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dc.contributor.author | Benlloch Baviera, Jose María![]() |
es_ES |
dc.contributor.author | Cortés, J.-C.![]() |
es_ES |
dc.contributor.author | Martínez-Rodríguez, David![]() |
es_ES |
dc.contributor.author | San Julián-Garcés, Raúl![]() |
es_ES |
dc.contributor.author | Villanueva Micó, Rafael Jacinto![]() |
es_ES |
dc.date.accessioned | 2021-02-06T04:33:55Z | |
dc.date.available | 2021-02-06T04:33:55Z | |
dc.date.issued | 2020-11 | es_ES |
dc.identifier.issn | 0960-0779 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/160839 | |
dc.description.abstract | [EN] It seems that we are far from controlling COVID-19 pandemics, and, consequently, returning to a fully normal life. Until an effective vaccine is found, safety measures as the use of face masks, social distancing, washing hands regularly, etc., have to be taken. Also, the use of appropriate antivirals in order to alleviate the symptoms, to control the severity of the illness and to prevent the transmission, could be a good option that we study in this work. In this paper, we propose a computational random network model to study the transmission dynamics of COVID-19 in Spain. Once the model has been calibrated and validated, we use it to simulate several scenarios where effective antivirals are available. The results show how the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse of the health system. (c) 2020 Elsevier Ltd. All rights reserved. | es_ES |
dc.description.sponsorship | This work has been financed in part by ERC grant 695536-4D-PET. This work has been supported by the Spanish Ministerio de Economa, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P. This paper has been supported by the European Union through the Operational Program of the [European Regional Development Fund (ERDF)/European Social Fund (ESF)] of the Valencian Community 2014-2020. Files: GJIDI/2018/A/010 and GJIDI/2018/A/009. The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer JUDAC at Julich Supercomputing Centre (JSC), project transdyn_cov2, and the Partnership For Advanced Computing in Europe (PRACE-RI) support to mitigate the impact of COVID-19 pandemic. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Chaos, Solitons and Fractals | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | COVID-19 | es_ES |
dc.subject | Transmission dynamics | es_ES |
dc.subject | Computational random network model | es_ES |
dc.subject | Antiviral effectiveness | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.chaos.2020.110168 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/695536/EU/Innovative PET scanner for dynamic imaging/4D-PET/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F009/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F010/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario Mixto de Biología Molecular y Celular de Plantas - Institut Universitari Mixt de Biologia Molecular i Cel·lular de Plantes | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària | es_ES |
dc.description.bibliographicCitation | Benlloch Baviera, JM.; Cortés, J.; Martínez-Rodríguez, D.; San Julián-Garcés, R.; Villanueva Micó, RJ. (2020). Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach. Chaos, Solitons and Fractals. 140:1-9. https://doi.org/10.1016/j.chaos.2020.110168 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.chaos.2020.110168 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 9 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 140 | es_ES |
dc.identifier.pmid | 32836917 | es_ES |
dc.identifier.pmcid | PMC7434368 | es_ES |
dc.relation.pasarela | S\416361 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | European Research Council | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
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dc.subject.ods | 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades | es_ES |