Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach
Fecha
Autores
Directores
Handle
https://riunet.upv.es/handle/10251/160839
Cita bibliográfica
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
Titulación
Resumen
[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.
Palabras clave
COVID-19, Transmission dynamics, Computational random network model, Antiviral effectiveness
ISSN
0960-0779
ISBN
Fuente
Chaos, Solitons and Fractals
DOI
10.1016/j.chaos.2020.110168
Versión del editor
https://doi.org/10.1016/j.chaos.2020.110168
dc.description.uri
Código de Proyecto
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/
info:eu-repo/grantAgreement/EC/H2020/695536/EU/Innovative PET scanner for dynamic imaging/4D-PET/
info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F009/
info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F010/
info:eu-repo/grantAgreement/EC/H2020/695536/EU/Innovative PET scanner for dynamic imaging/4D-PET/
info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F009/
info:eu-repo/grantAgreement/GVA//GJIDI%2F2018%2FA%2F010/
Agradecimientos
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.