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