Computational Approaches to Influenza Surveillance: Beyond Timeliness

Several digital data sources and systems have been advanced for use in augmenting traditional influenza surveillance systems. Although timeliness is one of the main advantages of these tools, there are several other recognizable uses and potential impact of these systems on the public and global pub...

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Detalles Bibliográficos
Autores principales: Nsoesie, Elaine O., Brownstein, John S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2015
Materias:
Commentary
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492472/
https://www.ncbi.nlm.nih.gov/pubmed/25766284
http://dx.doi.org/10.1016/j.chom.2015.02.004
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author Nsoesie, Elaine O.
Brownstein, John S.
author_facet Nsoesie, Elaine O.
Brownstein, John S.
author_sort Nsoesie, Elaine O.
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description Several digital data sources and systems have been advanced for use in augmenting traditional influenza surveillance systems. Although timeliness is one of the main advantages of these tools, there are several other recognizable uses and potential impact of these systems on the public and global public health.
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spelling pubmed-44924722016-03-11 Computational Approaches to Influenza Surveillance: Beyond Timeliness Nsoesie, Elaine O. Brownstein, John S. Cell Host Microbe Commentary Several digital data sources and systems have been advanced for use in augmenting traditional influenza surveillance systems. Although timeliness is one of the main advantages of these tools, there are several other recognizable uses and potential impact of these systems on the public and global public health. Elsevier Inc. 2015-03-11 2015-03-11 /pmc/articles/PMC4492472/ /pubmed/25766284 http://dx.doi.org/10.1016/j.chom.2015.02.004 Text en Copyright © 2015 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Commentary
Nsoesie, Elaine O.
Brownstein, John S.
Computational Approaches to Influenza Surveillance: Beyond Timeliness
title Computational Approaches to Influenza Surveillance: Beyond Timeliness
title_full Computational Approaches to Influenza Surveillance: Beyond Timeliness
title_fullStr Computational Approaches to Influenza Surveillance: Beyond Timeliness
title_full_unstemmed Computational Approaches to Influenza Surveillance: Beyond Timeliness
title_short Computational Approaches to Influenza Surveillance: Beyond Timeliness
title_sort computational approaches to influenza surveillance: beyond timeliness
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492472/
https://www.ncbi.nlm.nih.gov/pubmed/25766284
http://dx.doi.org/10.1016/j.chom.2015.02.004
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