Constructing a segregation index
We leveraged a spatial and localizable segregation measure based on census tract data for each ethnoracial group, assigned to the mean population-weighted centroids of each tract (27, 28). Each county was projected to the appropriate state-plane projection system, and then we conducted a Gaussian kernel density smoothing procedure for the total population using the spatstat package in R (29). We used the same bandwidth to calculate the smooth for each subgroup. Each kernel-smoothed ethnoracial subgroup value was divided by the corresponding value for the total population to create a concentration measure per tract. Each value was multiplied by 100 to create a percent value. This approach relies on multiple tracts per county, which was not true for all counties, specifically in Virginia and West Virginia. When we encountered such errors, we merged the county with its nearest neighbor based on centroid distances.