Before revision:  The main outputs of our model are estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures . All of our outputs have attached Bayesian credible intervals. An important conclusion is that the confirmed case counts greatly underestimate the total number of infected individuals .
After revision:  The main outputs of our model are estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures have been at mitigating or suppressing the virus. Our analysis uses a Bayesian model of COVID-19 fatalities with a likelihood based on an underlying differential equation model of the epidemic. We provide analysis for four states with significant epidemics: California, Florida, New York, and Washington. Our short-term forecasts suggest that these states may be following somewhat different trajectories for growth of the number of cases and fatalities .