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Factors Contributing to the Insufficient Understanding of how COVID-19 is Intertwined with Race and Ethnicity in the United States

Kalix, Elora Corrine (2021) Factors Contributing to the Insufficient Understanding of how COVID-19 is Intertwined with Race and Ethnicity in the United States. Master Essay, University of Pittsburgh.

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Background: The United States is currently experiencing how the COVID-19 pandemic is disproportionately affecting many non-white communities, yet there continues to be difficulty in accurately analyzing and interpreting racial and ethnic disparities, as the methods for collecting and reporting these data vary dramatically across the nation. The goals of this study were to provide an overview of how states were reporting their COVID-19 race and ethnicity data and to explore if there were state-level factors associated with how Hispanic ethnicity was being reported.

Methods: Data on all fifty states’ reporting of race and ethnicity distributions of COVID-19 cases, hospitalizations, and deaths were collected from state health departments’ publicly available COVID-19 data. State factors that included sociodemographics, healthcare, and politics were collected and used in univariate and multivariate logistic regression analyses assessing associations with the outcome of reporting ethnicity as a variable separate from or included with race.

Results: As of February 2021, there were 49 (98%) states publicly reporting race and ethnicity data for COVID-19 cases, 17 (34%) for COVID-19 hospitalizations, and 45 (90%) for COVID-19 deaths. Indicators used for race and ethnicity varied across states. For all states, missing race and/or ethnicity of COVID-19 cases and deaths data ranged from 5% to 67.8% for cases and 0% to 43.3% for deaths. In the multivariate logistic regression model with case data, two predictors were statistically significantly associated with lower odds of reporting ethnicity separate from race: higher state proportion of Hispanic population (OR 0.81; 95%CI 0.68, 0.97) and higher state median income (OR 0.70 95%CI 0.52, 0.92). In the multivariate logistic regression with death data, the only factor that was statistically significant was median income (OR 0.78; 95%CI 0.65, 0.94).

Conclusion: Across the United States, data on race and ethnicity in cases, hospitalizations, and deaths from COVID-19 vary in their reporting. It is imperative that the collection and reporting of COVID-19 race and ethnicity data be improved, as the ability to have meaningful impact on this public health concern is contingent on high-quality data.


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Item Type: Other Thesis, Dissertation, or Long Paper (Master Essay)
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Kalix, Elora Corrineeck45@pitt.edueck45
ContributionContributors NameEmailPitt UsernameORCID
Committee Chairvan Panhuis, Wilbertwgvanpanhuis@gmail.comUNSPECIFIEDUNSPECIFIED
Committee MemberFine, Michael Jonahmichael.fine@va.govUNSPECIFIEDUNSPECIFIED
Committee MemberEl Khoudary, Samar R.elkhoudarys@edc.pitt.eduelkhoudarysUNSPECIFIED
Committee MemberGary-Webb, Tiffany L.tgary@pitt.edutgaryUNSPECIFIED
Date: 13 May 2021
Date Type: Completion
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 59
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Epidemiology
Degree: MPH - Master of Public Health
Thesis Type: Master Essay
Refereed: Yes
Date Deposited: 13 May 2021 17:39
Last Modified: 13 May 2023 05:15


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