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Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake
Inequities in COVID-19 vaccine uptake by racialized groups have been persistent throughout the vaccine rollout, leading to disparate burdens of COVID-19 outcomes. A cross-sectional study was conducted to determine COVID-19 vaccine uptake across racialized groups within the nine-county Finger Lakes r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143258/ https://www.ncbi.nlm.nih.gov/pubmed/37112788 http://dx.doi.org/10.3390/vaccines11040876 |
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author | Russ, Savanah Bramley, John Liu, Yu Boyce, Irena |
author_facet | Russ, Savanah Bramley, John Liu, Yu Boyce, Irena |
author_sort | Russ, Savanah |
collection | PubMed |
description | Inequities in COVID-19 vaccine uptake by racialized groups have been persistent throughout the vaccine rollout, leading to disparate burdens of COVID-19 outcomes. A cross-sectional study was conducted to determine COVID-19 vaccine uptake across racialized groups within the nine-county Finger Lakes region of New York State in December 2021. Cross-matching and validation were performed across multiple health information systems for the region to reduce the percentage of vaccine records with missing race information. Additionally, imputation techniques were applied to address the remaining missing values. Uptake of ≥1 dose of the COVID-19 vaccine by race was then examined. By December 2021, 828,551 individuals in our study region had received ≥1 dose of the COVID-19 vaccine, with ~25% having missing race values. Cross-matching and validation within existing records reduced this to ~7%. Uptake of ≥1 dose of a COVID-19 vaccine was greatest among individuals identifying as White, followed by those identifying as Black. The application of imputation techniques reduced the percent of missing race values to <1%; however, this reduction did not significantly change the distribution of vaccine uptake across race groups. Utilization of relevant health information systems, accompanied by imputation techniques, stands to greatly reduce the burden of missing race data within vaccine registries, facilitating accurate targeted interventions to mitigate inequities in COVID-19 vaccination. |
format | Online Article Text |
id | pubmed-10143258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101432582023-04-29 Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake Russ, Savanah Bramley, John Liu, Yu Boyce, Irena Vaccines (Basel) Communication Inequities in COVID-19 vaccine uptake by racialized groups have been persistent throughout the vaccine rollout, leading to disparate burdens of COVID-19 outcomes. A cross-sectional study was conducted to determine COVID-19 vaccine uptake across racialized groups within the nine-county Finger Lakes region of New York State in December 2021. Cross-matching and validation were performed across multiple health information systems for the region to reduce the percentage of vaccine records with missing race information. Additionally, imputation techniques were applied to address the remaining missing values. Uptake of ≥1 dose of the COVID-19 vaccine by race was then examined. By December 2021, 828,551 individuals in our study region had received ≥1 dose of the COVID-19 vaccine, with ~25% having missing race values. Cross-matching and validation within existing records reduced this to ~7%. Uptake of ≥1 dose of a COVID-19 vaccine was greatest among individuals identifying as White, followed by those identifying as Black. The application of imputation techniques reduced the percent of missing race values to <1%; however, this reduction did not significantly change the distribution of vaccine uptake across race groups. Utilization of relevant health information systems, accompanied by imputation techniques, stands to greatly reduce the burden of missing race data within vaccine registries, facilitating accurate targeted interventions to mitigate inequities in COVID-19 vaccination. MDPI 2023-04-21 /pmc/articles/PMC10143258/ /pubmed/37112788 http://dx.doi.org/10.3390/vaccines11040876 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Russ, Savanah Bramley, John Liu, Yu Boyce, Irena Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title | Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title_full | Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title_fullStr | Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title_full_unstemmed | Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title_short | Bolstering the Measurement of Racial Inequity of COVID-19 Vaccine Uptake |
title_sort | bolstering the measurement of racial inequity of covid-19 vaccine uptake |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143258/ https://www.ncbi.nlm.nih.gov/pubmed/37112788 http://dx.doi.org/10.3390/vaccines11040876 |
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