COVID-19 Risk Factor Identification based on Ohio Data - Shao, Qin; Thompson, Gerard; Thompson, Amy (Translation: The University of Toledo Journal of Medical Sciences, 2020)
In January COVID-19 was declared to be a global emergency and everyday life was disrupted. Many questions about COVID-19 remain to be answered. This paper provides an examination of the Ohio COVID-19 data set. In particular, logistic regression is applied to the analysis of age and gender characteristics on the mortality of a patient. Based on the statistics and the p-values, gender and age play an important role in the outcome of a patient and the most vulnerable group is comprised of male patients who are more than eighty years old. This paper is an attempt to help in the formulation of public health policy towards confronting COVID-19 and paves the way towards a more comprehensive quantitative analysis as more data become available.