Racial and ethnic data justice: The urgency of surveillance data disaggregation

Abstract

Disease and overdose surveillance across industrialized countries, including the United States (US), have historically relied upon racial and ethnic classifications such as Non-Hispanic Black, White, Asian and Hispanic/Latinx to characterize the populations it describes. These categories underestimate significant HIV, hepatitis C (HCV) and drug overdose variance within these groups, by both place of birth and ethnicity. For socioeconomically disadvantaged people of color in the US, frontline workers (i.e., harm reduction outreach workers, case managers, etc.) are a medullar entry point to the HIV, HCV, and drug misuse care continuums. Racial/ethnic data aggregates fail to characterize vulnerable groups in ways that can increase these workers’ efficacy. HIV, HCV, and overdose data disaggregation is urgent to end HIV and to control HCV and drug overdoses more effectively, and to also move closer to an anti-racist epidemiology.

Keywords

• Surveillance disaggregation
• Race
• Ethnicity
• HIV
• HCV
• Overdose