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种族和族裔数据公正:监测数据分类的紧迫性。

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

作者信息

Gelpí-Acosta Camila, Cano Manuel, Hagan Holly

机构信息

LaGuardia Community College, City University of New York, USA.

School of Social Work, Arizona State University, USA.

出版信息

Drug Alcohol Depend Rep. 2022 Sep;4. doi: 10.1016/j.dadr.2022.100082. Epub 2022 Jul 27.

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.

摘要

包括美国在内的工业化国家的疾病和药物过量监测,历来依靠非西班牙裔黑人、白人、亚洲人和西班牙裔/拉丁裔等种族和族裔分类来描述其所涵盖的人群。这些类别无论是按出生地还是按种族,都低估了这些群体内部显著的艾滋病毒、丙型肝炎(HCV)和药物过量差异。对于美国社会经济处境不利的有色人种来说,一线工作者(即减少伤害外展工作者、个案管理员等)是艾滋病毒、丙型肝炎和药物滥用护理连续统一体的关键切入点。种族/族裔数据汇总未能以提高这些工作者效率的方式来描述弱势群体。对艾滋病毒、丙型肝炎和药物过量数据进行分类,对于终结艾滋病毒、更有效地控制丙型肝炎和药物过量,以及更接近反种族主义流行病学而言,刻不容缓。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56b1/9948807/2253be36c131/gr1.jpg

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