Masking Mandate Policies and Community-Level Factors Associated with COVID-19 Cases Spread in the State of Texas.

This exploratory study investigates the intersection of county demographics, healthcare disparities, and COVID-19 policies with COVID-19 outcomes in Texas. Using hierarchical clustering, random forest, and multinomial logistic regression algorithms, the study analyzes COVID-19 case data from March 4, 2020, to December 15, 2020, across 254 Texas counties. The findings reveal six distinct clusters, with key differentiating factors including the number of days under mask mandate, number of churches, population density, water area, and proportion of African American population. Longer mask mandates are associated with higher case rates, suggesting remedial rather than preventive implementation. Higher population density and more churches per person correlate with steeper case increases. Access to bodies of water and the proportion of the African American population were also associated with case trends. These insights helped us formulate hypotheses that can inform tailored public health interventions to address regional characteristics within Texas.