This study explored the relationships between COVID-19 incidence with demographic and socioeconomic variables within the United States of America. These variables were collected from publicly available data sets and aggregated at the county level. Data science techniques such as correlation analysis and machine learning via XGBoost were used to determine important topics to explore. First, mental and physical health showed strong correlations with COVID-19 infection and death. Second, research has shown that Area Deprivation Indices (ADI) generally have a positive correlation with COVID-19 incidence. Third, policy measures have been implemented to impact mobility with the objective of mitigating transmission rates. The goal of this paper is to then identify relationships within each of the previously mentioned topics where strong correlations with COVID-19 incidence exist to inform research, practice, and policy development related to the continued efforts to address the pandemic status of this disease.