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Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan
COVID-19′s rapid onset left many public health entities scrambling. But establishing community-academic partnerships to digest data and create advocacy steps offers an opportunity to link research to action. Here we document disparities in COVID-19 death uncovered during a collaboration between a he...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420028/ https://www.ncbi.nlm.nih.gov/pubmed/36460446 http://dx.doi.org/10.1016/j.sste.2022.100536 |
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author | Sadler, Richard Casey Wojciechowski, Thomas W. Buchalski, Zachary Harris, Alan Lederer, Danielle Peters, Matt Hackert, Pamela Furr-Holden, C. Debra |
author_facet | Sadler, Richard Casey Wojciechowski, Thomas W. Buchalski, Zachary Harris, Alan Lederer, Danielle Peters, Matt Hackert, Pamela Furr-Holden, C. Debra |
author_sort | Sadler, Richard Casey |
collection | PubMed |
description | COVID-19′s rapid onset left many public health entities scrambling. But establishing community-academic partnerships to digest data and create advocacy steps offers an opportunity to link research to action. Here we document disparities in COVID-19 death uncovered during a collaboration between a health department and university research center. We geocoded COVID-19 deaths in Genesee County, Michigan, to model clusters during two waves in spring and fall 2020. We then aggregated these deaths to census block groups, where group-based trajectory modeling identified latent patterns of change and continuity. Linking with socioeconomic data, we identified the most affected communities. We discovered a geographic and racial gap in COVID-19 deaths during the first wave, largely eliminated during the second. Our partnership generated added and immediate value for community partners, including around prevention, testing, treatment, and vaccination. Our identification of the aforementioned racial disparity helped our community nearly eliminate disparities during the second wave. |
format | Online Article Text |
id | pubmed-9420028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94200282022-08-30 Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan Sadler, Richard Casey Wojciechowski, Thomas W. Buchalski, Zachary Harris, Alan Lederer, Danielle Peters, Matt Hackert, Pamela Furr-Holden, C. Debra Spat Spatiotemporal Epidemiol Article COVID-19′s rapid onset left many public health entities scrambling. But establishing community-academic partnerships to digest data and create advocacy steps offers an opportunity to link research to action. Here we document disparities in COVID-19 death uncovered during a collaboration between a health department and university research center. We geocoded COVID-19 deaths in Genesee County, Michigan, to model clusters during two waves in spring and fall 2020. We then aggregated these deaths to census block groups, where group-based trajectory modeling identified latent patterns of change and continuity. Linking with socioeconomic data, we identified the most affected communities. We discovered a geographic and racial gap in COVID-19 deaths during the first wave, largely eliminated during the second. Our partnership generated added and immediate value for community partners, including around prevention, testing, treatment, and vaccination. Our identification of the aforementioned racial disparity helped our community nearly eliminate disparities during the second wave. Elsevier Ltd. 2022-11 2022-08-27 /pmc/articles/PMC9420028/ /pubmed/36460446 http://dx.doi.org/10.1016/j.sste.2022.100536 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Sadler, Richard Casey Wojciechowski, Thomas W. Buchalski, Zachary Harris, Alan Lederer, Danielle Peters, Matt Hackert, Pamela Furr-Holden, C. Debra Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title | Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title_full | Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title_fullStr | Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title_full_unstemmed | Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title_short | Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan |
title_sort | using trajectory modeling of spatio-temporal trends to illustrate disparities in covid-19 death in flint and genesee county, michigan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420028/ https://www.ncbi.nlm.nih.gov/pubmed/36460446 http://dx.doi.org/10.1016/j.sste.2022.100536 |
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