Estimating and simulating a SIRD model of COVID-19 for many countries, states, and cities

Estimating and simulating a SIRD model of COVID-19 for many countries, states, and cities

Collection:
Health Policy and Services Research
Series Title(s):
Working paper (Stanford Institute for Economic Policy Research)
Author(s):
Fernández-Villaverde, Jesús, author
Jones, Charles I. (Charles Irving), author
Contributor(s):
Stanford Institute for Economic Policy Research, issuing body.
Publication:
Stanford, CA : Stanford Institute for Economic Policy Research (SIEPR), June 2020
Language(s):
English
Format:
Text
Subject(s):
COVID-19 -- mortality
Models, Theoretical
COVID-19 -- transmission
Physical Distancing
Immunity, Herd
Abstract:
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.
Copyright:
Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY-NC-ND license. (More information)
Extent:
1 online resource (1 PDF file (58 pages))
Illustrations:
Illustrations
NLM Unique ID:
101776180 (See catalog record)
OCLC no.:
1157318263
Permanent Link:
http://resource.nlm.nih.gov/101776180