Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis.

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dc.citation.journalTitleDiseases
dc.contributor.authorParra, Mayra Elizabeth
dc.contributor.authorM.E PUERTA
dc.contributor.authorLisarralde, Diana Paola
dc.contributor.authorArboleda, Sair
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupMatemáticas y Aplicacionesspa
dc.creatorParra, Mayra Elizabeth
dc.creatorM.E PUERTA
dc.creatorLisarralde, Diana Paola
dc.creatorArboleda, Sair
dc.date.accessioned2021-04-12T14:04:21Z
dc.date.available2021-04-12T14:04:21Z
dc.date.issued2016-03-29
dc.description.abstractDengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=6611
dc.identifier.doi10.3390/diseases4020016
dc.identifier.issn20799721
dc.identifier.otherPUBMED;28933396
dc.identifier.urihttp://hdl.handle.net/10784/27705
dc.language.isoengeng
dc.publisherMDPI
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/2079-9721
dc.sourceDiseases
dc.subjectdengue risk classificationeng
dc.subjectearly warningeng
dc.subjectspatial analysiseng
dc.subjecttemporal indiceseng
dc.titleEarly Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis.eng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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