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Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015

Google Trends (GT) was mined from 2004 to 2015, searching for West-Nile virus disease (WNVD) in Italy. GT-generated data were modeled as a time series and were analyzed using classical time series analyses. In particular, correlation between GT-based Relative Search Volumes (RSVs) related to WNVD an...

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Autores principales: Bragazzi, Nicola Luigi, Bacigaluppi, Susanna, Robba, Chiara, Siri, Anna, Canepa, Giovanna, Brigo, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107683/
https://www.ncbi.nlm.nih.gov/pubmed/27872881
http://dx.doi.org/10.1016/j.dib.2016.10.022
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author Bragazzi, Nicola Luigi
Bacigaluppi, Susanna
Robba, Chiara
Siri, Anna
Canepa, Giovanna
Brigo, Francesco
author_facet Bragazzi, Nicola Luigi
Bacigaluppi, Susanna
Robba, Chiara
Siri, Anna
Canepa, Giovanna
Brigo, Francesco
author_sort Bragazzi, Nicola Luigi
collection PubMed
description Google Trends (GT) was mined from 2004 to 2015, searching for West-Nile virus disease (WNVD) in Italy. GT-generated data were modeled as a time series and were analyzed using classical time series analyses. In particular, correlation between GT-based Relative Search Volumes (RSVs) related to WNVD and “real-world” epidemiological cases in the same study period resulted r=0.76 (p<0.0001) on a monthly basis and r=0.80 (p<0.0001) on a yearly basis. The partial autocorrelation analysis and the spectral analysis confirmed that a 1-year regular pattern could be detected. Correlation between GT-based RSVs related to WNVD yielded a r=0.54 (p<0.05) on a regional basis. Summarizing, GT-generated data concerning WNVD well correlated with epidemiology and could be exploited for complementing traditional surveillance.
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spelling pubmed-51076832016-11-21 Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015 Bragazzi, Nicola Luigi Bacigaluppi, Susanna Robba, Chiara Siri, Anna Canepa, Giovanna Brigo, Francesco Data Brief Data Article Google Trends (GT) was mined from 2004 to 2015, searching for West-Nile virus disease (WNVD) in Italy. GT-generated data were modeled as a time series and were analyzed using classical time series analyses. In particular, correlation between GT-based Relative Search Volumes (RSVs) related to WNVD and “real-world” epidemiological cases in the same study period resulted r=0.76 (p<0.0001) on a monthly basis and r=0.80 (p<0.0001) on a yearly basis. The partial autocorrelation analysis and the spectral analysis confirmed that a 1-year regular pattern could be detected. Correlation between GT-based RSVs related to WNVD yielded a r=0.54 (p<0.05) on a regional basis. Summarizing, GT-generated data concerning WNVD well correlated with epidemiology and could be exploited for complementing traditional surveillance. Elsevier 2016-11-02 /pmc/articles/PMC5107683/ /pubmed/27872881 http://dx.doi.org/10.1016/j.dib.2016.10.022 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Bragazzi, Nicola Luigi
Bacigaluppi, Susanna
Robba, Chiara
Siri, Anna
Canepa, Giovanna
Brigo, Francesco
Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title_full Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title_fullStr Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title_full_unstemmed Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title_short Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015
title_sort infodemiological data of west-nile virus disease in italy in the study period 2004–2015
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107683/
https://www.ncbi.nlm.nih.gov/pubmed/27872881
http://dx.doi.org/10.1016/j.dib.2016.10.022
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