Short-term forecasting of COVID-19 in Germany and Poland during the second wave – a preregistered study
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..
Medienart: |
Preprint |
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Erscheinungsjahr: |
2021 |
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Erschienen: |
2021 |
Enthalten in: |
bioRxiv.org - (2021) vom: 15. Dez. Zur Gesamtaufnahme - year:2021 |
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Sprache: |
Englisch |
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Beteiligte Personen: |
Bracher, J. [VerfasserIn] |
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Links: |
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doi: |
10.1101/2020.12.24.20248826 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
XBI019592329 |
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520 | |a 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. | ||
700 | 1 | |a Wolffram, D. |e verfasserin |4 aut | |
700 | 1 | |a Deuschel, J. |e verfasserin |4 aut | |
700 | 1 | |a Görgen, K. |e verfasserin |4 aut | |
700 | 1 | |a Ketterer, J.L. |e verfasserin |4 aut | |
700 | 1 | |a Ullrich, A. |e verfasserin |4 aut | |
700 | 1 | |a Abbott, S. |e verfasserin |4 aut | |
700 | 1 | |a Barbarossa, M.V. |e verfasserin |4 aut | |
700 | 1 | |a Bertsimas, D. |e verfasserin |4 aut | |
700 | 1 | |a Bhatia, S. |e verfasserin |4 aut | |
700 | 1 | |a Bodych, M. |e verfasserin |4 aut | |
700 | 1 | |a Bosse, N.I. |e verfasserin |4 aut | |
700 | 1 | |a Burgard, J.P. |e verfasserin |4 aut | |
700 | 1 | |a Castro, L. |e verfasserin |4 aut | |
700 | 1 | |a Fairchild, G. |e verfasserin |4 aut | |
700 | 1 | |a Fuhrmann, J. |e verfasserin |4 aut | |
700 | 1 | |a Funk, S. |e verfasserin |4 aut | |
700 | 1 | |a Gogolewski, K. |e verfasserin |4 aut | |
700 | 1 | |a Gu, Q. |e verfasserin |4 aut | |
700 | 1 | |a Heyder, S. |e verfasserin |4 aut | |
700 | 1 | |a Hotz, T. |e verfasserin |4 aut | |
700 | 1 | |a Kheifetz, Y. |e verfasserin |4 aut | |
700 | 1 | |a Kirsten, H. |e verfasserin |4 aut | |
700 | 1 | |a Krueger, T. |e verfasserin |4 aut | |
700 | 1 | |a Krymova, E. |e verfasserin |4 aut | |
700 | 1 | |a Li, M.L. |e verfasserin |4 aut | |
700 | 1 | |a Meinke, J.H. |e verfasserin |4 aut | |
700 | 1 | |a Michaud, I.J. |e verfasserin |4 aut | |
700 | 1 | |a Niedzielewski, K. |e verfasserin |4 aut | |
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700 | 1 | |a Schienle, M. |e verfasserin |4 aut | |
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