Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/27755
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dc.contributor.authorMavragani, Amaryllisen_UK
dc.contributor.authorOchoa, Gabrielaen_UK
dc.date.accessioned2018-09-08T00:00:08Z-
dc.date.available2018-09-08T00:00:08Z-
dc.date.issued2018-12-31en_UK
dc.identifier.other30en_UK
dc.identifier.urihttp://hdl.handle.net/1893/27755-
dc.description.abstractBig Data Analytics have become an integral part of Health Informatics over the past years, with the analysis of Internet data being all the more popular in health assessment in various topics. In this study, we first examine the geographical distribution of the online behavioral variations towards Chlamydia, Gonorrhea, Syphilis, Tuberculosis, and Hepatitis in the United States by year from 2004 to 2017. Next, we examine the correlations between Google Trends data and official health data from the ‘Centers for Disease Control and Prevention’ (CDC) on said diseases, followed by estimating linear regressions for the respective relationships. The results show that Infoveillance can assist with exploring public awareness and accurately measure the behavioral changes towards said diseases. The correlations between Google Trends data and CDC data on Chlamydia cases are statistically significant at a national level and in most of the states, while the forecasting exhibits good performing results in many states. For Hepatitis, significant correlations are observed for several US States, while forecasting also exhibits promising results. On the contrary, several factors can affect the applicability of this forecasting method, as in the cases of Gonorrhea, Syphilis, and Tuberculosis, where the correlations are statistically significant in fewer states. Thus this study highlights that the analysis of Google Trends data should be done with caution in order for the results to be robust. In addition, we suggest that the applicability of this method is not that trivial or universal, and that several factors need to be taken into account when using online data in this line of research. However, this study also supports previous findings suggesting that the analysis of real-time online data is important in health assessment, as it tackles the long procedure of data collection and analysis in traditional survey methods, and provides us with information that could not be accessible otherwise.en_UK
dc.language.isoenen_UK
dc.publisherSpringer Nature America, Incen_UK
dc.relationMavragani A & Ochoa G (2018) Infoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitis. Journal of Big Data, 5 (1), Art. No.: 30. https://doi.org/10.1186/s40537-018-0140-9en_UK
dc.rights© The Author(s) 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectBig dataen_UK
dc.subjectChlamydiaen_UK
dc.subjectGonorrheaen_UK
dc.subjectGoogle trends Infodemiologyen_UK
dc.subjectInfoveillanceen_UK
dc.subjectHealth informaticsen_UK
dc.subjectHepatitisen_UK
dc.subjectInternet behavioren_UK
dc.subjectPublic healthen_UK
dc.subjectSexually transmitted diseasesen_UK
dc.subjectSyphilisen_UK
dc.subjectTuberculosisen_UK
dc.titleInfoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitisen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1186/s40537-018-0140-9en_UK
dc.citation.jtitleJournal Of Big Dataen_UK
dc.citation.issn2196-1115en_UK
dc.citation.volume5en_UK
dc.citation.issue1en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.citation.date06/09/2018en_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.wtid993409en_UK
dc.contributor.orcid0000-0001-6106-0873en_UK
dc.contributor.orcid0000-0001-7649-5669en_UK
dc.date.accepted2018-08-22en_UK
dcterms.dateAccepted2018-08-22en_UK
dc.date.filedepositdate2018-09-07en_UK
rioxxterms.apcpaiden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorMavragani, Amaryllis|0000-0001-6106-0873en_UK
local.rioxx.authorOchoa, Gabriela|0000-0001-7649-5669en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2018-09-07en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2018-09-07|en_UK
local.rioxx.filenames40537-018-0140-9.pdfen_UK
local.rioxx.filecount1en_UK
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