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BouardiAyer, TurgayTurgayAyerAdee, MadelineMadelineAdeeChhatwal, JagpreetJagpreetChhatwalDalgic, Ozden OOzden ODalgicLadd, Mary AMary ALaddLinas, Benjamin PBenjamin PLinasMueller, PeterPeterMuellerXiao, JadeJadeXiaoWang, YuanjiaYuanjiaWangWang, QinxiaQinxiaWangXie, ShanghongShanghongXieZeng, DonglinDonglinZengGreen, AldenAldenGreenBien, JacobJacobBienBrooks, LoganLoganBrooksHu, Addison JAddison JHuJahja, MariaMariaJahjaMcDonald, DanielDanielMcDonaldNarasimhan, BalasubramanianBalasubramanianNarasimhanPolitsch, CollinCollinPolitschRajanala, SamyakSamyakRajanalaRumack, AaronAaronRumackSimon, NoahNoahSimonTibshirani, Ryan JRyan JTibshiraniTibshirani, RobRobTibshiraniVentura, ValerieValerieVenturaWasserman, LarryLarryWassermanO'Dea, Eamon BEamon BO'DeaDrake, John MJohn MDrakePagano, RobertRobertPaganoTran, Quoc TQuoc TTranHo, Lam Si TungLam Si TungHoHuynh, HuongHuongHuynhWalker, Jo WJo WWalkerSlayton, Rachel BRachel BSlaytonJohansson, Michael AMichael AJohanssonBiggerstaff, MatthewMatthewBiggerstaffReich, Nicholas GNicholas GReich2024-10-092024-10-092022-04-12https://boris-portal.unibe.ch/handle/20.500.12422/70082SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.enCOVID-19 ensemble forecast forecasting model evaluation300 - Social sciences, sociology & anthropology::360 - Social problems & social services500 - Science::510 - Mathematicsarticle10.48350/1691783539486210.1073/pnas.2113561119