(Georgia Institute of Technology, 2020)
Nair, Shruthy
COVID-19 is a highly infective virus with a rapid transmission rate. It has led to a pandemic that has impacted millions of people all around the world. In the United States alone, over 3 million people have being directly affected by COVID-19 as they tested positive and millions more have been affected indirectly due to the virus. The purpose of this study is to determine if a COVID-19 Vulnerability Index can be created using GIS, that would enable one to identify high risk counties within the United States. A Vulnerability Index measures how vulnerable a population or region is to a particular illness. Multiple socio-economic, demographic, transportation and health related factors were utilized in the development of the Vulnerability Index. Principal Component Analysis were applied to analyze the distribution and correlation in the factors and create the index values. The COVID-19 case rates, death rates and the COVID-19 Vulnerability Index values were compared using spatial clustering and then their actual results were compared to see if the Vulnerability Index is a good measure for COVID-19 case rates and death rates. Results indicated that the COVID-19 Vulnerability Index is a good measure to identify counties that are at risk of increasing their case rate, but not death rates. Furthermore, ordinary least squares regression and spatial lag model were run to evaluate the effectivity of the COVID-19 Vulnerability Index in identifying counties with increasing risk of COVID-19 cases. The regression models indicated that the Vulnerability Index is a relatively good measure determining high risk counties.