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dc.creatorAlamo, Teodoroes
dc.creatorGutiérrez Reina, Danieles
dc.creatorMammarella, Martinaes
dc.creatorAbella, Albertoes
dc.date.accessioned2020-05-18T18:15:15Z
dc.date.available2020-05-18T18:15:15Z
dc.date.issued2020-05
dc.identifier.citationAlamo, T., Gutiérrez Reina, D., Mammarella, M. y Abella, A. (2020). Covid-19: Open-Data Resources for Monitoring, Modeling, and Forecasting the Epidemic. Electronics, 9 (5), 827.
dc.identifier.issn2079-9292es
dc.identifier.urihttps://hdl.handle.net/11441/96875
dc.description.abstractWe provide an insight into the open-data resources pertinent to the study of the spread of the Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behavior, regional mortality rates, and effectiveness of government measures. Open-data resources, along with data-driven methodologies, provide many opportunities to improve the response of the different administrations to the virus. We describe the present limitations and difficulties encountered in most of the open-data resources. To facilitate the access to the main open-data portals and resources, we identify the most relevant institutions, on a global scale, providing Covid-19 information and/or auxiliary variables (demographics, mobility, etc.). We also describe several open resources to access Covid-19 datasets at a country-wide level (i.e., China, Italy, Spain, France, Germany, US, etc.). To facilitate the rapid response to the study of the seasonal behavior of Covid-19, we enumerate the main open resources in terms of weather and climate variables. We also assess the reusability of some representative open-data sources.es
dc.description.sponsorshipPlan Propio de la Universidad de Sevillaes
dc.formatapplication/pdfes
dc.format.extent28 p.es
dc.language.isoenges
dc.publisherMDPI AGes
dc.relation.ispartofElectronics, 9 (5), 827.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCovid-19es
dc.subjectCoronaviruses
dc.subjectSARS-CoV-2es
dc.subjectOpen dataes
dc.subjectData-driven methodses
dc.subjectMachine learninges
dc.subjectSeasonal behaviores
dc.subjectGovernment measureses
dc.titleCovid-19: Open-Data Resources for Monitoring, Modeling, and Forecasting the Epidemices
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería Electrónicaes
dc.relation.publisherversionhttps://www.mdpi.com/2079-9292/9/5/827es
dc.identifier.doi10.3390/electronics9050827es
dc.contributor.groupUniversidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Controles
dc.journaltitleElectronicses
dc.publication.volumen9es
dc.publication.issue5es
dc.publication.initialPage827es

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