COVID-19 is a viral disease that began impacting the world in the latter part of 2019. In early 2020, the world would be in a state of pandemic due to the rapid spread of the disease. Statistical analysis has been an extremely useful tool in determining the impact of COVID-19. Some discussion about the COVID-19 pandemic is how medical and non-medical factors can influence i the severity of the infection of a person. A case study was conducted regarding cases that occurred in Wake County, North Carolina. The relationship between demographic factors (age, sex, and race) and both ICU admittance and death were investigated using the chi-square test of association and binary logistic regression. Age and race were determined to have some significant relationship with severe cases of COVID-19 while sex did not. Binary logistic regression also produced model equations that can be utilized to predict the likelihood of ICU admittance or death of an individual as the result of COVID-19 based on these factors.

Logistic regression