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

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Article in Spatial and spatio-temporal epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 · What the graph read from it

What it found

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3 · Its place in the literature

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1 citing paper in PubMed.

'Nobody Shops at the Neighborhood Store': Leveraging a Community's Pediatric Fresh Produce Prescription Program to Inform Future Participating Store Redemption Locations.Cities & health · 2024
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5 · Who and what money

Authors and funding

8 authors.

Richard Casey SadlerAssociate Professor, Michigan State University, Flint, MI, USA. Electronic address: sadlerr@msu.edu.

Thomas W WojciechowskiAssistant Professor, Michigan State University, East Lansing, MI, USA.

Zachary BuchalskiData Analyst, Michigan State University, Flint, MI, USA.

Alan HarrisGIS Analyst, Michigan State University, Flint, MI, USA.

Danielle LedererChief Epidemiologist, Genesee County Health Department, Flint, MI, USA.

Matt PetersEpidemiologist, Genesee County Health Department, Flint, MI, USA.

Pamela HackertMedical Health Officer, Genesee County Health Department, Flint, MI, USA.

C Debra Furr-HoldenC.S. Mott Endowed Professor of Public Health, Michigan State University, Flint, MI, USA.

Funding

NCCDPHP CDC HHS U48 DP006397

6 · The paper itself

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.

Indexed as

COVID-19HumansMichiganSeasonsCOVID-19Epidemiological methodsGroup-based trajectory modelingHealth inequalitiesRacial disparitiesSpatial analysis

Identifiers

PMID36460446

DOI10.1016/j.sste.2022.100536

PMCPMC9420028

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