dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2021-06-25T10:27:27Z
dc.date.accessioned2022-12-19T22:13:38Z
dc.date.available2021-06-25T10:27:27Z
dc.date.available2022-12-19T22:13:38Z
dc.date.created2021-06-25T10:27:27Z
dc.date.issued2021-05-01
dc.identifierJournal of Biomedical Informatics, v. 117.
dc.identifier1532-0464
dc.identifierhttp://hdl.handle.net/11449/206154
dc.identifier10.1016/j.jbi.2021.103753
dc.identifier2-s2.0-85103695064
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5386751
dc.description.abstractVisual analytics techniques are useful tools to support decision-making and cope with increasing data, particularly to monitor natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination. We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on comparing a city under consideration and its neighborhood. Moreover, such analysis is performed within periods, which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of São Paulo state, Brazil.
dc.languageeng
dc.relationJournal of Biomedical Informatics
dc.sourceScopus
dc.subjectCOVID-19
dc.subjectRisk assessment
dc.subjectVisual analytics
dc.titleVisual analytics of COVID-19 dissemination in São Paulo state, Brazil
dc.typeArtículos de revistas


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