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The United States COVID-19 forecast hub dataset

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posted on 2024-09-02, 15:04 authored by 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 Hannan Kanji, Ayush Khandelwal, Pierre NouvelletPierre Nouvellet, et al.
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.

History

Publication status

  • Published

File Version

  • Published version

Journal

Scientific Data

ISSN

2052-4463

Publisher

Springer Science and Business Media LLC

Issue

1

Volume

9

Article number

462

Institution

University of Sussex

Full text available

  • Yes

Peer reviewed?

  • Yes