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Use Internet search data to accurately track state level influenza epidemics

For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a method...

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Detalles Bibliográficos
Autores principales: Yang, Shihao, Ning, Shaoyang, Kou, S. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889878/
https://www.ncbi.nlm.nih.gov/pubmed/33597556
http://dx.doi.org/10.1038/s41598-021-83084-5
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author Yang, Shihao
Ning, Shaoyang
Kou, S. C.
author_facet Yang, Shihao
Ning, Shaoyang
Kou, S. C.
author_sort Yang, Shihao
collection PubMed
description For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a methodology, ARGOX (Augmented Regression with GOogle data CROSS space), for accurate real-time tracking of state-level influenza epidemics in the United States. ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people’s Internet search pattern. ARGOX achieves on average 28% error reduction over the best alternative for real-time state-level influenza estimation for 2014 to 2020. ARGOX is robust and reliable and can be potentially applied to track county- and city-level influenza activity and other infectious diseases.
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spelling pubmed-78898782021-02-22 Use Internet search data to accurately track state level influenza epidemics Yang, Shihao Ning, Shaoyang Kou, S. C. Sci Rep Article For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a methodology, ARGOX (Augmented Regression with GOogle data CROSS space), for accurate real-time tracking of state-level influenza epidemics in the United States. ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people’s Internet search pattern. ARGOX achieves on average 28% error reduction over the best alternative for real-time state-level influenza estimation for 2014 to 2020. ARGOX is robust and reliable and can be potentially applied to track county- and city-level influenza activity and other infectious diseases. Nature Publishing Group UK 2021-02-17 /pmc/articles/PMC7889878/ /pubmed/33597556 http://dx.doi.org/10.1038/s41598-021-83084-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Shihao
Ning, Shaoyang
Kou, S. C.
Use Internet search data to accurately track state level influenza epidemics
title Use Internet search data to accurately track state level influenza epidemics
title_full Use Internet search data to accurately track state level influenza epidemics
title_fullStr Use Internet search data to accurately track state level influenza epidemics
title_full_unstemmed Use Internet search data to accurately track state level influenza epidemics
title_short Use Internet search data to accurately track state level influenza epidemics
title_sort use internet search data to accurately track state level influenza epidemics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889878/
https://www.ncbi.nlm.nih.gov/pubmed/33597556
http://dx.doi.org/10.1038/s41598-021-83084-5
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