Excess Mortality Associated With COVID-19 by Demographic Group: Evidence From Florida and Ohio
Language English Country United States Media print-electronic
Document type Journal Article
PubMed
34436948
PubMed Central
PMC8579393
DOI
10.1177/00333549211041550
Knihovny.cz E-resources
- Keywords
- demographic factors, disease outbreaks, epidemiology, infectious disease, public health, racial disparities,
- MeSH
- COVID-19 epidemiology mortality MeSH
- Child MeSH
- Adult MeSH
- Infant MeSH
- Comorbidity MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Pandemics MeSH
- Child, Preschool MeSH
- Cause of Death MeSH
- Racial Groups MeSH
- SARS-CoV-2 MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Sex Factors MeSH
- Socioeconomic Factors MeSH
- Age Factors MeSH
- Health Status MeSH
- Check Tag
- Child MeSH
- Adult MeSH
- Infant MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Child, Preschool MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Florida epidemiology MeSH
- Ohio epidemiology MeSH
- United States epidemiology MeSH
OBJECTIVE: COVID-19 mortality varies across demographic groups at the national level, but little is known about potential differences in COVID-19 mortality across states. The objective of this study was to estimate the number of all-cause excess deaths associated with COVID-19 in Florida and Ohio overall and by sex, age, and race. METHODS: We calculated the number of weekly and cumulative excess deaths among adults aged ≥20 from March 15 through December 5, 2020, in Florida and Ohio as the observed number of deaths less the expected number of deaths, adjusted for population, secular trends, and seasonality. We based our estimates on death certificate data from the previous 10 years. RESULTS: The results were based on ratios of observed-to-expected deaths. The ratios were 1.17 (95% prediction interval, 1.14-1.21) in Florida and 1.15 (95% prediction interval, 1.11-1.19) in Ohio. Although the largest number of excess deaths occurred in the oldest age groups, in both states the ratios of observed-to-expected deaths were highest among adults aged 20-49 (1.21; 95% prediction interval, 1.11-1.32). The ratio of observed-to-expected deaths for the Black population was especially elevated in Florida. CONCLUSIONS: Although excess deaths were largely concentrated among older cohorts, the high ratios of observed-to-expected deaths among younger age groups indicate widespread effects of COVID-19. The high levels of observed-to-expected deaths among Black adults may reflect in part disparities in infection rates, preexisting conditions, and access to care. The finding of high excess deaths among Black adults deserves further attention.
College of Behavioral and Community Sciences University of South Florida Tampa FL USA
College of Public Health University of South Florida Tampa FL USA
Department of Neurology Charles University and Motol University Hospital Prague Czech Republic
International Clinical Research Center St Anne's University Hospital Brno Czech Republic
See more in PubMed
Council of State and Territorial Epidemiologists . Position statement: standardized surveillance case definition and national notification for 2019 novel coronavirus disease. April 5, 2020. Accessed June 8, 2021. https://asprtracie.hhs.gov/technical-resources/resource/8322/standardized-surveillance-case-definition-and-national-notification-for-2019-novel-coronavirus-disease-covid-19
Resnick B., Scott D. America’s shamefully slow coronavirus testing threatens all of us. Vox. March 12, 2020. Accessed April 9, 2021. https://www.vox.com/science-and-health/2020/3/12/21175034/coronavirus-covid-19-testing-usa
Goh KJ., Wong J., Tien J-CC. et al.. Preparing your intensive care unit for the COVID-19 pandemic: practical considerations and strategies. Crit Care. 2020;24(1):215.10.1186/s13054-020-02916-4 PubMed DOI PMC
