < 0.05). Whites showed the lowest mortality rates among all three racial/ethnic groups.

Conclusions

In summary, COVID-19 health disparities among Black and Hispanic populations were evident in this study. Blacks and Hispanics had significantly higher mortality rates when compared to Whites. Blacks had the highest mortality rates during wave 1, and in wave 3, Hispanics has the highest mortality rates. Our data are important because they show monthly COVID-19 deaths data by race. Data reported this way gives a better and more accurate understanding of what is really happening in Black, Indigenous, and people of color populations.

Complex systems models for causal inference in social epidemiology

Systems models, which by design aim to capture multi-level complexity, are a natural choice of tool for bridging the divide between social epidemiology and causal inference. In this commentary, we discuss the potential uses of complex systems models for improving our understanding of quantitative causal effects in social epidemiology. To put systems models in context, we will describe how this approach could be used to optimise the distribution of COVID-19 response resources to minimise social inequalities during and after the pandemic.

Trends in Intensive Care for Patients with COVID-19 in England, Wales, and Northern Ireland

Rationale: By describing trends in intensive care for patients with coronavirus disease (COVID-19) we aim to support clinical learning, service planning, and hypothesis generation.Objectives: To describe variation in ICU admission rates over time and by geography during the first wave of the epidemic in England, Wales, and Northern Ireland; to describe trends in patient characteristics on admission to ICU, first-24-hours physiology in ICU, processes of care in ICU and patient outcomes; and to explore deviations in trends during the peak period.Methods: A cohort of 10,741 patients with COVID-19 in the Case Mix Program national clinical audit from February 1 to July 31, 2020, was used. Analyses were stratified by time period (prepeak, peak, and postpeak periods) and geographical region. Logistic regression was used to estimate adjusted differences in 28-day in-hospital mortality between periods.Measurements and Main Results: Admissions to ICUs peaked almost simultaneously across regions but varied 4.6-fold in magnitude. Compared with patients admitted in the prepeak period, patients admitted in the postpeak period were slightly younger but with higher degrees of dependency and comorbidity on admission to ICUs and more deranged first-24-hours physiology. Despite this, receipt of invasive ventilation and renal replacement therapy decreased, and adjusted 28-day in-hospital mortality was reduced by 11.8% (95% confidence interval, 8.7%-15.0%). Many variables exhibited u-shaped or n-shaped curves during the peak.Conclusions: The population of patients with COVID-19 admitted to ICUs, and the processes of care in ICUs, changed over the first wave of the epidemic. After adjustment for important risk factors, there was a substantial improvement in patient outcomes.

Impact of COVID-19 on services for people with disabilities and chronic health conditions

BACKGROUND

People with disabilities and chronic health conditions rely on a range of services and supports to complete daily tasks, maintain health, and participate in the community. Preliminary research suggests the COVID-19 pandemic greatly disrupted these services and this population may be particularly susceptible to unemployment.

OBJECTIVE

Describe employment and service disruptions for individuals with disabilities and chronic health conditions during the onset of community-based spread of COVID-19 in the United States.

METHODS

Adults with disabilities and chronic health conditions completed online surveys to report employment and service changes via multiple choice and open-ended questions. Multiple choice questions were analyzed using descriptive statistics; open-ended responses were coded using content analysis.

RESULTS

Participants (n = 109): 79.8% female, 88.1% white, 77.121% completed a 4-year college degree or greater, 61.4% had annual income ≥$45,000. Only 14.9% of survey respondents reported disruptions in employment. On average, 54.0% of service changes were due to discontinuation, including loss of physical therapy, job coaching, community organizations, transportation, and peer supports. Other changes included a shift to virtual service delivery and family members taking the role of service providers.

CONCLUSIONS

Individuals with chronic health conditions and disabilities experienced service disruptions, even in a sample with considerably more economic, social, and educational privilege than the general population of people with chronic health conditions and disabilities in the United States.

Racial and Ethnic Disparities in COVID-19-Related Infections, Hospitalizations, and Deaths : A Systematic Review

BACKGROUND

Data suggest that the effects of coronavirus disease 2019 (COVID-19) differ among U.S. racial/ethnic groups.

PURPOSE

To evaluate racial/ethnic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and COVID-19 outcomes, factors contributing to disparities, and interventions to reduce them.

DATA SOURCES

English-language articles in MEDLINE, PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus, searched from inception through 31 August 2020. Gray literature sources were searched through 2 November 2020.

STUDY SELECTION

Observational studies examining SARS-CoV-2 infections, hospitalizations, or deaths by race/ethnicity in U.S. settings.

DATA EXTRACTION

Single-reviewer abstraction confirmed by a second reviewer; independent dual-reviewer assessment of quality and strength of evidence.

