Identifying Significant Predictors of COVID-19 Mortality Rate in the United States

Abstract

Identifying useful predictors of COVID-19 mortality rate is of critical importance to fight the ongoing pandemic. Based on the Lasso regression and linear discriminant analysis (LDA), hospitalization rate and incident rate seem to be more significant as predictors of COVID-19 mortality rate than latitude, longitude, and testing rate. We further discuss possible causes and implications of the results above by analyzing associations between testing rate, incident rate, and mortality rate