author keywords: Severe Acute Respiratory Syndrome Coronavirus 2; SARS-CoV-2; Coronavirus Disease 2019; COVID-19; Disparities; Hospitalization Risks; Predictors; Negative Binomial Models; Geographically Weighted Regression Models; Epidemiology; Missouri

MeSH headings : COVID-19; Hospitalization; Humans; Missouri / epidemiology; Models, Statistical; SARS-CoV-2

TL;DR: Investigation of Zip Code Tabulation Area (ZCTA)-level geographic disparities and identify predictors of COVID-19 hospitalization risks in the St. Louis area found that a ‘one-size-fits-all’ approach may not be appropriate for management and control. (via Semantic Scholar)