Publication:
Social media posts and online search behaviour as early-warning system for MRSA outbreaks.

dc.contributor.authorvan de Belt, Tom H
dc.contributor.authorvan Stockum, Pieter T
dc.contributor.authorEngelen, Lucien J L P G
dc.contributor.authorLancee, Jules
dc.contributor.authorSchrijver, Remco
dc.contributor.authorRodríguez-Baño, Jesús
dc.contributor.authorTacconelli, Evelina
dc.contributor.authorSaris, Katja
dc.contributor.authorvan Gelder, Marleen M H J
dc.contributor.authorVoss, Andreas
dc.date.accessioned2023-01-25T10:10:47Z
dc.date.available2023-01-25T10:10:47Z
dc.date.issued2018-05-30
dc.description.abstractDespite many preventive measures, outbreaks with multi-drug resistant micro-organisms (MDROs) still occur. Moreover, current alert systems from healthcare organizations have shortcomings due to delayed or incomplete notifications, which may amplify the spread of MDROs by introducing infected patients into a new healthcare setting and institutions. Additional sources of information about upcoming and current outbreaks, may help to prevent further spread of MDROs.The study objective was to evaluate whether methicillin-resistant Staphylococcus aureus (MRSA) outbreaks could be detected via social media posts or online search behaviour; if so, this might allow earlier detection than the official notifications by healthcare organizations. We conducted an exploratory study in which we compared information about MRSA outbreaks in the Netherlands derived from two online sources, Coosto for Social Media, and Google Trends for search behaviour, to the mandatory Dutch outbreak notification system (SO-ZI/AMR). The latter provides information on MDRO outbreaks including the date of the outbreak, micro-organism involved, the region/location, and the type of health care organization. During the research period of 15 months (455 days), 49 notifications of outbreaks were recorded in SO-ZI/AMR. For Coosto, the number of unique potential outbreaks was 37 and for Google Trends 24. The use of social media and online search behaviour missed many of the hospital outbreaks that were reported to SO-ZI/AMR, but detected additional outbreaks in long-term care facilities. Despite several limitations, using information from social media and online search behaviour allows rapid identification of potential MRSA outbreaks, especially in healthcare settings with a low notification compliance. When combined in an automated system with real-time updates, this approach might increase early discovery and subsequent implementation of preventive measures.
dc.identifier.doi10.1186/s13756-018-0359-4
dc.identifier.essn2047-2994
dc.identifier.pmcPMC5977481
dc.identifier.pmid29876100
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977481/pdf
dc.identifier.unpaywallURLhttps://doi.org/10.1186/s13756-018-0359-4
dc.identifier.urihttp://hdl.handle.net/10668/12556
dc.journal.titleAntimicrobial resistance and infection control
dc.journal.titleabbreviationAntimicrob Resist Infect Control
dc.language.isoen
dc.organizationInstituto de Biomedicina de Sevilla-IBIS
dc.organizationHospital Universitario Virgen del Rocío
dc.organizationHospital Universitario Virgen Macarena
dc.page.number69
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGoogle trends
dc.subjectMRSA
dc.subjectMethicillin-resistant Staphylococcus aureus
dc.subjectNowcasting
dc.subjectOutbreaks
dc.subjectSocial media monitoring
dc.subject.meshCross Infection
dc.subject.meshDisease Outbreaks
dc.subject.meshDrug Resistance, Multiple, Bacterial
dc.subject.meshHumans
dc.subject.meshInfection Control
dc.subject.meshLong-Term Care
dc.subject.meshMethicillin-Resistant Staphylococcus aureus
dc.subject.meshNetherlands
dc.subject.meshSearch Engine
dc.subject.meshSocial Media
dc.subject.meshStaphylococcal Infections
dc.titleSocial media posts and online search behaviour as early-warning system for MRSA outbreaks.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number7
dspace.entity.typePublication

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