Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

dc.contributor.author Cramer, Estee
dc.contributor.author Lopez, Velma
dc.contributor.author Niemi, Jarad
dc.contributor.author Niemi, Jarad
dc.contributor.author George, Glover
dc.contributor.author Cegan, Jeffrey
dc.contributor.author Dettwiller, Ian
dc.contributor.author England, William
dc.contributor.author Farthing, Matthew
dc.contributor.author Hunter, Robert
dc.contributor.author Lafferty, Brandon
dc.contributor.author Linkov, Igor
dc.contributor.author Mayo, Michael
dc.contributor.author Parno, Matthew
dc.contributor.author Rowland, Michael
dc.contributor.author Trump, Benjamin
dc.contributor.author Wang, Lily
dc.contributor.author Gao, Lei
dc.contributor.author Gu, Zhiling
dc.contributor.author Kim, Myungjin
dc.contributor.author Wang, Yueying
dc.contributor.author Walker, Jo
dc.contributor.author Slayton, Rachel
dc.contributor.author Johansson, Michael
dc.contributor.author Biggerstaff, Matthew
dc.contributor.author et al.
dc.contributor.department Finance
dc.contributor.department Statistics
dc.date 2021-02-11T13:56:24.000
dc.date.accessioned 2021-02-26T13:20:35Z
dc.date.available 2021-02-26T13:20:35Z
dc.date.issued 2022-04-08
dc.description.abstract Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.
dc.description.comments This article is published as Cramer, Estee Y., Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Aaron Gerding et al. "Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States." Proceedings of the National Academy of Sciences 119, no. 15 (2022): e2113561119. doi:10.1073/pnas.2113561119. Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
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dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/315/
dc.identifier.articleid 1317
dc.identifier.contextkey 21590679
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/315
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/98891
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/315/2021_Niemi_EvaluationIndividualPreprint.pdf|||Fri Jan 14 23:32:14 UTC 2022
dc.source.uri https://doi.org/10.1073/pnas.2113561119
dc.subject.disciplines Probability
dc.subject.disciplines Public Health
dc.subject.disciplines Statistical Models
dc.subject.disciplines Virus Diseases
dc.title Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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