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The coronavirus pandemic has rapidly evolved into an unprecedented crisis.The susceptible-infectious-removed (SIR) model and its variants have been usedfor modeling the pandemic. However, time-independent parameters in theclassical models may not capture the dynamic transmission and removalprocesses, governed by virus containment strategies taken at various phases ofthe epidemic. Moreover, very few models account for possible inaccuracies ofthe reported cases. We propose a Poisson model with time-dependent transmissionand removal rates to account for possible random errors in reporting andestimate a time-dependent disease reproduction number, which may be used toassess the effectiveness of virus control strategies. We apply our method tostudy the pandemic in several severely impacted countries, and analyze andforecast the evolving spread of the coronavirus. We have developed aninteractive web application to facilitate readers' use of our method.

Estimation of time-varying reproduction numbers underlying epidemiological processes: a new statistical tool for the COVID-19 pandemic