Racial/Ethnic and Age Differences in the Direct and Indirect Effects of the COVID-19 Pandemic on US Mortality.

Objectives. To estimate the direct and indirect effects of the COVID-19 pandemic on overall, race/ethnicity‒specific, and age-specific mortality in 2020 in the United States. Methods. Using surveillance data, we modeled expected mortality, compared it to observed mortality, and estimated the share of "excess" mortality that was indirectly attributable to the pandemic versus directly attributed to COVID-19. We present absolute risks and proportions of total pandemic-related mortality, stratified by race/ethnicity and age. Results. We observed 16.6 excess deaths per 10 000 US population in 2020; 84% were directly attributed to COVID-19. The indirect effects of the pandemic accounted for 16% of excess mortality, with proportions as low as 0% among adults aged 85 years and older and more than 60% among those aged 15 to 44 years. Indirect causes accounted for a higher proportion of excess mortality among racially minoritized groups (e.g., 32% among Black Americans and 23% among Native Americans) compared with White Americans (11%). Conclusions. The effects of the COVID-19 pandemic on mortality and health disparities are underestimated when only deaths directly attributed to COVID-19 are considered. An equitable public health response to the pandemic should also consider its indirect effects on mortality. (Am J Public Health. 2022;112(1):154-164. https://doi.org/10.2105/AJPH.2021.306541).

U.S. Nursing Home Quality Ratings Associated with COVID-19 Cases and Deaths.

OBJECTIVES: To inform future policies and disaster preparedness plans in the vulnerable nursing home setting, we need greater insight into the relationship between nursing homes' (NHs') quality and the spread and severity of COVID-19 in NH facilities. We therefore extend current evidence on the relationships between NH quality and resident COVID-19 infection rates and deaths, taking into account NH structural characteristics and community characteristics. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: 15,390 Medicaid- and Medicare-certified NHs. METHODS: We obtained and merged the following data sets: (1) COVID-19 weekly data reported by each nursing home to the Centers for Disease Control and Prevention's National Healthcare Safety Network, (2) Centers for Medicare & Medicaid Services Five Star Quality Rating System, (3) county-level COVID-19 case counts, (4) county-level population data, and (5) county-level sociodemographic data. RESULTS: Among 1-star NHs, there were an average of 13.19 cases and 2.42 deaths per 1000 residents per week between May 25 and December 20, 2020. Among 5-star NHs, there were an average of 9.99 cases and 1.83 deaths per 1000 residents per week. The rate of confirmed cases of COVID-19 was 31% higher among 1-star NHs compared with 5-star NHs [model 1: incidence rate ratio (IRR) 1.31, 95% confidence interval (CI) 1.23-1.39], and the rate of COVID-19 deaths was 30% higher (IRR 1.30, 95% CI 1.20, 1.41). These associations were only partially explained by differences in community spread of COVID-19, case mix, and the for-profit status and size of NHs. CONCLUSIONS AND IMPLICATIONS: We found that COVID-19 case and death rates were substantially higher among NHs with lower star ratings, suggesting that NHs with quality much below average are more susceptible to the spread of COVID-19. This relationship, particularly with regard to case rates, can be partially attributed to external factors: lower-rated NHs are often located in areas with greater COVID-19 community spread and serve more socioeconomically vulnerable residents than higher-rated NHs.

A Geography of Risk: Structural Racism and Coronavirus Disease 2019 Mortality in the United States.

Coronavirus disease 2019 (COVID-19) is disproportionately burdening racial and ethnic minority groups in the United States. Higher risks of infection and mortality among racialized minorities are a consequence of structural racism, reflected in specific policies that date back centuries and persist today. Yet our surveillance activities do not reflect what we know about how racism structures risk. When measuring racial and ethnic disparities in deaths due to COVID-19, the Centers for Disease Control and Prevention statistically accounts for the geographic distribution of deaths throughout the United States to reflect the fact that deaths are concentrated in areas with different racial and ethnic distributions from those of the larger United States. In this commentary, we argue that such an approach misses an important driver of disparities in COVID-19 mortality, namely the historical forces that determine where individuals live, work, and play, and that consequently determine their risk of dying from COVID-19. We explain why controlling for geography downplays the disproportionate burden of COVID-19 on racialized minority groups in the United States. Finally, we offer recommendations for the analysis of surveillance data to estimate racial disparities, including shifting from distribution-based to risk-based measures, to help inform a more effective and equitable public health response to the pandemic.

Who Counts and Who Gets Counted? Health Equity in Infectious Disease Surveillance

[...]if health equity is not at the core of our surveillance activities, inequities will inevitably arise, persist, and widen over time. [...]our current surveillance activities have focused almost exclusively on the direct effects of the pandemic on population health, measured in terms of SARS-CoV-2 infections or deaths that can be directly attributed to COVID-19. ACKNOWLEDGING SOCIAL AND HISTORICAL CONTEXT The methodological choices we make when analyzing data can profoundly affect the conclusions we draw about the existence, direction, and magnitude of health inequities. [...]choices are not purely objective and value-free;rather, they reflect one's view of the world and judgments about what sources of variation in health status are permissible. [...]statistical adjustment for covariates such as age and geography when comparing disease risk across racial/ethnic groups reflects the belief that different distributions of age or geography are not important components of racial disparities in disease risk.7 By contrast, an analytic approach that seeks to understand how racial health inequities are produced might stratify on age and place to assess the roles of age and geography-population characteristics that are themselves shaped by structural racism-in determiningthe distribution of disease across population groups. Because the analysis and interpretation of surveillance data have real consequences for the subsequent implementation of public health interventions, it is critical that analyses be grounded in an antiracist approach that acknowledges the role of social and historical forces in shaping the distribution of disease.