TY - JOUR
T1 - The United States COVID-19 Forecast Hub dataset
AU - US COVID-19 Forecast Hub Consortium
AU - Cramer, Estee Y.
AU - Huang, Yuxin
AU - Wang, Yijin
AU - Ray, Evan L.
AU - Cornell, Matthew
AU - Bracher, Johannes
AU - Brennen, Andrea
AU - Rivadeneira, Alvaro J.Castro
AU - Gerding, Aaron
AU - House, Katie
AU - Jayawardena, Dasuni
AU - Kanji, Abdul Hannan
AU - Khandelwal, Ayush
AU - Le, Khoa
AU - Mody, Vidhi
AU - Mody, Vrushti
AU - Niemi, Jarad
AU - Stark, Ariane
AU - Shah, Apurv
AU - Wattanchit, Nutcha
AU - Zorn, Martha W.
AU - Reich, Nicholas G.
AU - Gneiting, Tilmann
AU - Mühlemann, Anja
AU - Gu, Youyang
AU - Chen, Yixian
AU - Chintanippu, Krishna
AU - Jivane, Viresh
AU - Khurana, Ankita
AU - Kumar, Ajay
AU - Lakhani, Anshul
AU - Mehrotra, Prakhar
AU - Pasumarty, Sujitha
AU - Shrivastav, Monika
AU - You, Jialu
AU - Bannur, Nayana
AU - Deva, Ayush
AU - Jain, Sansiddh
AU - Kulkarni, Mihir
AU - Merugu, Srujana
AU - Raval, Alpan
AU - Shingi, Siddhant
AU - Tiwari, Avtansh
AU - White, Jerome
AU - Adiga, Aniruddha
AU - Hurt, Benjamin
AU - Lewis, Bryan
AU - Marathe, Madhav
AU - Peddireddy, Akhil Sai
AU - Wang, Lijing
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85135353963&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135353963&partnerID=8YFLogxK
U2 - 10.1038/s41597-022-01517-w
DO - 10.1038/s41597-022-01517-w
M3 - Article
C2 - 35915104
AN - SCOPUS:85135353963
SN - 2052-4463
VL - 9
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 462
ER -