The United States COVID-19 Forecast Hub dataset
The United States COVID-19 Forecast Hub dataset
About this item
Full title
Author / Creator
Cramer, Estee Y. , Huang, Yuxin , Wang, Yijin , Ray, Evan L. , Cornell, Matthew , Bracher, Johannes , Brennen, Andrea , Rivadeneira, Alvaro J. Castro , Gerding, Aaron , House, Katie , Jayawardena, Dasuni , Kanji, Abdul Hannan , Khandelwal, Ayush , Le, Khoa , Mody, Vidhi , Mody, Vrushti , Niemi, Jarad , Stark, Ariane , Shah, Apurv , Wattanchit, Nutcha , Zorn, Martha W. , Reich, Nicholas G. , US COVID-19 Forecast Hub Consortium and Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
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 U...
Alternative Titles
Full title
The United States COVID-19 Forecast Hub dataset
Authors, Artists and Contributors
Author / Creator
Huang, Yuxin
Wang, Yijin
Ray, Evan L.
Cornell, Matthew
Bracher, Johannes
Brennen, Andrea
Rivadeneira, Alvaro J. Castro
Gerding, Aaron
House, Katie
Jayawardena, Dasuni
Kanji, Abdul Hannan
Khandelwal, Ayush
Le, Khoa
Mody, Vidhi
Mody, Vrushti
Niemi, Jarad
Stark, Ariane
Shah, Apurv
Wattanchit, Nutcha
Zorn, Martha W.
Reich, Nicholas G.
US COVID-19 Forecast Hub Consortium
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_300e02be0bde4c32adf9ae19db234dca
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_300e02be0bde4c32adf9ae19db234dca
Other Identifiers
ISSN
2052-4463
E-ISSN
2052-4463
DOI
10.1038/s41597-022-01517-w