Sehdev AES., Hutchins GM. Problems with proper completion and accuracy of the cause-of-death statement. Arch Intern Med. 2001;161(2):277-284.10.1001/archinte.161.2.277 PubMed DOI
McGivern L., Shulman L., Carney JK., Shapiro S., Bundock E. Death certification errors and the effect on mortality statistics. Public Health Rep. 2017;132(6):669-675.10.1177/0033354917736514 PubMed DOI PMC
Schuppener LM., Olson K., Brooks EG. Death certification: errors and interventions. Clin Med Res. 2020;18(1):21-26.10.3121/cmr.2019.1496 PubMed DOI PMC
Czeisler MÉ., Marynak K., Clarke KEN. et al.. Delay or avoidance of medical care because of COVID-19–related concerns—United States, June 2020. MMWR Morb Mortal Wkly Rep. 2020;69(36):1250-1257.10.15585/mmwr.mm6936a4 PubMed DOI PMC
Webb L. COVID-19 lockdown: a perfect storm for older people’s mental health. J Psychiatr Ment Health Nurs. 2021;28(2):300. 10.1111/jpm.12644 PubMed DOI PMC
Zhai Y., Du X. Addressing collegiate mental health amid COVID-19 pandemic. Psychiatry Res. 2020;288:113003. 10.1016/j.psychres.2020.113003 PubMed DOI PMC
Stephens KU Sr., Grew D., Chin K. et al.. Excess mortality in the aftermath of Hurricane Katrina: a preliminary report. Disaster Med Public Health Prep. 2007;1(1):15-20.10.1097/DMP.0b013e3180691856 PubMed DOI
Santos-Burgoa C., Sandberg J., Suárez E. et al.. Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis. Lancet Planet Health. 2018;2(11):e478-e488.10.1016/S2542-5196(18)30209-2 PubMed DOI
Santos-Lozada AR., Howard JT. Use of death counts from vital statistics to calculate excess deaths in Puerto Rico following Hurricane Maria. JAMA. 2018;320(14):1491-1493.10.1001/jama.2018.10929 PubMed DOI
Whitman S., Good G., Donoghue ER., Benbow N., Shou W., Mou S. Mortality in Chicago attributed to the July 1995 heat wave. Am J Public Health. 1997;87(9):1515-1518.10.2105/AJPH.87.9.1515 PubMed DOI PMC
Krieger N., Chen JT., Waterman PD. Excess mortality in men and women in Massachusetts during the COVID-19 pandemic. Lancet. 2020;395(10240):1829.10.1016/S0140-6736(20)31234-4 PubMed DOI PMC
Weinberger DM., Chen J., Cohen T. et al.. Estimation of excess deaths associated with the COVID-19 pandemic in the United States, March to may 2020. MMWR Morb Mortal Wkly Rep. 2020;180(10):1336-1344.10.1001/jamainternmed.2020.3391 PubMed DOI PMC
Freitas ARR., de Medeiros NM., Frutuoso LCV. et al.. Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy—preliminary results of the evaluation of six Brazilian capitals. Preprint. Posted online May 12, 2020. medRxiv.10.1101/2020.05.08.20093617 PubMed DOI PMC
Vieira A., Ricoca VP., Aguiar P., Abrantes A. Rapid estimation of excess mortality in times of COVID-19 in Portugal—beyond reported deaths. Preprint. Posted online May 19, 2020. medRxiv.10.1101/2020.05.14.20100909 PubMed DOI PMC
Kontopantelis E., Mamas MA., Deanfield J., Asaria M., Doran T. Excess mortality in England and Wales during the first wave of the COVID-19 pandemic. J Epidemiol Community Health. 2021;75(3):212-223.10.1136/jech-2020-214764 PubMed DOI PMC
McLeay S. Measuring excess mortality: a second look at Germany. Preprint. Posted online June 17, 2020. SSRN.10.2139/ssrn.35=626618 DOI
Modi C., Boehm V., Ferraro S. et al.. How deadly is COVID-19? A rigorous analysis of excess mortality and age-dependent fatality rates in Italy. Preprint. Posted online May 14, 2020. medRxiv.10.1101/2020.04.15.20067074 DOI
Rossen LM., Branum AM., Ahmad FB., Sutton P., Anderson RN. Excess deaths associated with COVID-19, by age and race and ethnicity—United states, January 26–October 3, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(42):1522-1527.10.15595/mmwr.mm6942e2 PubMed DOI PMC
Faust JS., Krumholz HM., Du C. et al.. All-cause excess mortality and COVID-19–related mortality among US adults aged 25-44 years, March–July 2020. JAMA. 2021;325(8):785-787.10.1001/jama.2020.24243 PubMed DOI PMC
