TY - JOUR
T1 - Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan
AU - Sadler, Richard Casey
AU - Wojciechowski, Thomas W.
AU - Buchalski, Zachary
AU - Harris, Alan
AU - Lederer, Danielle
AU - Peters, Matt
AU - Hackert, Pamela
AU - Furr-Holden, C. Debra
N1 - Funding Information:
The authors were supported by a grant from the Community Foundation of Greater Flint's COVID Urgent Relief Fund.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/11
Y1 - 2022/11
N2 - 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.
AB - 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.
KW - COVID-19
KW - Epidemiological methods
KW - Group-based trajectory modeling
KW - Health inequalities
KW - Racial disparities
KW - Spatial analysis
UR - http://www.scopus.com/inward/record.url?scp=85137596809&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85137596809&partnerID=8YFLogxK
U2 - 10.1016/j.sste.2022.100536
DO - 10.1016/j.sste.2022.100536
M3 - Article
C2 - 36460446
AN - SCOPUS:85137596809
SN - 1877-5845
VL - 43
JO - Spatial and Spatio-temporal Epidemiology
JF - Spatial and Spatio-temporal Epidemiology
M1 - 100536
ER -