A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave
Forecasting models have been used extensively to inform decision making during the COVID-19 pandemic. In this preregistered and prospective study, the authors evaluated 14 short-term models for Germany and Poland, finding considerable heterogeneity in predictions and highlighting the benefits of com...
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doaj-24a309c146094b3e8b03c37e224aa56b2021-08-29T11:37:13ZengNature Publishing GroupNature Communications2041-17232021-08-0112111610.1038/s41467-021-25207-0A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second waveJ. Bracher0D. Wolffram1J. Deuschel2K. Görgen3J. L. Ketterer4A. Ullrich5S. Abbott6M. V. Barbarossa7D. Bertsimas8S. Bhatia9M. Bodych10N. I. Bosse11J. P. Burgard12L. Castro13G. Fairchild14J. Fuhrmann15S. Funk16K. Gogolewski17Q. Gu18S. Heyder19T. Hotz20Y. Kheifetz21H. Kirsten22T. Krueger23E. Krymova24M. L. Li25J. H. Meinke26I. J. Michaud27K. Niedzielewski28T. Ożański29F. Rakowski30M. Scholz31S. Soni32A. Srivastava33J. Zieliński34D. Zou35T. Gneiting36M. Schienle37List of Contributors by TeamChair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Robert Koch Institute (RKI)London School of Hygiene and Tropical MedicineFrankfurt Institute for Advanced StudiesSloan School of Management, Massachusetts Institute of TechnologyMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College LondonWroclaw University of Science and TechnologyLondon School of Hygiene and Tropical MedicineEconomic and Social Statistics Department, University of TrierInformation Systems and Modeling, Los Alamos National LaboratoryInformation Systems and Modeling, Los Alamos National LaboratoryFrankfurt Institute for Advanced StudiesLondon School of Hygiene and Tropical MedicineInstitute of Informatics, University of WarsawDepartment of Computer Science, University of CaliforniaInstitute of Mathematics, Technische Universität IlmenauInstitute of Mathematics, Technische Universität IlmenauInstitute for Medical Informatics, Statistics and Epidemiology, University of LeipzigInstitute for Medical Informatics, Statistics and Epidemiology, University of LeipzigWroclaw University of Science and TechnologySwiss Data Science Center, ETH Zurich and EPFLOperations Research Center, Massachusetts Institute of TechnologyJülich Supercomputing Centre, Forschungszentrum JülichStatistical Sciences Group, Los Alamos National LaboratoryInterdisciplinary Centre for Mathematical and Computational Modeling, University of WarsawWroclaw University of Science and TechnologyInterdisciplinary Centre for Mathematical and Computational Modeling, University of WarsawInstitute for Medical Informatics, Statistics and Epidemiology, University of LeipzigSloan School of Management, Massachusetts Institute of TechnologyMing Hsieh Department of Computer and Electrical Engineering, University of Southern CaliforniaInterdisciplinary Centre for Mathematical and Computational Modeling, University of WarsawDepartment of Computer Science, University of CaliforniaComputational Statistics Group, Heidelberg Institute for Theoretical Studies (HITS)Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT)Forecasting models have been used extensively to inform decision making during the COVID-19 pandemic. In this preregistered and prospective study, the authors evaluated 14 short-term models for Germany and Poland, finding considerable heterogeneity in predictions and highlighting the benefits of combined forecasts.https://doi.org/10.1038/s41467-021-25207-0 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. Bracher D. Wolffram J. Deuschel K. Görgen J. L. Ketterer A. Ullrich S. Abbott M. V. Barbarossa D. Bertsimas S. Bhatia M. Bodych N. I. Bosse J. P. Burgard L. Castro G. Fairchild J. Fuhrmann S. Funk K. Gogolewski Q. Gu S. Heyder T. Hotz Y. Kheifetz H. Kirsten T. Krueger E. Krymova M. L. Li J. H. Meinke I. J. Michaud K. Niedzielewski T. Ożański F. Rakowski M. Scholz S. Soni A. Srivastava J. Zieliński D. Zou T. Gneiting M. Schienle List of Contributors by Team |
spellingShingle |
J. Bracher D. Wolffram J. Deuschel K. Görgen J. L. Ketterer A. Ullrich S. Abbott M. V. Barbarossa D. Bertsimas S. Bhatia M. Bodych N. I. Bosse J. P. Burgard L. Castro G. Fairchild J. Fuhrmann S. Funk K. Gogolewski Q. Gu S. Heyder T. Hotz Y. Kheifetz H. Kirsten T. Krueger E. Krymova M. L. Li J. H. Meinke I. J. Michaud K. Niedzielewski T. Ożański F. Rakowski M. Scholz S. Soni A. Srivastava J. Zieliński D. Zou T. Gneiting M. Schienle List of Contributors by Team A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave Nature Communications |
author_facet |
J. Bracher D. Wolffram J. Deuschel K. Görgen J. L. Ketterer A. Ullrich S. Abbott M. V. Barbarossa D. Bertsimas S. Bhatia M. Bodych N. I. Bosse J. P. Burgard L. Castro G. Fairchild J. Fuhrmann S. Funk K. Gogolewski Q. Gu S. Heyder T. Hotz Y. Kheifetz H. Kirsten T. Krueger E. Krymova M. L. Li J. H. Meinke I. J. Michaud K. Niedzielewski T. Ożański F. Rakowski M. Scholz S. Soni A. Srivastava J. Zieliński D. Zou T. Gneiting M. Schienle List of Contributors by Team |
author_sort |
J. Bracher |
title |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave |
title_short |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave |
title_full |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave |
title_fullStr |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave |
title_full_unstemmed |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave |
title_sort |
pre-registered short-term forecasting study of covid-19 in germany and poland during the second wave |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2021-08-01 |
description |
Forecasting models have been used extensively to inform decision making during the COVID-19 pandemic. In this preregistered and prospective study, the authors evaluated 14 short-term models for Germany and Poland, finding considerable heterogeneity in predictions and highlighting the benefits of combined forecasts. |
url |
https://doi.org/10.1038/s41467-021-25207-0 |
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