Estimating the Unknown: Greater Racial and Ethnic Disparities in COVID-19 Burden After Accounting for Missing Race and Ethnicity Data.
Epidemiology
; 32(2): 157-161, 2021 03 01.
Article
in En
| MEDLINE
| ID: mdl-33323745
ABSTRACT
BACKGROUND:
Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data.METHODS:
We quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification.RESULTS:
The ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons.CONCLUSIONS:
These results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden.
Full text:
1
Database:
MEDLINE
Main subject:
Black or African American
/
Hispanic or Latino
/
Mortality
/
Indigenous Peoples
/
COVID-19
/
Hospitalization
Type of study:
Prognostic_studies
Limits:
Humans
Country/Region as subject:
America do norte
Language:
En
Journal:
Epidemiology
Journal subject:
EPIDEMIOLOGIA
Year:
2021
Type:
Article