Using trajectory modeling of spatio-temporal trends to illustrate disparities in COVID-19 death in flint and Genesee County, Michigan

Richard Casey Sadler, Thomas W. Wojciechowski, Zachary Buchalski, Alan Harris, Danielle Lederer, Matt Peters, Pamela Hackert, C. Debra Furr-Holden

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number100536
JournalSpatial and Spatio-temporal Epidemiology
Volume43
DOIs
StatePublished - Nov 2022

Keywords

  • COVID-19
  • Epidemiological methods
  • Group-based trajectory modeling
  • Health inequalities
  • Racial disparities
  • Spatial analysis

ASJC Scopus subject areas

  • Epidemiology
  • Geography, Planning and Development
  • Infectious Diseases
  • Health, Toxicology and Mutagenesis

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