Centers for Disease Control and Prevention . Excess deaths associated with COVID-19. January 17, 2021. Accessed February 12, 2021. https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
Centers for Disease Control and Prevention . COVID data tracker. January 10, 2021. Accessed January 15, 2021. https://covid.cdc.gov/covid-data-tracker/#compare-trends_newcases
Ohio Department of Health . Ohio Public Health Information Warehouse. Accessed January 8, 2021. http://publicapps.odh.ohio.gov/EDW/ DataBrowser/Browse/Mortality
Centers for Disease Control and Prevention . Readers’ guide: understanding MMWR weekly tables and annual reports about National Notifiable Diseases Surveillance System data. Accessed December 10, 2020. https://wwwn.cdc.gov/nndss/document/guide_to_interpreting_provisional_and_finalized_nndss_data_tables.pdf
National Center for Health Statistics . Vintage 2019 postcensal estimates of the resident population of the United States (April 1, 2010, July 1, 2010-July 1, 2019), by year, county, single-year of age (0, 1, 2,. ., 85 years and over), bridged race, Hispanic origin, and sex. Prepared under a collaborative arrangement with the U.S. Census Bureau. Accessed December 10, 2020. https://www.cdc.gov/nchs/nvss/bridged_race.htm
GitHub . COVID-19 in Ohio and Florida. Accessed July 12, 2021. https://github.com/troyquast/covid19_fl_oh
Patzer RE., McClellan WM. Influence of race, ethnicity and socioeconomic status on kidney disease. Nat Rev Nephrol. 2012;8(9):533-541.10.1038/nrneph.2012.117 PubMed DOI PMC
Akinbami LJ., Moorman JE., Simon AE., Schoendorf KC. Trends in racial disparities for asthma outcomes among children 0 to 17 years, 2001-2010. J Allergy Clin Immunol. 2014;134(3):547-553.10.1016/j.jaci.2014.05.037 PubMed DOI PMC
Petersen EE., Davis NL., Goodman D. et al.. Racial/ethnic disparities in pregnancy-related deaths—United States, 2007-2016. MMWR Morb Mortal Wkly Rep. 2019;68(35):762-765.10.15585/mmwr.mm6835a3 PubMed DOI PMC
Mahajan UV., Larkins-Pettigrew M. Racial, economic, and health inequality and COVID-19 infection in the United States. J Public Health. 2020;42(3):445-447.10.1093/pubmed/fdaa070 PubMed DOI PMC
Azar KMJ., Shen Z., Romanelli RJ. et al.. Disparities in outcomes among COVID-19 patients in a large health care system in California. Health Aff (Millwood). 2020;39(7):1253-1262.10.1377/hlthaff.2020.00598 PubMed DOI
Abedi V., Olulana O., Avula V. et al.. Racial, economic, and health inequality and COVID-19 infection in the United States. J Racial Ethn Health Disparities. 2021;8(3):732-742.10.1007/s40615-020-00833-4 PubMed DOI PMC
Millett GA., Jones AT., Benkeser D. et al.. Assessing differential impacts of COVID-19 on Black communities. Ann Epidemiol. 2020;47:37-44.10.1016/j.annepidem.2020.05.003 PubMed DOI PMC
Ioannidis JPA. Infection fatality rate of COVID-19 inferred from seroprevalence data. Bull World Health Organ. 2021;99(1):19F-33F.10.2471/BLT.20.265892 PubMed DOI PMC
Holtgrave DR., Barranco MA., Tesoriero JM., Blog DS., Rosenberg ES. Assessing racial and ethnic disparities using a COVID-19 outcomes continuum for New York State. Ann Epidemiol. 2020;48(7):9-14.10.1016/j.annepidem.2020.06.010 PubMed DOI PMC
Laurencin CT., McClinton A. The COVID-19 pandemic: a call to action to identify and address racial and ethnic disparities. J Racial Ethn Health Disparities. 2020;7(3):398-402.10.1007/s40615-020-00756-0 PubMed DOI PMC
Selden TM., Berdahl TA. COVID-19 and racial/ethnic disparities in health risk, employment, and household composition. Health Aff (Millwood). 2020;39(9):1624-1632.10.1377/hlthaff.2020.00897 PubMed DOI
Wrigley-Field E., Garcia S., Leider JP., Robertson C., Wurtz R. Racial disparities in COVID-19 and excess mortality in Minnesota. Socius. 2020;6:237802312098091.10.1177/2378023120980918 PubMed DOI PMC