DATA SYNTHESIS

37 mostly fair-quality cohort and cross-sectional studies, 15 mostly good-quality ecological studies, and data from the Centers for Disease Control and Prevention and APM Research Lab were included. African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection, hospitalization, and COVID-19-related mortality compared with non-Hispanic White populations, but not higher case-fatality rates (mostly reported as in-hospital mortality) (moderate- to high-strength evidence). Asian populations experience similar outcomes to non-Hispanic White populations (low-strength evidence). Outcomes for other racial/ethnic groups have been insufficiently studied. Health care access and exposure factors may underlie the observed disparities more than susceptibility due to comorbid conditions (low-strength evidence).

LIMITATIONS

Selection bias, missing race/ethnicity data, and incomplete outcome assessments in cohort and cross-sectional studies must be considered. In addition, adjustment for key demographic covariates was lacking in ecological studies.

CONCLUSION

African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection and COVID-19-related mortality but similar rates of case fatality. Differences in health care access and exposure risk may be driving higher infection and mortality rates.

PRIMARY FUNDING SOURCE

Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development. (PROSPERO: CRD42020187078).

Trends in Intensive Care for Patients with COVID-19 in England, Wales, and Northern Ireland

Rationale: By describing trends in intensive care for patients with coronavirus disease (COVID-19) we aim to support clinical learning, service planning, and hypothesis generation.Objectives: To describe variation in ICU admission rates over time and by geography during the first wave of the epidemic in England, Wales, and Northern Ireland; to describe trends in patient characteristics on admission to ICU, first-24-hours physiology in ICU, processes of care in ICU and patient outcomes; and to explore deviations in trends during the peak period.Methods: A cohort of 10,741 patients with COVID-19 in the Case Mix Program national clinical audit from February 1 to July 31, 2020, was used. Analyses were stratified by time period (prepeak, peak, and postpeak periods) and geographical region. Logistic regression was used to estimate adjusted differences in 28-day in-hospital mortality between periods.Measurements and Main Results: Admissions to ICUs peaked almost simultaneously across regions but varied 4.6-fold in magnitude. Compared with patients admitted in the prepeak period, patients admitted in the postpeak period were slightly younger but with higher degrees of dependency and comorbidity on admission to ICUs and more deranged first-24-hours physiology. Despite this, receipt of invasive ventilation and renal replacement therapy decreased, and adjusted 28-day in-hospital mortality was reduced by 11.8% (95% confidence interval, 8.7%-15.0%). Many variables exhibited u-shaped or n-shaped curves during the peak.Conclusions: The population of patients with COVID-19 admitted to ICUs, and the processes of care in ICUs, changed over the first wave of the epidemic. After adjustment for important risk factors, there was a substantial improvement in patient outcomes.

Ethnicity and COVID-19 cardiovascular complications: a multi-center UK cohort

BACKGROUND

Recent reports suggest an association between ethnicity and COVID-19 mortality. In the present multi-center study, we aimed to assess the differences underlying this association, and ascertain whether ethnicity also mediates other aspects of COVID-19 like cardiovascular complications.

METHODS

Data were collected from a mixed-ethnicity UK cohort of 613 patients admitted and diagnosed COVID-19 positive, across six hospitals in London during the second half of March 2020: 292 were White Caucasian ethnicity, 203 were Asian and 118 were of Afro-Caribbean ethnicity.

RESULTS

Caucasian patients were older (P<0.001) and less likely to have hypertension (P=0.038), while Afro-Caribbean patients had higher prevalence of diabetes mellitus (P<0.001). Asian patients were more likely to present with venous thromboembolic disease (adj.OR=4.10, 95% CI 1.49-11.27, P=0.006). On the other hand, Afro-Caribbean had more heart failure (adj.OR=3.64, 95% CI 1.50-8.84, P=0.004) and myocardial injury (adj.OR=2.64, 95% CI 1.10-6.35, P=0.030). Importantly, our adjusted multi-variate Cox regression analysis revealed significantly higher all-cause mortality both for Asian (adj.HR=1.89, 95% CI 1.23-2.91, P=0.004) and Afro-Caribbean ethnicity (adj.HR=2.09, 95% CI 1.30-3.37, P=0.002).

CONCLUSIONS

Our data show that COVID-19 may have different presentations and follow different clinical trajectories depending on the ethnicity of the affected subject. Awareness of complications more likely to arise in specific ethnicities will allow a more timely diagnosis and preventive measures for patients at risk. Due to increased mortality, individuals of Afro-Caribbean and Asian ethnicity should be considered as high-risk groups. This may have an impact on health-resource allocation and planning, definition of vulnerable groups, disease management, and the protection of healthcare workers at the frontline.