dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2021-06-25T10:27:27Z | |
dc.date.accessioned | 2022-12-19T22:13:38Z | |
dc.date.available | 2021-06-25T10:27:27Z | |
dc.date.available | 2022-12-19T22:13:38Z | |
dc.date.created | 2021-06-25T10:27:27Z | |
dc.date.issued | 2021-05-01 | |
dc.identifier | Journal of Biomedical Informatics, v. 117. | |
dc.identifier | 1532-0464 | |
dc.identifier | http://hdl.handle.net/11449/206154 | |
dc.identifier | 10.1016/j.jbi.2021.103753 | |
dc.identifier | 2-s2.0-85103695064 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5386751 | |
dc.description.abstract | Visual 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.language | eng | |
dc.relation | Journal of Biomedical Informatics | |
dc.source | Scopus | |
dc.subject | COVID-19 | |
dc.subject | Risk assessment | |
dc.subject | Visual analytics | |
dc.title | Visual analytics of COVID-19 dissemination in São Paulo state, Brazil | |
dc.type | Artículos de revistas | |