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dc.contributor.authorBertsimas, Dimitris
dc.date.accessioned2022-07-27T16:16:19Z
dc.date.available2022-07-27T16:16:19Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/144073
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in 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.</jats:p>en_US
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionof10.1038/S41467-021-25207-0en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleA pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second waveen_US
dc.typeArticleen_US
dc.identifier.citationBertsimas, Dimitris. 2021. "A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave." Nature Communications, 12 (1).
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.relation.journalNature Communicationsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-07-27T16:04:47Z
dspace.orderedauthorsBracher, J; Wolffram, D; Deuschel, J; Görgen, K; Ketterer, JL; Ullrich, A; Abbott, S; Barbarossa, MV; Bertsimas, D; Bhatia, S; Bodych, M; Bosse, NI; Burgard, JP; Castro, L; Fairchild, G; Fuhrmann, J; Funk, S; Gogolewski, K; Gu, Q; Heyder, S; Hotz, T; Kheifetz, Y; Kirsten, H; Krueger, T; Krymova, E; Li, ML; Meinke, JH; Michaud, IJ; Niedzielewski, K; Ożański, T; Rakowski, F; Scholz, M; Soni, S; Srivastava, A; Zieliński, J; Zou, D; Gneiting, T; Schienle, M; Li, ML; Bertsimas, D; Bouardi, HT; Lami, OS; Soni, S; Abbott, S; Bosse, NI; Funk, S; Barbarossa, MV; Fuhrmann, J; Meinke, JH; Bracher, J; Deuschel, J; Gneiting, T; Görgen, K; Ketterer, J; Schienle, M; Ullrich, A; Wolffram, D; Górski, Ł; Gruziel-Słomka, M; Kaczorek, A; Moszyński, A; Niedzielewski, K; Nowosielski, J; Radwan, M; Rakowski, F; Semeniuk, M; Zieliński, J; Bartczuk, R; Kisielewski, J; Bhatia, S; Biecek, P; Bezborodov, V; Bodych, M; Krueger, T; Burgard, JP; Heyder, S; Hotz, T; Osthus, DA; Michaud, IJ; Castro, L; Fairchild, G; Kheifetz, Y; Kirsten, H; Scholz, M; Gambin, A; Gogolewski, K; Miasojedow, B; Szczurek, E; Rabczenko, D; Rosińska, M; Bawiec, M; Bodych, M; Ożański, T; Pabjan, B; Rafajłlowicz, E; Skubalska-Rafajłowicz, E; Rafajłowicz, W; Migalska, A; Szczurek, E; Flahault, A; Manetti, E; Choirat, C; Haro, BB; Krymova, E; Lee, G; Obozinski, G; Sun, T; Thanou, D; Gu, Q; Xu, P; Chen, J; Wang, L; Zou, D; Zhang, W; Srivastava, A; Prasanna, VK; Xu, FTen_US
dspace.date.submission2022-07-27T16:04:48Z
mit.journal.volume12en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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