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Comparing human and model-based forecasts of COVID-19 in Germany and Poland

Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Bosse, Nikos I.; Abbott, Sam; Bracher, Johannes 1; Hain, Habakuk; Quilty, Billy J.; Jit, Mark; van Leeuwen, Edwin; Cori, Anne; Funk, Sebastian; McCaw, James M. [Hrsg.]
1 Institut für Volkswirtschaftslehre (ECON), Karlsruher Institut für Technologie (KIT)

Abstract:

Forecasts based on epidemiological modelling have played an important role in shaping public policy throughout the COVID-19 pandemic. This modelling combines knowledge about infectious disease dynamics with the subjective opinion of the researcher who develops and refines the model and often also adjusts model outputs. Developing a forecast model is difficult, resource- and time-consuming. It is therefore worth asking what modelling is able to add beyond the subjective opinion of the researcher alone. To investigate this, we analysed different real-time forecasts of cases of and deaths from COVID-19 in Germany and Poland over a 1-4 week horizon submitted to the German and Polish Forecast Hub. We compared crowd forecasts elicited from researchers and volunteers, against a) forecasts from two semi-mechanistic models based on common epidemiological assumptions and b) the ensemble of all other models submitted to the Forecast Hub. We found crowd forecasts, despite being overconfident, to outperform all other methods across all forecast horizons when forecasting cases (weighted interval score relative to the Hub ensemble 2 weeks ahead: 0.89). ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000151791
Veröffentlicht am 28.10.2022
Originalveröffentlichung
DOI: 10.1371/journal.pcbi.1010405
Scopus
Zitationen: 11
Web of Science
Zitationen: 8
Dimensions
Zitationen: 20
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Volkswirtschaftslehre (ECON)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 1553-7358, 1553-734X
KITopen-ID: 1000151791
Erschienen in PLOS Computational Biology
Verlag Public Library of Science (PLoS)
Band 18
Heft 9
Seiten Art.Nr. e1010405
Vorab online veröffentlicht am 19.09.2022
Nachgewiesen in Dimensions
Web of Science
Scopus
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