The United States COVID-19 Forecast Hub dataset
Date
2022
Authors
Cramer, Estee Y.
Huang, Yuxin
Wang, Yijin
Ray, Evan L.
Cornell, Matthew
Bracher, Johannes
Brennen, Andrea
Castro Rivadeneira, Alvaro J.
Gerding, Aaron
House, Katie
Journal Title
Journal ISSN
Volume Title
Publisher
Scientific Data
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.
Description
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Citation
Cramer, E. Y., Huang, Y., Wang, Y., Ray, E. L., Cornell, M., Bracher, J., . . . US COVID-19 Forecast Hub Consortium (2022). “The United States COVID-19 Forecast Hub dataset.” Scientific Data, 9(462). https://doi.org/10.1038/s41597-022-01517-w