Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts

被引:5
作者
Spangler, Keith R. [1 ]
Levy, Jonathan, I [1 ]
Fabian, M. Patricia [1 ]
Haley, Beth M. [1 ]
Carnes, Fei [1 ]
Patil, Prasad [2 ]
Tieskens, Koen [1 ]
Klevens, R. Monina [3 ]
Erdman, Elizabeth A. [4 ]
Troppy, T. Scott [3 ]
Leibler, Jessica H. [1 ]
Lane, Kevin J. [1 ]
机构
[1] Boston Univ, Sch Publ Hlth, Dept Environm Hlth, Boston, MA 02215 USA
[2] Boston Univ, Dept Biostat, Sch Publ Hlth, Boston, MA USA
[3] Bur Infect Dis & Lab Sci, MA Dept Publ Hlth, Boston, MA USA
[4] Off Populat Hlth, MA Dept Publ Hlth, Boston, MA USA
基金
美国国家卫生研究院;
关键词
COVID-19; Health equity; Data collection; Race and ethnicity; Surveillance epidemiology; PROVIDERS COLLECTING INFORMATION; LANGUAGE DATA-COLLECTION; HEALTH-CARE; PATIENTS ATTITUDES; DISPARITIES; PERCEPTIONS; EQUITY; STATES; PLAN;
D O I
10.1007/s40615-022-01387-3
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.
引用
收藏
页码:2071 / 2080
页数:10
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