Working Paper: CEPR ID: DP14711
Authors: Jess Fernández-Villaverde; Charles I. Jones
Abstract: 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.
Keywords: SIRD model; COVID-19; estimation
JEL Codes: I10; C52
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| social distancing (I14) | time-varying contact rate (C41) |
| social distancing (I14) | effective reproduction number (R0) (C59) |
| estimated fraction of the population infected (J11) | potential for herd immunity (C92) |
| infection rates (I14) | policy decisions regarding social distancing (J18) |
| mortality rates (I12) | observed death rates (J11) |