The United States COVID-19 Forecast Hub dataset.

Cramer, Estee YORCID logo; Huang, Yuxin; Wang, YijinORCID logo; Ray, Evan L; Cornell, Matthew; Bracher, Johannes; Brennen, Andrea; Rivadeneira, Alvaro J Castro; Gerding, Aaron; House, Katie; +13 more...Jayawardena, Dasuni; Kanji, Abdul Hannan; Khandelwal, Ayush; Le, Khoa; Mody, Vidhi; Mody, Vrushti; Niemi, JaradORCID logo; Stark, ArianeORCID logo; Shah, Apurv; Wattanchit, Nutcha; Zorn, Martha W; Reich, Nicholas G; and US COVID-19 Forecast Hub Consortium (2022) The United States COVID-19 Forecast Hub dataset. Scientific data, 9 (1). 462-. ISSN 2052-4463 DOI: 10.1038/s41597-022-01517-w
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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.


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