Estimating and simulating a SIRD model of COVID-19 for many countries, states, and cities Working paper (Stanford Institute for Economic Policy Research) Fernández-Villaverde, Jesús, author. Jones, Charles I. (Charles Irving), author. COVID-19 -- mortality Models, Theoretical COVID-19 -- transmission Physical Distancing Immunity, Herd We use data on deaths in New York City, Madrid, Stockholm, and other world cities as well as in various U.S. states and various countries and regions 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 1.0% but we recognize there is substantial uncertainty about this number. Our model fits the death data equally well with alternative mortality rates of 0.5% or 1.2%, 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. Stanford, CA : Stanford Institute for Economic Policy Research (SIEPR), June 2020 Stanford Institute for Economic Policy Research, issuing body. Text Illustrations 1 online resource (1 PDF file (58 pages)) nlm:nlmuid-101776180-pdf 101776180 http://resource.nlm.nih.gov/101776180 OCLC: 1157318263 English Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY-NC-ND license. https://creativecommons.org/licenses/by-nc-nd/3.0