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Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439275/ https://www.ncbi.nlm.nih.gov/pubmed/36056195 http://dx.doi.org/10.1007/s40615-022-01387-3 |
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author | Spangler, Keith R. Levy, Jonathan I. Fabian, M. Patricia Haley, Beth M. Carnes, Fei Patil, Prasad Tieskens, Koen Klevens, R. Monina Erdman, Elizabeth A. Troppy, T. Scott Leibler, Jessica H. Lane, Kevin J. |
author_facet | Spangler, Keith R. Levy, Jonathan I. Fabian, M. Patricia Haley, Beth M. Carnes, Fei Patil, Prasad Tieskens, Koen Klevens, R. Monina Erdman, Elizabeth A. Troppy, T. Scott Leibler, Jessica H. Lane, Kevin J. |
author_sort | Spangler, Keith R. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9439275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-94392752022-09-06 Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts Spangler, Keith R. Levy, Jonathan I. Fabian, M. Patricia Haley, Beth M. Carnes, Fei Patil, Prasad Tieskens, Koen Klevens, R. Monina Erdman, Elizabeth A. Troppy, T. Scott Leibler, Jessica H. Lane, Kevin J. J Racial Ethn Health Disparities Article 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. Springer International Publishing 2022-09-02 2023 /pmc/articles/PMC9439275/ /pubmed/36056195 http://dx.doi.org/10.1007/s40615-022-01387-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Spangler, Keith R. Levy, Jonathan I. Fabian, M. Patricia Haley, Beth M. Carnes, Fei Patil, Prasad Tieskens, Koen Klevens, R. Monina Erdman, Elizabeth A. Troppy, T. Scott Leibler, Jessica H. Lane, Kevin J. Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title | Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title_full | Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title_fullStr | Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title_full_unstemmed | Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title_short | Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts |
title_sort | missing race and ethnicity data among covid-19 cases in massachusetts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439275/ https://www.ncbi.nlm.nih.gov/pubmed/36056195 http://dx.doi.org/10.1007/s40615-022-01387-3 |
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