ArticleCommunications medicine2022
National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.
Article in Communications medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Estimating the COVID-19 prevalence from wastewater.Scientific reports · 2024Article
- Challenges of COVID-19 Case Forecasting in the US, 2020-2021.PLoS computational biology · 2024Article
- Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England.Royal Society open science · 2024Article
- Evaluation of predictive capability of Bayesian spatio-temporal models for Covid-19 spread.BMC medical research methodology · 2023Article
- Scoring epidemiological forecasts on transformed scales.PLoS computational biology · 2023Article
- Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations.eLife · 2023Article
- Human judgement forecasting of COVID-19 in the UK.Wellcome open research · 2023Article
- National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.Communications medicine · 2022Article
- Comparing human and model-based forecasts of COVID-19 in Germany and Poland.PLoS computational biology · 2022Article
- Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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Authors and funding
42 authors.
Funding
Abstract
backgroundDuring 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.
methodsWe 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.
resultsWe 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.
conclusionsMulti-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.
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