Early and Real-Time Detection of Seasonal Influenza Onset

Detalhes bibliográficos
Autor(a) principal: Won, Miguel
Data de Publicação: 2017
Outros Autores: Marques-Pita, Manuel, Louro, Carlota, Gonçalves-Sá, Joana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.1371/journal.pcbi.1005330
Resumo: Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.
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spelling Early and Real-Time Detection of Seasonal Influenza OnsetMODELSEPIDEMICSEcology, Evolution, Behavior and SystematicsModelling and SimulationEcologyMolecular BiologyGeneticsCellular and Molecular NeuroscienceComputational Theory and MathematicsEvery year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNWon, MiguelMarques-Pita, ManuelLouro, CarlotaGonçalves-Sá, Joana2018-04-18T22:11:24Z2017-02-032017-02-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.1371/journal.pcbi.1005330eng1553-734XPURE: 2748199http://www.scopus.com/inward/record.url?scp=85014289036&partnerID=8YFLogxKhttps://doi.org/10.1371/journal.pcbi.1005330info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:19:05Zoai:run.unl.pt:10362/34823Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:30:13.014282Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Early and Real-Time Detection of Seasonal Influenza Onset
title Early and Real-Time Detection of Seasonal Influenza Onset
spellingShingle Early and Real-Time Detection of Seasonal Influenza Onset
Won, Miguel
MODELS
EPIDEMICS
Ecology, Evolution, Behavior and Systematics
Modelling and Simulation
Ecology
Molecular Biology
Genetics
Cellular and Molecular Neuroscience
Computational Theory and Mathematics
title_short Early and Real-Time Detection of Seasonal Influenza Onset
title_full Early and Real-Time Detection of Seasonal Influenza Onset
title_fullStr Early and Real-Time Detection of Seasonal Influenza Onset
title_full_unstemmed Early and Real-Time Detection of Seasonal Influenza Onset
title_sort Early and Real-Time Detection of Seasonal Influenza Onset
author Won, Miguel
author_facet Won, Miguel
Marques-Pita, Manuel
Louro, Carlota
Gonçalves-Sá, Joana
author_role author
author2 Marques-Pita, Manuel
Louro, Carlota
Gonçalves-Sá, Joana
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Won, Miguel
Marques-Pita, Manuel
Louro, Carlota
Gonçalves-Sá, Joana
dc.subject.por.fl_str_mv MODELS
EPIDEMICS
Ecology, Evolution, Behavior and Systematics
Modelling and Simulation
Ecology
Molecular Biology
Genetics
Cellular and Molecular Neuroscience
Computational Theory and Mathematics
topic MODELS
EPIDEMICS
Ecology, Evolution, Behavior and Systematics
Modelling and Simulation
Ecology
Molecular Biology
Genetics
Cellular and Molecular Neuroscience
Computational Theory and Mathematics
description Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.
publishDate 2017
dc.date.none.fl_str_mv 2017-02-03
2017-02-03T00:00:00Z
2018-04-18T22:11:24Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.1371/journal.pcbi.1005330
url https://doi.org/10.1371/journal.pcbi.1005330
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1553-734X
PURE: 2748199
http://www.scopus.com/inward/record.url?scp=85014289036&partnerID=8YFLogxK
https://doi.org/10.1371/journal.pcbi.1005330
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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