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A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave.
Bracher, J; Wolffram, D; Deuschel, J; Görgen, K; Ketterer, J L; Ullrich, A; Abbott, S; Barbarossa, M V; Bertsimas, D; Bhatia, S; Bodych, M; Bosse, N I; Burgard, J P; Castro, L; Fairchild, G; Fuhrmann, J; Funk, S; Gogolewski, K; Gu, Q; Heyder, S; Hotz, T; Kheifetz, Y; Kirsten, H; Krueger, T; Krymova, E; Li, M L; Meinke, J H; Michaud, I J; Niedzielewski, K; Ozanski, T; Rakowski, F; Scholz, M; Soni, S; Srivastava, A; Zielinski, J; Zou, D; Gneiting, T; Schienle, M.
  • Bracher J; Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany. johannes.bracher@kit.edu.
  • Wolffram D; Computational Statistics Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany. johannes.bracher@kit.edu.
  • Deuschel J; Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
  • Görgen K; Computational Statistics Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany.
  • Ketterer JL; Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
  • Ullrich A; Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
  • Abbott S; Chair of Statistics and Econometrics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
  • Barbarossa MV; Robert Koch Institute (RKI), Berlin, Germany.
  • Bertsimas D; London School of Hygiene and Tropical Medicine, London, UK.
  • Bhatia S; Frankfurt Institute for Advanced Studies, Frankfurt, Germany.
  • Bodych M; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Bosse NI; MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK.
  • Burgard JP; Wroclaw University of Science and Technology, Wroclaw, Poland.
  • Castro L; London School of Hygiene and Tropical Medicine, London, UK.
  • Fairchild G; Economic and Social Statistics Department, University of Trier, Trier, Germany.
  • Fuhrmann J; Information Systems and Modeling, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Funk S; Information Systems and Modeling, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Gogolewski K; Frankfurt Institute for Advanced Studies, Frankfurt, Germany.
  • Gu Q; Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.
  • Heyder S; London School of Hygiene and Tropical Medicine, London, UK.
  • Hotz T; Institute of Informatics, University of Warsaw, Warsaw, Poland.
  • Kheifetz Y; Department of Computer Science, University of California, Los Angeles, CA, USA.
  • Kirsten H; Institute of Mathematics, Technische Universität Ilmenau, Ilmenau, Germany.
  • Krueger T; Institute of Mathematics, Technische Universität Ilmenau, Ilmenau, Germany.
  • Krymova E; Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
  • Li ML; Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
  • Meinke JH; Wroclaw University of Science and Technology, Wroclaw, Poland.
  • Michaud IJ; Swiss Data Science Center, ETH Zurich and EPFL, Lausanne, Switzerland.
  • Niedzielewski K; Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Ozanski T; Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.
  • Rakowski F; Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Scholz M; Interdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Warsaw, Poland.
  • Soni S; Wroclaw University of Science and Technology, Wroclaw, Poland.
  • Srivastava A; Interdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Warsaw, Poland.
  • Zielinski J; Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
  • Zou D; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Gneiting T; Ming Hsieh Department of Computer and Electrical Engineering, University of Southern California, Los Angeles, CA, USA.
  • Schienle M; Interdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Warsaw, Poland.
Nat Commun ; 12(1): 5173, 2021 08 27.
Article in English | MEDLINE | ID: covidwho-1376196
ABSTRACT
Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-25207-0

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-25207-0