Scientific article
OA Policy
English

The United States COVID-19 Forecast Hub dataset

Published inScientific data, vol. 9, no. 1, 462
Publication date2022-08-01
First online date2022-08-01
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 cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, 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.

Keywords
  • COVID-19
  • Centers for Disease Control and Prevention, U.S
  • Forecasting
  • Humans
  • Pandemics
  • United States / epidemiology
Funding
  • ACL HHS [U01CK000538]
  • NCEZID CDC HHS [U01 CK000594]
  • NIGMS NIH HHS [R01 GM140564]
  • NCEZID CDC HHS [U01 CK000531]
  • NCIRD CDC HHS [U01 IP001137]
  • ACL HHS [U01IP001122]
  • ACL HHS [U01CK000531]
  • ACL HHS [U01CK000594]
  • NIGMS NIH HHS [R35 GM119582]
  • NIGMS NIH HHS [R01 GM111510]
  • NIGMS NIH HHS [R01 GM109718]
  • NIGMS NIH HHS [R01 GM076570]
  • NICHD NIH HHS [P2C HD066613]
Citation (ISO format)
CRAMER, Estee Y et al. The United States COVID-19 Forecast Hub dataset. In: Scientific data, 2022, vol. 9, n° 1, p. 462. doi: 10.1038/s41597-022-01517-w
Main files (1)
Article (Published version)
Identifiers
Additional URL for this publicationhttps://www.nature.com/articles/s41597-022-01517-w
Journal ISSN2052-4463
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3downloads

Technical informations

Creation30/09/2025 16:45:54
First validation14/07/2026 08:41:44
Update14/07/2026 08:41:44
Status update14/07/2026 08:41:44
Last indexation14/07/2026 08:41:45
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