Understanding the Differences in COVID-19 Case Fatality Rates Observed Across Alabama Counties.
Journal
Journal of public health management and practice : JPHMP
ISSN: 1550-5022
Titre abrégé: J Public Health Manag Pract
Pays: United States
ID NLM: 9505213
Informations de publication
Date de publication:
Historique:
entrez:
25
3
2021
pubmed:
26
3
2021
medline:
14
4
2021
Statut:
ppublish
Résumé
To understand county-level variation in case fatality rates of COVID-19, a statewide analysis of COVID-19 incidence and fatality data was performed, using publicly available incidence and case fatality rate data of COVID-19 for all 67 Alabama counties and mapped with health disparities at the county level. A specific adaptation of the Shewhart p-chart, called a funnel chart, was used to compare case fatality rates. Important differences in case fatality rates across the counties did not appear to be reflective of differences in testing or incidence rates. Instead, a higher prevalence of comorbidities and vulnerabilities was observed in high fatality rate counties, while showing no differences in access to acute care. Funnel charts reliably identify counties with unexpected high and low COVID-19 case fatality rates. Social determinants of health are strongly associated with such differences. These data may assist in public health decisions including vaccination strategies, especially in southern states with similar demographics.
Identifiants
pubmed: 33762546
doi: 10.1097/PHH.0000000000001366
pii: 00124784-202105000-00015
doi:
Types de publication
Journal Article
Langues
eng
Pagination
305-309Informations de copyright
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.
Références
Subbaraman N. Why daily death tolls have become unusually important in understanding the coronavirus pandemic [published online ahead of print April 9, 2020]. Nature. doi:10.1038/d41586-020-01008-1.
Centers for Disease Control and Prevention, National Center for Health Statistics. Understanding the numbers: provisional death counts and COVID-19. https://www.cdc.gov/nchs/data/nvss/coronavirus/Understanding-COVID-19-Provisional-Death-Counts.pdf . Accessed February 11, 2021.
Hawkins D. Social determinants of COVID-19 in Massachusetts, United States: an ecological study. J Prev Med Public Health. 2020;53(4):220–227.
Dalsania AK, Fastiggi MJ, Kahlam A, et al. The relationship between social determinants of health and racial disparities in COVID-19 mortality [published online ahead of print January 5, 2021]. J Racial Ethn Health Disparities. doi:10.1007/s40615-020-00952-y.
Provost LP, Murray SK. The Health Care Data Guide: Learning From Data for Improvement. San Francisco, CA: Jossey-Bass; 2011.
Spiegelhalter DJ. Funnel plots for comparing institutional performance. Stat Med. 2005;24(8):1185–1202.
Alabama's COVID-19 Data and Surveillance Dashboard. https://alpublichealth.maps.arcgis.com/apps/opsdashboard/index.html#/6d2771faa9da4a2786a509d82c8cf0f7 . Accessed November 25, 2020.
Coronavirus Resource Center. Johns Hopkins Coronavirus Resource Center. Baltimore, MD: John Hopkins University & Medicine; 2020. https://coronavirus.jhu.edu . Accessed November 13, 2020.
Razzaghi H, Wang Y, Lu H, et al. Estimated county-level prevalence of selected underlying medical conditions associated with increased risk for severe COVID-19 illness—United States, 2018. MMWR Morb Mortal Wkly Rep. 2020;69(29):945–950.
County Health Rankings & Roadmaps. Alabama county-based outcome measures. https://www.countyhealthrankings.org/app/alabama/2020/measure/outcomes/60/data . Accessed November 25, 2020.
Perla RJ, Provost SM, Parry GJ, Little K, Provost LP. Understanding variation in COVID-19 reported deaths with a novel Shewhart chart application [published online ahead of print June 26, 2020]. Int J Qual Health Care. doi:10.1093/intqhc/mzaa069.
Antoine D, Chollet F, Pascal L, et al. Effect of monitoring surgical outcomes using control charts to reduce major adverse events in patients: cluster randomised trial. BMJ. 2020;371:m3840.
Gale CP, Roberts AP, Batin PD, Hall AS. Funnel plots, performance variation and the Myocardial Infarction National Audit Project 2003-2004. BMC Cardiovasc Disord. 2006;6:34.
Dover DC, Schopflocher DP. Using funnel plots in public health surveillance. Popul Health Metr. 2011;9(1):58.
Krouse HJ. COVID-19 and the widening gap in health inequity. Otolaryngol Head Neck Surg. 2020;163(1):65–66.
Garg S, Kim L, Whitaker M, et al. Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019—COVID-NET, 14 states, March 1-30, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(15):458–464.