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Short-term forecasting of COVID-19 in Germany and Poland during the second wave - a preregistered study
Johannes Bracher; Daniel Wolffram; Jannik Deuschel; Konstantin Goergen; Jakob L. Ketterer; Alexander Ullrich; Sam Abbott; Maria Vittoria Barbarossa; Dimitris Bertsimas; Sangeeta Bhatia; Marcin Bodych; Nikos I. Bosse; Jan Pablo Burgard; Lauren Castro; Geoffrey Fairchild; Jan Fuhrmann; Sebastian Funk; Krzysztof Gogolewski; Quanquan Gu; Stefan Heyder; Thomas Hotz; Yuri Kheifetz; Holger Kirsten; Tyll Krueger; Ekaterina Krymova; Michael Lingzhi Li; Jan H. Meinke; Isaac J. Michaud; Karol Niedzielewski; Tomasz Ozanski; Franciszek Rakowski; Markus Scholz; Saksham Soni; Ajitesh Srivastava; Jakub Zielinski; Difan Zou; Tilmann Gneiting; Melanie Schienle.
Afiliação
  • Johannes Bracher; Karlsruhe Institute of Technology and Heidelberg Institute for Theoretical Studies
  • Daniel Wolffram; Heidelberg Institute for Theoretical Studies and Karlsruhe Institute of Technology
  • Jannik Deuschel; Karlsruhe Institute of Technology
  • Konstantin Goergen; Karlsruhe Institute of Technology
  • Jakob L. Ketterer; Karlsruhe Institute of Technology
  • Alexander Ullrich; Robert Koch Institute, Berlin
  • Sam Abbott; London School of Hygiene and Tropical Medicine
  • Maria Vittoria Barbarossa; Frankfurt Institute of Advanced Studies
  • Dimitris Bertsimas; MIT Sloan School of Management
  • Sangeeta Bhatia; Imperial College, London
  • Marcin Bodych; Wroclaw University of Science and Technology
  • Nikos I. Bosse; London School of Hygiene and Tropical Medicine
  • Jan Pablo Burgard; Trier University
  • Lauren Castro; Information Systems and Modeling, Los Alamos National Laboratory
  • Geoffrey Fairchild; Information Systems and Modeling, Los Alamos National Laboratory
  • Jan Fuhrmann; Frankfurt Institute for Advanced Studies and Juelich Supercomputing Centre, Forschungszentrum Juelich
  • Sebastian Funk; London School of Hygiene and Tropical Medicine
  • Krzysztof Gogolewski; Institute of Informatics, University of Warsaw
  • Quanquan Gu; University of California Los Angeles
  • Stefan Heyder; TU Ilmenau
  • Thomas Hotz; TU Ilmenau
  • Yuri Kheifetz; University of Leipzig
  • Holger Kirsten; University of Leipzig
  • Tyll Krueger; Wroclaw University of Science and Technology
  • Ekaterina Krymova; Swiss Data Science Center, ETH Zurich and EPFL, Lausanne
  • Michael Lingzhi Li; Operations Research Center, Massachusetts Institute of Technology
  • Jan H. Meinke; Juelich Supercomputing Centre, Forschungszentrum Juelich
  • Isaac J. Michaud; Statistical Sciences Group, Los Alamos National Laboratory
  • Karol Niedzielewski; University of Warsaw
  • Tomasz Ozanski; Wroclaw University of Science and Technology
  • Franciszek Rakowski; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw
  • Markus Scholz; University of Leipzig
  • Saksham Soni; Sloan School of Management, Massachusetts Institute of Technology
  • Ajitesh Srivastava; University of Southern California, Los Angeles
  • Jakub Zielinski; University of Warsaw
  • Difan Zou; University of California, Los Angeles
  • Tilmann Gneiting; Heidelberg Institue for Thoretical Studies and Karlsruhe Institute of Technology
  • Melanie Schienle; Karlsruhe Institute of Technology
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20248826
ABSTRACT
We report insights from ten weeks of collaborative COVID-19 forecasting for Germany and Poland (12 October - 19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.
Licença
cc_by_nc
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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