Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31085
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dc.contributor.authorMavragani, Amaryllisen_UK
dc.date.accessioned2020-05-01T00:04:32Z-
dc.date.available2020-05-01T00:04:32Z-
dc.date.issued2020-04en_UK
dc.identifier.urihttp://hdl.handle.net/1893/31085-
dc.description.abstractBackground: Web-based sources are increasingly employed in the analysis, detection, and forecasting of diseases and epidemics, and in predicting human behavior toward several health topics. This use of the internet has come to be known as infodemiology, a concept introduced by Gunther Eysenbach. Infodemiology and infoveillance studies use web-based data and have become an integral part of health informatics research over the past decade. Objective: The aim of this paper is to provide a scoping review of the state-of-the-art in infodemiology along with the background and history of the concept, to identify sources and health categories and topics, to elaborate on the validity of the employed methods, and to discuss the gaps identified in current research. Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to extract the publications that fall under the umbrella of infodemiology and infoveillance from the JMIR, PubMed, and Scopus databases. A total of 338 documents were extracted for assessment. Results: Of the 338 studies, the vast majority (n=282, 83.4%) were published with JMIR Publications. The Journal of Medical Internet Research features almost half of the publications (n=168, 49.7%), and JMIR Public Health and Surveillance has more than one-fifth of the examined studies (n=74, 21.9%). The interest in the subject has been increasing every year, with 2018 featuring more than one-fourth of the total publications (n=89, 26.3%), and the publications in 2017 and 2018 combined accounted for more than half (n=171, 50.6%) of the total number of publications in the last decade. The most popular source was Twitter with 45.0% (n=152), followed by Google with 24.6% (n=83), websites and platforms with 13.9% (n=47), blogs and forums with 10.1% (n=34), Facebook with 8.9% (n=30), and other search engines with 5.6% (n=19). As for the subjects examined, conditions and diseases with 17.2% (n=58) and epidemics and outbreaks with 15.7% (n=53) were the most popular categories identified in this review, followed by health care (n=39, 11.5%), drugs (n=40, 10.4%), and smoking and alcohol (n=29, 8.6%). Conclusions: The field of infodemiology is becoming increasingly popular, employing innovative methods and approaches for health assessment. The use of web-based sources, which provide us with information that would not be accessible otherwise and tackles the issues arising from the time-consuming traditional methods, shows that infodemiology plays an important role in health informatics research.en_UK
dc.language.isoenen_UK
dc.publisherJMIR Publications Inc.en_UK
dc.relationMavragani A (2020) Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research, 22 (4), p. e16206. https://doi.org/10.2196/16206en_UK
dc.rights©Amaryllis Mavragani. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.04.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectbig dataen_UK
dc.subjectinfodemiologyen_UK
dc.subjectinfoveillanceen_UK
dc.subjectinterneten_UK
dc.subjectreviewen_UK
dc.subjectweb-based dataen_UK
dc.titleInfodemiology and Infoveillance: Scoping Reviewen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.2196/16206en_UK
dc.identifier.pmid32310818en_UK
dc.citation.jtitleJournal of Medical Internet Researchen_UK
dc.citation.issn1438-8871en_UK
dc.citation.issn1439-4456en_UK
dc.citation.volume22en_UK
dc.citation.issue4en_UK
dc.citation.spagee16206en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.citation.date28/04/2020en_UK
dc.contributor.affiliationComputing Science and Mathematics - Divisionen_UK
dc.identifier.isiWOS:000529065600001en_UK
dc.identifier.scopusid2-s2.0-85084168060en_UK
dc.identifier.wtid1609670en_UK
dc.contributor.orcid0000-0001-6106-0873en_UK
dc.date.accepted2020-02-08en_UK
dcterms.dateAccepted2020-02-08en_UK
dc.date.filedepositdate2020-04-30en_UK
rioxxterms.apcpaiden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorMavragani, Amaryllis|0000-0001-6106-0873en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2020-04-30en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2020-04-30|en_UK
local.rioxx.filenameAMavragani-JMIR-Apr2020.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1438-8871en_UK
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