Abstract
COVID-19 has arrived in the USA and spread quickly, causing deaths. The factors affecting the fast spread of COVID-19 and associated deaths are not clearly understood. In this research, we tried to identify the most significant environmental, economic, and demographic features impacting COVID-19 cases and associated mortality in the USA using statistical methods, including linear regression. We have chosen a wide range of feature parameters such as; average daily high temperature, hours of sunshine, population density, average relative humidity, median household income, persons 65 years and over, and percentage of African American, Hispanic and White population. We examined the correlation between the selected features and COVID-19 cases and associated deaths in 50 US counties. The counties are selected from each US state where the most populated city is located. We applied multiple linear regression and backward elimination method to decide which variables have the most impact on Corona related cases and deaths. Using these features, we tried to estimate COVID-19 cases and related deaths in the USA. We repeated the procedure for the state-wise comparison and chosen the parameters for the 50 US states and examined the correlation for the same attributes.
Published Version
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