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现有监测系统监测种族主义、社会耻辱和 COVID 不平等现象的充分性:详细评估和建议。

Adequacy of Existing Surveillance Systems to Monitor Racism, Social Stigma and COVID Inequities: A Detailed Assessment and Recommendations.

机构信息

Center for the Study of Racism, Social Justice & Health, Department of Community Health Sciences, Fielding School of Public Health, University of California at Los Angeles, Los Angeles, CA 90095, USA.

Department of Urban Public Health, College of Science & Health, Charles R. Drew University of Medicine & Science, Los Angeles, CA 90059, USA.

出版信息

Int J Environ Res Public Health. 2021 Dec 12;18(24):13099. doi: 10.3390/ijerph182413099.

Abstract

The populations impacted most by COVID are also impacted by racism and related social stigma; however, traditional surveillance tools may not capture the intersectionality of these relationships. We conducted a detailed assessment of diverse surveillance systems and databases to identify characteristics, constraints and best practices that might inform the development of a novel COVID surveillance system that achieves these aims. We used subject area expertise, an expert panel and CDC guidance to generate an initial list of N > 50 existing surveillance systems as of 29 October 2020, and systematically excluded those not advancing the project aims. This yielded a final reduced group ( = 10) of COVID surveillance systems ( = 3), other public health systems (4) and systems tracking racism and/or social stigma ( = 3, which we evaluated by using CDC evaluation criteria and Critical Race Theory. Overall, the most important contribution of COVID-19 surveillance systems is their real-time (e.g., daily) or near-real-time (e.g., weekly) reporting; however, they are severely constrained by the lack of complete data on race/ethnicity, making it difficult to monitor racial/ethnic inequities. Other public health systems have validated measures of psychosocial and behavioral factors and some racism or stigma-related factors but lack the timeliness needed in a pandemic. Systems that monitor racism report historical data on, for instance, hate crimes, but do not capture current patterns, and it is unclear how representativeness the findings are. Though existing surveillance systems offer important strengths for monitoring health conditions or racism and related stigma, new surveillance strategies are needed to monitor their intersecting relationships more rigorously.

摘要

受 COVID 影响最大的人群也受到种族主义和相关社会耻辱感的影响;然而,传统的监测工具可能无法捕捉到这些关系的交叉性。我们对各种监测系统和数据库进行了详细评估,以确定可能为开发实现这些目标的新型 COVID 监测系统提供信息的特征、限制和最佳实践。我们利用主题专业知识、专家小组和疾控中心的指导,生成了截至 2020 年 10 月 29 日的现有监测系统(N>50)的初始列表,并系统地排除了那些不符合项目目标的系统。这产生了一个最终的简化组(=10),其中包括 COVID 监测系统(=3)、其他公共卫生系统(4)和跟踪种族主义和/或社会耻辱感的系统(=3),我们通过使用疾控中心评估标准和关键种族理论对其进行了评估。总体而言,COVID-19 监测系统最重要的贡献是其实时(例如,每日)或近实时(例如,每周)报告;然而,它们受到缺乏完整的种族/族裔数据的严重限制,这使得很难监测种族/族裔不平等现象。其他公共卫生系统具有经过验证的心理社会和行为因素以及一些与种族主义或耻辱感相关的因素的衡量标准,但缺乏大流行期间所需的及时性。监测种族主义的系统报告了仇恨犯罪等历史数据,但无法捕捉当前的模式,也不清楚调查结果的代表性如何。尽管现有的监测系统为监测健康状况或种族主义和相关耻辱感提供了重要优势,但需要新的监测策略来更严格地监测它们的交叉关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9dc/8701783/5e050b692602/ijerph-18-13099-g001.jpg

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