Comparison of Weighted and Unweighted Population Data to Assess Inequities in Coronavirus Disease 2019 Deaths by Race/Ethnicity Reported by the US Centers for Disease Control and Prevention
Tori L Cowger, Brigette A Davis, Onisha S Etkins, Keletso Makofane, Jourdyn A Lawrence, Mary T Bassett, Nancy Krieger, Tori L Cowger, Brigette A Davis, Onisha S Etkins, Keletso Makofane, Jourdyn A Lawrence, Mary T Bassett, Nancy Krieger
Abstract
This cross-sectional study compares the use of weighted and unweighted population data to assess inequities in coronavirus disease 2019 (COVID-19) deaths by race/ethnicity as reported by the US Centers for Disease Control and Prevention (CDC).
Conflict of interest statement
Conflict of Interest Disclosures: None reported.
Figures
The figure shows examples of CDC geographical population weighting using a fictitious state with 3 counties (A) and actual CDC weighting of counties in New York State (B) by population, household crowding, and percentage of county population who are people of color (POC). The impact of the CDC’s method of geographical reweighting is demonstrated by juxtaposing the hypothetical example in panel A with actual county population data in panel B. By up-weighting counties such as county A (eg, Bronx), down-weighting counties such as county C (eg, Albany), and excluding counties such as county B (eg, Saratoga), the CDC inflates the proportion of residents of color in the weighted population, making their risk of death appear lower, while deflating the proportion of White residents, making their risk of death appear greater.
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Source: PubMed