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Bayesian Modeling of COVID-19 Positivity Rate -- the Indiana experience

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.

preprint2020arXivOpen access
Ben BoukaiJiayue Wang
MethodologyPopulations and Evolution
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Open access2 authors2 topics
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Ben BoukaiJiayue Wang

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