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Data management in epiGraph COVID-19 epidemic simulator

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.contributor.authorGuzmán Merino, Miguel
dc.contributor.authorDuran Gonzalez, Christian
dc.contributor.authorMarinescu, María Cristina
dc.contributor.authorDelgado Sanz, Concepción
dc.contributor.authorGómez Barroso, Diana
dc.contributor.authorCarretero Pérez, Jesús
dc.contributor.authorExpósito Singh, David
dc.contributor.funderEuropean Commissionen
dc.contributor.other
dc.date.accessioned2022-01-14T11:23:53Z
dc.date.available2022-01-14T11:23:53Z
dc.date.issued2021-08-29
dc.description.abstractThe transmission of COVID-19 through a population depends on many factors which model, incorporate, and integrate a large number of heterogeneous data sources. The work we describe in this paper focuses on the data management aspect of EpiGraph, a scalable agent-based virus-propagation simulator. We describe the data acquisition and pre-processing tasks that are necessary to map the data to the different models implemented in EpiGraph in a way that is efficient and comprehensible. We also report on post-processing, analysis, and visualization of the outputs, tasks that are fundamental to make the simulation results useful for the final users. Our simulator captures complex interactions between social processes, virus characteristics, travel patterns, climate, vaccination, and non-pharmaceutical interventions. We end by demonstrating the entire pipeline with one evaluation for Spain for the third COVID wave starting on December 27th of 2020.en
dc.description.sponsorshipThis work has been supported by the Spanish Instituto de Salud Carlos III under the project grant 2020/00183/001, the project grant BCV-2021-1-0011, of the Spanish Supercomputing Network (RES) and the European Union's Horizon 2020 JTI-EuroHPC research and innovation program under grant agreement No 956748.en
dc.format.extent13
dc.identifier.bibliographicCitationGuzmán, M., Durán, C., Marinescu, M.C., Delgado, C., Gómez, D., Carretero, J., Singh, D. (2021). Data management in epiGraph COVID-19 epidemic simulator. EasyChair: the world for scientits. https://easychair.org/publications/preprint/Qnvqen
dc.identifier.otherhttps://easychair.org/publications/preprint/Qnvq
dc.identifier.urihttps://hdl.handle.net/10016/33879
dc.identifier.uxxiDT/0000001960
dc.language.isoengen
dc.relation.ispartofseriesEasyChairen
dc.relation.projectIDGobierno de España. COV20/00935
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/956748
dc.rights© The Authors, 2021en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherepidemiological simulationen
dc.subject.otherCOVID-19en
dc.subject.otherheterogeneousen
dc.subject.otherdata processingen
dc.subject.otherparallel toolen
dc.titleData management in epiGraph COVID-19 epidemic simulatoren
dc.typeworking paper*
dc.type.hasVersionSMUR*
dspace.entity.typePublication
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