  The COVID-19 disease spreads swiftly, and nearly three months after the first
positive case was confirmed in China, Coronavirus started to spread all over
the United States. Some states and counties reported high number of positive
cases and deaths, while some reported lower COVID-19 related cases and
mortality. In this paper, the factors that could affect the risk of COVID-19
infection and mortality were analyzed in county level. An innovative method by
using K-means clustering and several classification models is utilized to
determine the most critical factors. Results showed that mean temperature,
percent of people below poverty, percent of adults with obesity, air pressure,
population density, wind speed, longitude, and percent of uninsured people were
the most significant attributes
