Multiscale influenza forecasting
Influenza forecasting in the United States is challenging and consequential, with the ability to improve the public health response. Here the authors show the performance of the multiscale flu forecasting model, Dante, that won the CDC’s 2018/19 national, regional and state flu forecasting challenge...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-05-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-021-23234-5 |
id |
doaj-0db49a9184444d2a95732ba48372ba74 |
---|---|
record_format |
Article |
spelling |
doaj-0db49a9184444d2a95732ba48372ba742021-05-23T11:13:09ZengNature Publishing GroupNature Communications2041-17232021-05-0112111110.1038/s41467-021-23234-5Multiscale influenza forecastingDave Osthus0Kelly R. Moran1Los Alamos National Laboratory, Statistical Sciences GroupLos Alamos National Laboratory, Statistical Sciences GroupInfluenza forecasting in the United States is challenging and consequential, with the ability to improve the public health response. Here the authors show the performance of the multiscale flu forecasting model, Dante, that won the CDC’s 2018/19 national, regional and state flu forecasting challenges.https://doi.org/10.1038/s41467-021-23234-5 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dave Osthus Kelly R. Moran |
spellingShingle |
Dave Osthus Kelly R. Moran Multiscale influenza forecasting Nature Communications |
author_facet |
Dave Osthus Kelly R. Moran |
author_sort |
Dave Osthus |
title |
Multiscale influenza forecasting |
title_short |
Multiscale influenza forecasting |
title_full |
Multiscale influenza forecasting |
title_fullStr |
Multiscale influenza forecasting |
title_full_unstemmed |
Multiscale influenza forecasting |
title_sort |
multiscale influenza forecasting |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2021-05-01 |
description |
Influenza forecasting in the United States is challenging and consequential, with the ability to improve the public health response. Here the authors show the performance of the multiscale flu forecasting model, Dante, that won the CDC’s 2018/19 national, regional and state flu forecasting challenges. |
url |
https://doi.org/10.1038/s41467-021-23234-5 |
work_keys_str_mv |
AT daveosthus multiscaleinfluenzaforecasting AT kellyrmoran multiscaleinfluenzaforecasting |
_version_ |
1721430033985175552 |