%0 Journal Article
%@ 2369-2960
%I JMIR Publications
%V 8
%N 7
%P e32164
%T Explaining the Varying Patterns of COVID-19 Deaths Across the United States: 2-Stage Time Series Clustering Framework
%A Megahed,Fadel M
%A Jones-Farmer,L Allison
%A Ma,Yinjiao
%A Rigdon,Steven E
%+ Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, 3545 Lafayette Ave, St Louis, MO, 63104, United States, 1 3149772781, steve.rigdon@slu.edu
%K explanatory modeling
%K multinomial regression
%K SARS-CoV-2
%K COVID-19
%K socioeconomic analyses
%K time series analysis
%D 2022
%7 19.7.2022
%9 Original Paper
%J JMIR Public Health Surveill
%G English
%X Background: Socially vulnerable communities are at increased risk for adverse health outcomes during a pandemic. Although this association has been established for H1N1, Middle East respiratory syndrome (MERS), and COVID-19 outbreaks, understanding the factors influencing the outbreak pattern for different communities remains limited. Objective: Our 3 objectives are to determine how many distinct clusters of time series there are for COVID-19 deaths in 3108 contiguous counties in the United States, how the clusters are geographically distributed, and what factors influence the probability of cluster membership. Methods: We proposed a 2-stage data analytic framework that can account for different levels of temporal aggregation for the pandemic outcomes and community-level predictors. Specifically, we used time-series clustering to identify clusters with similar outcome patterns for the 3108 contiguous US counties. Multinomial logistic regression was used to explain the relationship between community-level predictors and cluster assignment. We analyzed county-level confirmed COVID-19 deaths from Sunday, March 1, 2020, to Saturday, February 27, 2021. Results: Four distinct patterns of deaths were observed across the contiguous US counties. The multinomial regression model correctly classified 1904 (61.25%) of the counties’ outbreak patterns/clusters. Conclusions: Our results provide evidence that county-level patterns of COVID-19 deaths are different and can be explained in part by social and political predictors. 
%M 35476722
%R 10.2196/32164
%U https://publichealth.jmir.org/2022/7/e32164
%U https://doi.org/10.2196/32164
%U http://www.ncbi.nlm.nih.gov/pubmed/35476722