Predictive performance of international COVID-19 mortality forecasting models

Forecasts of COVID-19 mortality have been critical inputs into a range of policies, and decision-makers need information about their predictive performance. Here, the authors gather a panel of global epidemiological models and assess their predictive performance across time and space.

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Autores principales:	Joseph Friedman, Patrick Liu, Christopher E. Troeger, Austin Carter, Robert C. Reiner, Ryan M. Barber, James Collins, Stephen S. Lim, David M. Pigott, Theo Vos, Simon I. Hay, Christopher J. L. Murray, Emmanuela Gakidou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/52bc9ab11980476da45be7562b888e3f
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spelling	oai:doaj.org-article:52bc9ab11980476da45be7562b888e3f2021-12-02T14:35:39ZPredictive performance of international COVID-19 mortality forecasting models10.1038/s41467-021-22457-w2041-1723https://doaj.org/article/52bc9ab11980476da45be7562b888e3f2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22457-whttps://doaj.org/toc/2041-1723Forecasts of COVID-19 mortality have been critical inputs into a range of policies, and decision-makers need information about their predictive performance. Here, the authors gather a panel of global epidemiological models and assess their predictive performance across time and space.Joseph FriedmanPatrick LiuChristopher E. TroegerAustin CarterRobert C. ReinerRyan M. BarberJames CollinsStephen S. LimDavid M. PigottTheo VosSimon I. HayChristopher J. L. MurrayEmmanuela GakidouNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Joseph Friedman Patrick Liu Christopher E. Troeger Austin Carter Robert C. Reiner Ryan M. Barber James Collins Stephen S. Lim David M. Pigott Theo Vos Simon I. Hay Christopher J. L. Murray Emmanuela Gakidou Predictive performance of international COVID-19 mortality forecasting models
description	Forecasts of COVID-19 mortality have been critical inputs into a range of policies, and decision-makers need information about their predictive performance. Here, the authors gather a panel of global epidemiological models and assess their predictive performance across time and space.
format	article
author	Joseph Friedman Patrick Liu Christopher E. Troeger Austin Carter Robert C. Reiner Ryan M. Barber James Collins Stephen S. Lim David M. Pigott Theo Vos Simon I. Hay Christopher J. L. Murray Emmanuela Gakidou
author_facet	Joseph Friedman Patrick Liu Christopher E. Troeger Austin Carter Robert C. Reiner Ryan M. Barber James Collins Stephen S. Lim David M. Pigott Theo Vos Simon I. Hay Christopher J. L. Murray Emmanuela Gakidou
author_sort	Joseph Friedman
title	Predictive performance of international COVID-19 mortality forecasting models
title_short	Predictive performance of international COVID-19 mortality forecasting models
title_full	Predictive performance of international COVID-19 mortality forecasting models
title_fullStr	Predictive performance of international COVID-19 mortality forecasting models
title_full_unstemmed	Predictive performance of international COVID-19 mortality forecasting models
title_sort	predictive performance of international covid-19 mortality forecasting models
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/52bc9ab11980476da45be7562b888e3f
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Predictive performance of international COVID-19 mortality forecasting models

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