Racial and Ethnic Disparities in Population-Level Covid-19 Mortality
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Caregiver loss is even more heavily concentrated in vulnerable populations than shown in our results.
“Our ability to observe more specific geographic and demographic disparities is constrained by the limitations of available data, but we can infer from other analyses that caregiver loss is even more heavily concentrated in vulnerable populations than shown in our results.”
From Parental and Other Caregiver Loss Due to COVID-19 in the United States: Prevalence by Race, State, Relationship, and Child Age (2023) · cites this paper as [11]
The Results report substantially higher COVID-19 mortality among Black and Latinx populations than among White populations. The Discussion says unadjusted mortality rates can underestimate those disparities. The paper does not examine caregiver loss, so it supports the mortality-disparity basis for the inference but not the stated concentration of caregiver loss. (LLM, conf=0.83)
Experimental — accuracy not yet measuredLow-income individuals are at highest risk of death from COVID-19, and low-income counties faced disproportionately large shares of COVID-19 deaths, even after controlling for other indicators of wellbeing.
“Low-income individuals are at highest risk of death from COVID-19 and low-income counties faced disproportionately large shares of COVID-19 deaths, even after controlling for other indicators of wellbeing in two studies focused on individual and communitylevel associations with COVID-19 mortality rates of all persons [11, 28].”
From Parental and Other Caregiver Loss Due to COVID-19 in the United States: Prevalence by Race, State, Relationship, and Child Age (2023) · cites this paper as [11]
The Methods and Results (pages unavailable in our copy) analyze COVID-19 mortality by race and ethnicity, with adjustment for age. Searches for income, poverty, county-level mortality, and wellbeing found no passage addressing whether low-income individuals or counties had higher mortality. (LLM, conf=0.76)
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- [1]APM Research Lab Staff. The color of Coronovirus: Covid-19 deaths by race and ethnicity in the U.S. Associated Press News. 2020.
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Wrigley‐Field, E., Garcia, S., Leider, J. P., & Riper, D. C. V. (2021) · Health Affairs · doi:10.1377/hlthaff.2021.00365 · Cited by 33 · see citing works
COVID-19 Outcomes Among the Hispanic Population of 27 Large US Cities, 2020–2021
Ramos, I. P. D., Lazo, M., Schnake-Mahl, A. S., Li, R., Martínez-Donate, A. P., Roux, A. V. D., & Bilal, U. (2022) · American Journal of Public Health · doi:10.2105/ajph.2022.306809 · Cited by 31 · see citing works
Cefalu, W. T., & Rodgers, G. P. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.02.006 · Cited by 30 · see citing works
Ong, P. M., Pech, C., Gutierrez, N. R., & Mays, V. M. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18094829 · Cited by 30 · see citing works
Dorélien, A., Ramen, A., Swanson, I., & Hill, R. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-06610-w · Cited by 30 · see citing works
Torres‐Torres, J., Martinez-Portilla, R. J., y Sosa, S. E., Estrada‐Gutiérrez, G., Solis‐Paredes, J. M., Villafán-Bernal, J. R., Medina-Jimenez, V., Rodriguez-Morales, A. J., Rojas‐Zepeda, L., & Poon, L. C. (2021) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.24797 · Cited by 31 · see citing works
Empirical evidence on structural racism as a driver of racial inequities in COVID-19 mortality
Brown, T. H., Kamis, C., & Homan, P. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.1007053 · Cited by 30 · see citing works
Williamson, C. G., Hadaya, J. E., Mandelbaum, A. D., Verma, A., Gandjian, M., Rahimtoola, R., & Benharash, P. (2021) · CHEST Journal · doi:10.1016/j.chest.2021.02.018 · Cited by 29 · see citing works
The impact of race and ethnicity on outcomes in 19,584 adults hospitalized with COVID-19
Návar, A. M., Purinton, S., Hou, Q., Taylor, R. J., & Peterson, E. D. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254809 · Cited by 29 · see citing works
Falzarano, F. B., Winoker, H., Burke, R. V., Mendoza, J. A., Munoz, F., Tergas, A. I., Maciejewski, P. K., & Prigerson, H. G. (2022) · Health Equity · doi:10.1089/heq.2022.0031 · Cited by 28 · see citing works
Bassett, I. V., Triant, V. A., Bunda, B. A., Selvaggi, C. A., Shinnick, D. J., He, W. W., Lu, F., Porneala, B., Cao, T., Lubitz, S. A., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0244270 · Cited by 28 · see citing works
Economic Inequality and COVID-19 Deaths and Cases in the First Wave: A Cross-Country Analysis
Davies, J. (2021) · Canadian Public Policy · doi:10.3138/cpp.2021-033 · Cited by 28 · see citing works
The Experience of Homebound Older Adults During the COVID-19 Pandemic
Ankuda, C. K., Kotwal, A., Reckrey, J. M., Harrison, K. L., & Ornstein, K. A. (2022) · Journal of General Internal Medicine · doi:10.1007/s11606-021-07361-9 · Cited by 28 · see citing works
- Authors
- Gross, C. P., Essien, U. R., Pasha, S., Gross, J. R., Wang, S.-Y., & Nunez-Smith, M.
- Affiliations
- Yale Cancer Center (US)
- University of Pittsburgh (US)
- Tufts University (US)
- Corresponding author
- Gross, Cary P.
- Venue
- Journal of General Internal Medicine
- Published
- 2020-08-04
- Volume
- 35
- Issue
- 10
- Pages
- 3097-3099
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC7402388
- OpenAlex
- W3046980818
- Cited by
- 410
- References
- 2
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 26 · 2023: 65 · 2022: 106 · 2021: 136 · 2020: 51
- FWCI
- 14.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of General Internal Medicine (publishedVersion)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Pfizer
- Yale University
- National Comprehensive Cancer Network
- Flatiron Health
- National Institutes of Health (UL1TR001863)
- National Center for Advancing Translational Sciences
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Health Professions › General Health Professions › Healthcare Systems and Challenges
- Keywords
- COVID-19 mortality, racial and ethnic disparities, African Americans, Hispanic Americans, age-adjusted mortality, indirect standardization, standardized mortality ratio, racial disparities in health, COVID-19 pandemic, United States states, New York City, New Jersey, New York, California, Texas
- MeSH terms
- Data Accuracy, Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Aged, Aged, 80 and over, Black or African American, Cross-Sectional Studies, Female, Hispanic or Latino, Humans, Male, Middle Aged, Pneumonia, Viral, United States, Coronavirus Infections, White People, Health Status Disparities, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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