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The United States COVID-19 Forecast Hub dataset
Estee Y Cramer; Yuxin Huang; Yijin Wang; Evan L Ray; Matthew Cornell; Johannes Bracher; Andrea Brennen; Alvaro J Castro Rivadeneira; Aaron Gerding; Katie House; Dasuni Jayawardena; Abdul H Kanji; Ayush Khandelwal; Khoa Le; Jarad Niemi; Ariane Stark; Apurv Shah; Nutcha Wattanachit; Martha W Zorn; Nicholas G Reich; - US COVID-19 Forecast Hub Consortium.
Afiliação
  • Estee Y Cramer; University of Massachusetts Amherst
  • Yuxin Huang; University of Massachusetts Amherst
  • Yijin Wang; University of Massachusetts Amherst
  • Evan L Ray; University of Massachusetts Amherst
  • Matthew Cornell; University of Massachusetts Amherst
  • Johannes Bracher; Chair of Econometrics and Statistics, Karlsruhe Institute of Technology
  • Andrea Brennen; IQT Labs
  • Alvaro J Castro Rivadeneira; University of Massachusetts Amherst
  • Aaron Gerding; University of Massachusetts Amherst
  • Katie House; University of Massachusetts Amherst
  • Dasuni Jayawardena; University of Massachusetts Amherst
  • Abdul H Kanji; University of Massachusetts Amherst
  • Ayush Khandelwal; University of Massachusetts Amherst
  • Khoa Le; University of Massachusetts Amherst
  • Jarad Niemi; Iowa State University
  • Ariane Stark; University of Massachusetts Amherst
  • Apurv Shah; University of Massachusetts Amherst
  • Nutcha Wattanachit; University of Massachusetts Amherst
  • Martha W Zorn; University of Massachusetts Amherst
  • Nicholas G Reich; University of Massachusetts Amherst
  • - US COVID-19 Forecast Hub Consortium;
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21265886
ABSTRACT
Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.
Licença
cc0
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Rct Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Rct Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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