Incorporating testing volume into estimation of effective reproduction number dynamics

08/08/2022

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by   Isaac H. Goldstein, et al.

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Branching process inspired models are widely used to estimate the effective reproduction number – a useful summary statistic describing an infectious disease outbreak – using counts of new cases. Case data is a real-time indicator of changes in the reproduction number, but is challenging to work with because cases fluctuate due to factors unrelated to the number of new infections. We develop a new model that incorporates the number of diagnostic tests as a surveillance model covariate. Using simulated data and data from the SARS-CoV-2 pandemic in California, we demonstrate that incorporating tests leads to improved performance over the state-of-the-art.