National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021
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Published:2022-10-31
Issue:1
Volume:2
Page:
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ISSN:2730-664X
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Container-title:Communications Medicine
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language:en
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Short-container-title:Commun Med
Author:
Bracher JohannesORCID, Wolffram DanielORCID, Deuschel JannikORCID, Görgen KonstantinORCID, Ketterer Jakob L.ORCID, Ullrich AlexanderORCID, Abbott Sam, Barbarossa Maria V.ORCID, Bertsimas Dimitris, Bhatia SangeetaORCID, Bodych MarcinORCID, Bosse Nikos I.ORCID, Burgard Jan PabloORCID, Castro LaurenORCID, Fairchild GeoffreyORCID, Fiedler Jochen, Fuhrmann Jan, Funk SebastianORCID, Gambin AnnaORCID, Gogolewski KrzysztofORCID, Heyder StefanORCID, Hotz Thomas, Kheifetz Yuri, Kirsten Holger, Krueger Tyll, Krymova EkaterinaORCID, Leithäuser NeeleORCID, Li Michael L.ORCID, Meinke Jan H.ORCID, Miasojedow Błażej, Michaud Isaac J.ORCID, Mohring JanORCID, Nouvellet Pierre, Nowosielski Jedrzej M.ORCID, Ozanski Tomasz, Radwan Maciej, Rakowski Franciszek, Scholz Markus, Soni SakshamORCID, Srivastava AjiteshORCID, Gneiting Tilmann, Schienle MelanieORCID
Abstract
Abstract
Background
During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021.
Methods
We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study.
Results
We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict.
Conclusions
Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.
Publisher
Springer Science and Business Media LLC
Reference65 articles.
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