Google Trends (GT) related to influenza

Autores
Wiwanitkit, Viroj; Orellano, Pablo Wenceslao; Reynoso, Julieta Itati; Antman, Julián; Argibay, Osvaldo
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The recent paper on Using Google Trends (GT) to Estimate the Incidence of Influenza-Like Illness in Argentina 1 is very interesting. Orellano et al. studied Google Flu Trends (GFT) and GT with a conclusion regarding “the utility of GT to complement influenza surveillance”. Indeed, the usefulness of GFT and GT has been mentioned in some earlier reports 2,3. However, as a computational model, there are several things to be considered in the simulation 4. Under- or over-estimation can be expected and this is still the present problem in using the Google system for predicting influenza 4. There is a need for modifications of GT and GFT into a more specific tool that is appropriate for each context. A good example of this is the development of FluBreaks by Pervaiz et al.
Fil: Wiwanitkit, Viroj. Wiwanitkit House; Tailandia. Surin Rajabhat University; Tailandia. Hainan Medical College; China
Fil: Orellano, Pablo Wenceslao. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Surin Rajabhat University; Tailandia
Fil: Reynoso, Julieta Itati. Wiwanitkit House; Tailandia
Fil: Antman, Julián. Hainan Medical College; China
Fil: Argibay, Osvaldo. Hainan Medical College; China
Materia
Human Influenza
Epidemiologic Models
Incidence
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/103668
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Google Trends (GT) related to influenzaGoogle Trends relacionado à influenzaGoogle Trends relacionado a la influenzaWiwanitkit, VirojOrellano, Pablo WenceslaoReynoso, Julieta ItatiAntman, JuliánArgibay, OsvaldoHuman InfluenzaEpidemiologic ModelsIncidencehttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3The recent paper on Using Google Trends (GT) to Estimate the Incidence of Influenza-Like Illness in Argentina 1 is very interesting. Orellano et al. studied Google Flu Trends (GFT) and GT with a conclusion regarding “the utility of GT to complement influenza surveillance”. Indeed, the usefulness of GFT and GT has been mentioned in some earlier reports 2,3. However, as a computational model, there are several things to be considered in the simulation 4. Under- or over-estimation can be expected and this is still the present problem in using the Google system for predicting influenza 4. There is a need for modifications of GT and GFT into a more specific tool that is appropriate for each context. A good example of this is the development of FluBreaks by Pervaiz et al.Fil: Wiwanitkit, Viroj. Wiwanitkit House; Tailandia. Surin Rajabhat University; Tailandia. Hainan Medical College; ChinaFil: Orellano, Pablo Wenceslao. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Surin Rajabhat University; TailandiaFil: Reynoso, Julieta Itati. Wiwanitkit House; TailandiaFil: Antman, Julián. Hainan Medical College; ChinaFil: Argibay, Osvaldo. Hainan Medical College; ChinaCadernos Saude Publica2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/103668Wiwanitkit, Viroj; Orellano, Pablo Wenceslao; Reynoso, Julieta Itati; Antman, Julián; Argibay, Osvaldo; Google Trends (GT) related to influenza; Cadernos Saude Publica; Cadernos de Saúde Pública; 31; 6; 6-2015; 1334-13350102-311X1678-4464CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2015000601334info:eu-repo/semantics/altIdentifier/doi/10.1590/0102-311XCA020615info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:46:13Zoai:ri.conicet.gov.ar:11336/103668instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:46:13.35CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Google Trends (GT) related to influenza
Google Trends relacionado à influenza
Google Trends relacionado a la influenza
title Google Trends (GT) related to influenza
spellingShingle Google Trends (GT) related to influenza
Wiwanitkit, Viroj
Human Influenza
Epidemiologic Models
Incidence
title_short Google Trends (GT) related to influenza
title_full Google Trends (GT) related to influenza
title_fullStr Google Trends (GT) related to influenza
title_full_unstemmed Google Trends (GT) related to influenza
title_sort Google Trends (GT) related to influenza
dc.creator.none.fl_str_mv Wiwanitkit, Viroj
Orellano, Pablo Wenceslao
Reynoso, Julieta Itati
Antman, Julián
Argibay, Osvaldo
author Wiwanitkit, Viroj
author_facet Wiwanitkit, Viroj
Orellano, Pablo Wenceslao
Reynoso, Julieta Itati
Antman, Julián
Argibay, Osvaldo
author_role author
author2 Orellano, Pablo Wenceslao
Reynoso, Julieta Itati
Antman, Julián
Argibay, Osvaldo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Human Influenza
Epidemiologic Models
Incidence
topic Human Influenza
Epidemiologic Models
Incidence
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv The recent paper on Using Google Trends (GT) to Estimate the Incidence of Influenza-Like Illness in Argentina 1 is very interesting. Orellano et al. studied Google Flu Trends (GFT) and GT with a conclusion regarding “the utility of GT to complement influenza surveillance”. Indeed, the usefulness of GFT and GT has been mentioned in some earlier reports 2,3. However, as a computational model, there are several things to be considered in the simulation 4. Under- or over-estimation can be expected and this is still the present problem in using the Google system for predicting influenza 4. There is a need for modifications of GT and GFT into a more specific tool that is appropriate for each context. A good example of this is the development of FluBreaks by Pervaiz et al.
Fil: Wiwanitkit, Viroj. Wiwanitkit House; Tailandia. Surin Rajabhat University; Tailandia. Hainan Medical College; China
Fil: Orellano, Pablo Wenceslao. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Surin Rajabhat University; Tailandia
Fil: Reynoso, Julieta Itati. Wiwanitkit House; Tailandia
Fil: Antman, Julián. Hainan Medical College; China
Fil: Argibay, Osvaldo. Hainan Medical College; China
description The recent paper on Using Google Trends (GT) to Estimate the Incidence of Influenza-Like Illness in Argentina 1 is very interesting. Orellano et al. studied Google Flu Trends (GFT) and GT with a conclusion regarding “the utility of GT to complement influenza surveillance”. Indeed, the usefulness of GFT and GT has been mentioned in some earlier reports 2,3. However, as a computational model, there are several things to be considered in the simulation 4. Under- or over-estimation can be expected and this is still the present problem in using the Google system for predicting influenza 4. There is a need for modifications of GT and GFT into a more specific tool that is appropriate for each context. A good example of this is the development of FluBreaks by Pervaiz et al.
publishDate 2015
dc.date.none.fl_str_mv 2015-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/103668
Wiwanitkit, Viroj; Orellano, Pablo Wenceslao; Reynoso, Julieta Itati; Antman, Julián; Argibay, Osvaldo; Google Trends (GT) related to influenza; Cadernos Saude Publica; Cadernos de Saúde Pública; 31; 6; 6-2015; 1334-1335
0102-311X
1678-4464
CONICET Digital
CONICET
url http://hdl.handle.net/11336/103668
identifier_str_mv Wiwanitkit, Viroj; Orellano, Pablo Wenceslao; Reynoso, Julieta Itati; Antman, Julián; Argibay, Osvaldo; Google Trends (GT) related to influenza; Cadernos Saude Publica; Cadernos de Saúde Pública; 31; 6; 6-2015; 1334-1335
0102-311X
1678-4464
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2015000601334
info:eu-repo/semantics/altIdentifier/doi/10.1590/0102-311XCA020615
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cadernos Saude Publica
publisher.none.fl_str_mv Cadernos Saude Publica
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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