  In this short technical report we model, within the Bayesian framework, the
rate of positive tests reported by the the State of Indiana, accounting also
for the substantial variability (and overdispeartion) in the daily count of the
tests performed. The approach we take, results with a simple procedure for
prediction, a posteriori, of this rate of 'positivity' and allows for an easy
and a straightforward adaptation by any agency tracking daily results of
COVID-19 tests. The numerical results provided herein were obtained via an
updatable R Markdown document.
