Alternative Methods for Grouping Race and Ethnicity to Monitor COVID-19 Outcomes and Vaccination Coverage

Using available COVID-19 case and vaccination data, the CDC compared three different methodologies for grouping race/ethnicity COVID-19 data. Two of these methodologies are focused on how to group race/ethnicity when fields are missing. The results show that methods that use race information when ethnicity is missing resulted in higher estimated COVID-19 cases, incidence, and vaccination coverage. However, more work must be done to improve upon these methods in order to create more equitable and reliable data.

Resource Details

• Population: Black or African American|Hispanic, Latino, or Latinx
• Topics of Practice: Data Collection and Analysis
• Outcomes of Interest: Improve Data Infrastructure
• Level of Evidence: Emerging
• Tools or Materials Included in Resource: No
• Outside of US: No