Dynamics of COVID-19 Exposure: Exploring age nonstationarity among older adults

Keywords: COVID-19, Age Nonstationarity, Health Disparity, Older Adults, Big Data
Abstract Type: Paper Abstract

Abstract

This study examines the differences in COVID-19 exposures among older adults (60-79) and older adults (80 and over), and explores the driving factors producing such outcomes. Over 13 million COVID-19 adult patients 60 years or older were assessed. This paper uses one-way ANOVA and Anselin’s Local Moran’s I to explore the disparities, and utilizes principal component analyses to generate fourteen factors of health determinants. The relationships between incidence rates of the two age groups and determinants of health used Pearson correlation in addition to OLS regressions and spatial lag/error models. Both groups had similar incidence rates, but older adults (80 and over) had much higher hospitalization rates, death rates, and case-fatality rates in 2020-2022. Geographically, the high cluster of incidence rates for both groups shifted from the Midwest at the beginning of the pandemic to the Southwest in 2022. The relationships between determinants of health components and incidence rates varied across age groups and years. More public health attention needs to be paid to older adults (80 and over) since they experience more severe COVID-19 impacts than adults age 60-79. COVID-19 policies and mitigations should further their efforts considering race, healthcare access, social capital, environment, household composition, and mobility.