Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities


This seminar will take place on Zoom

We use data on deaths in New York City, various U.S. states, and various countries around the world to estimate a standard epidemiological model of COVID-19. We allow for a time-varying contact rate in order to capture behavioral and policy-induced changes associated with social distancing. We simulate the model forward to consider possible futures for various countries, states, and cities, including the potential impact of herd immunity on re-opening. Our current baseline mortality rate (IFR) is assumed to be 0.8% but we recognize there is substantial uncertainty about this number. Our model fits the death data equally well with alternative mortality rates of 0.3% or 1.0%, so this parameter is unidentified in our data. However, its value matters enormously for the extent to which various places can relax social distancing without spurring a resurgence of deaths.

Link to paper: www.sas.upenn.edu/~jesusfv/sird.pdf