Gautham Pavar, Vedaank Tiwari, Namrata Kantamneni*
Our primary objective in this paper was to determine the impact of various factorsaffecting disproportionate COVID mortality rates between counties in the United States.
We primarily relied on the CDC’s demographics data and the CDC’s data on COVID andcomorbidities in US counties. We used these datasets to visualize mortality rates
andco-morbidity rates. Exploratory data analysis was then performed to attempt to find trends. Afterwards, we fit our data to a linear regression model to identify the factors
that contributed most to the model. The most important features of our model was the proportion of the population that was male and the median age. We found that the
median age of the population was a stronger predictor of COVID mortality than presence of comorbidities like diabetes and heart disease. More analysis has yet to be done
on the intersection of various comorbidities and median age.
分享此文章
English 
Spanish 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi 