{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Madlock-Brown C"],"funding":["National Center for Advancing Translational Sciences","NCATS NIH HHS","National Institute of Diabetes and Digestive and Kidney Diseases","NIDDK NIH HHS","U.S. National Library of Medicine","NLM NIH HHS"],"pagination":["747"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9008430"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["22(1)"],"pubmed_abstract":["<h4>Background</h4>There is a need to evaluate how the choice of time interval contributes to the lack of consistency of SDoH variables that appear as important to COVID-19 disease burden within an analysis for both case counts and death counts.<h4>Methods</h4>This study identified SDoH variables associated with U.S county-level COVID-19 cumulative case and death incidence for six different periods: the first 30, 60, 90, 120, 150, and 180 days since each county had COVID-19 one case per 10,000 residents. The set of SDoH variables were in the following domains: resource deprivation, access to care/health resources, population characteristics, traveling behavior, vulnerable populations, and health status. A generalized variance inflation factor (GVIF) analysis was used to identify variables "],"journal":["BMC public health"],"pubmed_title":["Clinical, social, and policy factors in COVID-19 cases and deaths: methodological considerations for feature selection and modeling in county-level analyses."],"pmcid":["PMC9008430"],"funding_grant_id":["5T32DK110966-04","T32 DK110966","UL1 TR001430","UL1 TR001855","U24TR002306","U24 TR002306","1UL1TR001430-01","1R21LM013645-01","R21 LM013645"],"pubmed_authors":["Weiskopf N","Bhattacharyya S","Goetz K","Phuong J","Lemon C","Wilkens K","Dorr D","Kharrazi H","Madlock-Brown C","Sule A","Adams WG","Cesare N","Riches NO","Espinoza J","Liu F"],"additional_accession":[]},"is_claimable":false,"name":"Clinical, social, and policy factors in COVID-19 cases and deaths: methodological considerations for feature selection and modeling in county-level analyses.","description":"<h4>Background</h4>There is a need to evaluate how the choice of time interval contributes to the lack of consistency of SDoH variables that appear as important to COVID-19 disease burden within an analysis for both case counts and death counts.<h4>Methods</h4>This study identified SDoH variables associated with U.S county-level COVID-19 cumulative case and death incidence for six different periods: the first 30, 60, 90, 120, 150, and 180 days since each county had COVID-19 one case per 10,000 residents. The set of SDoH variables were in the following domains: resource deprivation, access to care/health resources, population characteristics, traveling behavior, vulnerable populations, and health status. A generalized variance inflation factor (GVIF) analysis was used to identify variables ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Apr","modification":"2025-04-26T21:01:27.899Z","creation":"2024-10-19T13:34:52.97Z"},"accession":"S-EPMC9008430","cross_references":{"pubmed":["35421958"],"doi":["10.1186/s12889-022-13168-y"]}}