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dc.contributor.authorCatalà Sabaté, Martí
dc.contributor.authorCardona Iglesias, Pere Joan
dc.contributor.authorPrats Soler, Clara
dc.contributor.authorAlonso Muñoz, Sergio
dc.contributor.authorÁlvarez Lacalle, Enrique
dc.contributor.authorMarchena Angos, Miquel
dc.contributor.authorConesa Ortega, David
dc.contributor.authorEchebarría Domínguez, Blas
dc.contributor.authorLópez Codina, Daniel
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Física Computacional i Aplicada
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física
dc.date.accessioned2021-06-28T05:54:42Z
dc.date.available2021-06-28T05:54:42Z
dc.date.issued2021-06-14
dc.identifier.citationCatalà, M. [et al.]. Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries. 2021.
dc.identifier.urihttp://hdl.handle.net/2117/347919
dc.description.abstractThe present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the EU countries, and to be able to foresee the situation in the next coming days. We provide some figures and tables with several indexes and indicators as well as an Analysissection that discusses a specific topic related with the pandemic. As for the predictions, we employ an empirical model, verified with the evolution of the number of confirmed cases in previous countries where the epidemic is close to conclude, including all provinces of China. The model does not pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of control measures made in each state and a short-term prediction of trends. Note, however, that the effects of the measures’ control that start on a given day are not observed until approximately 7-14 days later. We show an individual report with 7 graphs and a summary table with the main indicators for different countries and regions. We are adjusting the model to countries and regions with at least 4 days with more than 100 confirmed cases and a current load over 200 cases.
dc.description.sponsorshipThese reports are funded by the European Commission (DG CONNECT, LC-01485746) PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia, Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00
dc.format.extent68 p.
dc.language.isoeng
dc.relation.ispartofDaily report; 243
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut
dc.subject.lcshCoronaviruses
dc.subject.lcshCOVID-19 (Disease)
dc.subject.lcshDiseases -- Mathematical models
dc.subject.lcshPandemics -- Prevention and control
dc.subject.lcshSARS (Disease)
dc.subject.otherCovid-19
dc.subject.otherPandèmies -- Predicció
dc.titleAnalysis and prediction of COVID-19 for EU-EFTA-UK and other countries
dc.typeExternal research report
dc.subject.lemacCOVID-19 (Malaltia)
dc.subject.lemacEpidèmies -- Predicció
dc.subject.lemacEpidemiologia -- Model matemàtics
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOCOM-SC - Grup de Biologia Computacional i Sistemes Complexos
dc.relation.publisherversionhttps://biocomsc.upc.edu/en/covid-19/daily-report
dc.rights.accessOpen Access
local.identifier.drac31862183
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/DGCONNECT/LC-01485746
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095456-B-I00/ES/COMPUTATIONAL MODELLING OF BIOPHYSICAL PROCESSES AT MULTIPLE SCALES/
dc.relation.projectidinfo:eu-repo/grantAgreement/SPAIN/LCF/PR/GN17/50300003
local.citation.authorCatalà, M.; Cardona, P.J.; Prats, C.; Alonso, S.; Alvarez-Lacalle, E.; Marchena, M.; Conesa, D.; Echebarria, B.; Lopez, D.


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