  This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in
two contrasting US states during 2020-2021. A variety of models are evaluated
at the county level for goodness-of-fit and an assessment of confounding
predictors is also made. It is found that models with three deprivation
predictors and neighborhood effects are important. In addition the work index
from Google mobility was also found to provide increased explanation of the
transmission dynamic.
