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Spatio-Temporal Bayesian Modeling of Deaths of Despair in Ohio from 2015-2020
Topics: Health and Medical
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Keywords: Deaths of Despair, Health, Epidemiology, Bayesian Session Type: Virtual Paper Abstract Day: Friday Session Start / End Time: 2/25/2022 11:20 AM (Eastern Time (US & Canada)) - 2/25/2022 12:40 PM (Eastern Time (US & Canada)) Room: Virtual 36
Authors:
Megan Lindstrom, The Ohio State University Department of Geography
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Abstract
Deaths of Despair are commonly described as a legacy of deindustrialization with non-Hispanic white population members experiencing the greatest impacts. However, our research indicates a shift has occurred in Deaths of Despair, particularly during COVID-19, that has resulted in other vulnerable populations bearing the highest risk. Using Bayesian spatio-temporal modeling we explore how the landscape of Deaths of Despair has shifted from 2015-2020, highlighting geographic drivers and social determinants of health. Our findings suggest reallocation of physical and social resources may be necessary as Deaths of Despair affect new populations.
Spatio-Temporal Bayesian Modeling of Deaths of Despair in Ohio from 2015-2020
