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

Chandra L. Ford, Bita Amani, Nina T. Harawa, Randall Akee, Gilbert C. Gee, Majid Sarrafzadeh, Consuela Abotsi-Kowu, Shayan Fazeli, Cindy Le, Ezinne Nwankwo, Davina Zamanzadeh, Anaelia Ovalle and Monica L. Ponder
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Chandra L. Ford: 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
Bita Amani: 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
Nina T. Harawa: 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
Randall Akee: 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
Gilbert C. Gee: 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
Majid Sarrafzadeh: Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA
Consuela Abotsi-Kowu: 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
Shayan Fazeli: Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA
Cindy Le: 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
Ezinne Nwankwo: 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
Davina Zamanzadeh: Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA
Anaelia Ovalle: Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA
Monica L. Ponder: Department of Communication, Culture & Media Studies, Cathy Hughes School of Communication, Howard University, Washington, DC 20059, USA

IJERPH, 2021, vol. 18, issue 24, 1-18

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 ( n = 10) of COVID surveillance systems ( n = 3), other public health systems (4) and systems tracking racism and/or social stigma ( n = 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.

Keywords: big data; surveillance; racism; evaluation; stigma; pandemic (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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