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2023-04-21Zeitschriftenartikel
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
dc.contributor.authorSherratt, Katharine
dc.contributor.authorGruson, Hugo
dc.contributor.authorGrah, Rok
dc.contributor.authorJohnson, Helen
dc.contributor.authorNiehus, Rene
dc.contributor.authorPrasse, Bastian
dc.contributor.authorSandmann, Frank
dc.contributor.authorDeuschel, Jannik
dc.contributor.authorWolffram, Daniel
dc.contributor.authorAbbott, Sam
dc.contributor.authorUllrich, Alexander
dc.contributor.authorGibson, Graham
dc.contributor.authorRay, Evan L.
dc.contributor.authorReich, Nicholas G.
dc.contributor.authorSheldon, Daniel
dc.contributor.authorWang, Yijin
dc.contributor.authorWattanachit, Nutcha
dc.contributor.authorWang, Lijing
dc.contributor.authorTrnka, Jan
dc.contributor.authorObozinski, Guillaume
dc.contributor.authorSun, Tao
dc.contributor.authorThanou, Dorina
dc.contributor.authorPottier, Loic
dc.contributor.authorKrymova, Ekaterina
dc.contributor.authorMeinke, Jan H
dc.contributor.authorBarbarossa, Maria Vittoria
dc.contributor.authorLeithauser, Neele
dc.contributor.authorMohring, Jan
dc.contributor.authorSchneider, Johanna
dc.contributor.authorWlazlo, Jaroslaw
dc.contributor.authorFuhrmann, Jan
dc.contributor.authorLange, Berit
dc.contributor.authorRodiah, Isti
dc.contributor.authorBaccam, Prasith
dc.contributor.authorGurung, Heidi
dc.contributor.authorStage, Steven
dc.contributor.authorSuchoski, Bradley
dc.contributor.authorBudzinski, Jozef
dc.contributor.authorWalraven, Robert
dc.contributor.authorVillanueva, Inmaculada
dc.contributor.authorTucek, Vit
dc.contributor.authorSmid, Martin
dc.contributor.authorZajicek, Milan
dc.contributor.authorPerez Alvarez, Cesar
dc.contributor.authorReina, Borja
dc.contributor.authorBosse, Nikos I.
dc.contributor.authorMeakin, Sophie R.
dc.contributor.authorCastro, Lauren
dc.contributor.authorFairchild, Geoffrey
dc.contributor.authorMichaud, Isaac
dc.contributor.authorOsthus, Dave
dc.contributor.authorAlaimo Di Loro, Pierfrancesco
dc.contributor.authorMaruotti, Antonello
dc.contributor.authorEclerova, Veronika
dc.contributor.authorKraus, Andrea
dc.contributor.authorKraus, David
dc.contributor.authorPribylova, Lenka
dc.contributor.authorDimitris, Bertsimas
dc.contributor.authorLingzhi Li, Michael
dc.contributor.authorSaksham, Soni
dc.contributor.authorDehning, Jonas
dc.contributor.authorMohr, Sebastian
dc.contributor.authorPriesemann, Viola
dc.contributor.authorRedlarski, Grzegorz
dc.contributor.authorBejar, Benjamin
dc.contributor.authorArdenghi, Giovanni
dc.contributor.authorParolini, Nicola
dc.contributor.authorZiarelli, Giovanni
dc.contributor.authorBock, Wolfgang
dc.contributor.authorHeyder, Stefan
dc.contributor.authorHotz, Thomas
dc.contributor.authorSingh, David E.
dc.contributor.authorGuzman-Merino, Miguel
dc.contributor.authorAznarte, Jose L.
dc.contributor.authorMorina, David
dc.contributor.authorAlonso, Sergio
dc.contributor.authorAlvarez, Enric
dc.contributor.authorLopez, Daniel
dc.contributor.authorPrats, Clara
dc.contributor.authorBurgard, Jan Pablo
dc.contributor.authorRodloff, Arne
dc.contributor.authorZimmermann, Tom
dc.contributor.authorKuhlmann, Alexander
dc.contributor.authorZibert, Janez
dc.contributor.authorPennoni, Fulvia
dc.contributor.authorDivino, Fabio
dc.contributor.authorCatala, Marti
dc.contributor.authorLovison, Gianfranco
dc.contributor.authorGiudici, Paolo
dc.contributor.authorTarantino, Barbara
dc.contributor.authorBartolucci, Francesco
dc.contributor.authorJona Lasinio, Giovanna
dc.contributor.authorMingione, Marco
dc.contributor.authorFarcomeni, Alessio
dc.contributor.authorSrivastava, Ajitesh
dc.contributor.authorMontero-Manso, Pablo
dc.contributor.authorAdiga, Aniruddha
dc.contributor.authorHurt, Benjamin
dc.contributor.authorLewis, Bryan
dc.contributor.authorMarathe, Madhav
dc.contributor.authorPorebski, Przemyslaw
dc.contributor.authorVenkatramanan, Srinivasan
dc.contributor.authorBartczuk, Rafal P
dc.contributor.authorDreger, Filip
dc.contributor.authorGambin, Anna
dc.contributor.authorGogolewski, Krzysztof
dc.contributor.authorGruziel-Slomka, Magdalena
dc.contributor.authorKrupa, Bartosz
dc.contributor.authorMoszyński, Antoni
dc.contributor.authorNiedzielewski, Karol
dc.contributor.authorNowosielski, Jedrzej
dc.contributor.authorRadwan, Maciej
dc.contributor.authorRakowski, Franciszek
dc.contributor.authorSemeniuk, Marcin
dc.contributor.authorSzczurek, Ewa
dc.contributor.authorZielinski, Jakub
dc.contributor.authorKisielewski, Jan
dc.contributor.authorPabjan, Barbara
dc.contributor.authorHolger, Kirsten
dc.contributor.authorKheifetz, Yuri
dc.contributor.authorScholz, Markus
dc.contributor.authorPrzemyslaw, Biecek
dc.contributor.authorBodych, Marcin
dc.contributor.authorFilinski, Maciej
dc.contributor.authorIdzikowski, Radoslaw
dc.contributor.authorKrueger, Tyll
dc.contributor.authorOzanski, Tomasz
dc.contributor.authorBracher, Johannes
dc.contributor.authorFunk, Sebastian
dc.date.accessioned2025-07-23T09:54:26Z
dc.date.available2025-07-23T09:54:26Z
dc.date.issued2023-04-21none
dc.identifier.other10.7554/eLife.81916
dc.identifier.urihttp://edoc.rki.de/176904/12861
dc.description.abstractBackground: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC0 1.0) Universell Public Domain Dedicationger
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/deed.de
dc.subjectResearch Articleeng
dc.subjectEpidemiology and Global Healtheng
dc.subjectmodellingeng
dc.subjectforecasteng
dc.subjectCOVID-19eng
dc.subjectEuropeeng
dc.subjectensembleeng
dc.subjectpredictioneng
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titlePredictive performance of multi-model ensemble forecasts of COVID-19 across European nationsnone
dc.typearticle
dc.identifier.urnurn:nbn:de:0257-176904/12861-2
dc.type.versionpublishedVersionnone
local.edoc.container-titleeLifenone
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameeLife Sciences Publications Ltd.none
local.edoc.container-reportyear2023none
local.edoc.container-firstpage1none
local.edoc.container-lastpage19none
dc.description.versionPeer Reviewednone

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