Authors: Ulisses Jacobo*, St. Cloud State University
Topics: Medical and Health Geography, Geographic Information Science and Systems
Keywords: Medical Geography, Minnesota Covid-19, Statistical Analyses
Session Type: Virtual Poster
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 52
Presentation File: Download
This project examines Covid-19 morbidity and mortality rates relative to social demographic data within zip codes and counties in Minnesota between March 1, 2020 and December 14, 2020. Drawing on work in medical geography and social geography and utilizing Geographic Information Systems (GIS) to visualize Covid-19 morbidity and mortality, I apply the Getis-Ord Gi* statistic method to identify statistical hot spots and cold spots and compare them against various social demographic data. In doing so, I aim to reveal the extent to which the spread and severity of the impact of Covid-19 may be a function of social factors.