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Modelling the COVID-19 pandemic: variants and vaccines

dc.conference.date5-9 Jun 2022
dc.conference.placeOslo
dc.conference.title8th European Congress on Computational Methods in Applied Sciences and Engineering
dc.contributor.authorKubik Gladys, Alicia Barbara
dc.contributor.authorFerrández, Miriam R.
dc.contributor.authorVela Pérez, María
dc.contributor.authorIvorra, Benjamín Pierre Paul
dc.contributor.authorRamos Del Olmo, Ángel Manuel
dc.date.accessioned2024-04-10T12:30:10Z
dc.date.available2024-04-10T12:30:10Z
dc.date.issued2022-11-24
dc.description.abstractOn December 2019, a new virus emerged and started to spread through the Chinese city of Wuhan, the SARS-CoV-2. On 30 January 2020, the WHO declared the COVID-19as a public health emergency of international concern. On 11 March 2020, it is declared the first pandemic caused by a coronavirus. Since then, lifestyle has been notably conditioned to this fact, and researchers have been working quickly and hard to improve the understanding of this unknown disease and shed some light on this situation. This last year, new SARS-CoV-2 variants have emerged and most of the European population is fully vaccinated against COVID-19. Here, we present a θ-SIR model that has been tested with real data during this pandemic. It is an improvement of previous models (see [1, 2]) -now we incorporate new compartments to consider vaccination and divide each infectious compartment depending on the amount of different SARS-CoV-2 variants, to finally apply it to the territory of Italy (see [3]). Compartmental models are very used models to treat epidemics mathematically. One of the main advantages of these models is the fact that its parameters are directly related to real biological processes, and hence they may give intuition about the functioning of some unknown processes (for example, the real magnitude of the pandemic studying the evolution of the asymptomatic cases, or estimations of the number of beds needed). The main result of the article presented here (i.e., [3]) is the definition of an effective reproduction number Rt for each variant – this led us to foresee the high probability of the variant Alpha generating a third wave in Italy, which finally happened.
dc.description.departmentDepto. de Análisis Matemático y Matemática Aplicada
dc.description.departmentDepto. de Economía Financiera y Actuarial y Estadística
dc.description.facultyInstituto de Matemática Interdisciplinar (IMI)
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación
dc.description.statuspub
dc.identifier.doi10.23967/eccomas.2022.184
dc.identifier.officialurlhttps://www.scipedia.com/public/Kubik_et_al_2022a
dc.identifier.urihttps://hdl.handle.net/20.500.14352/102960
dc.language.isoeng
dc.page.final12
dc.page.initial1
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106337GB-I00/ES/MODELIZACION, SIMULACION NUMERICA Y OPTIMIZACION PARA VARIOS PROBLEMAS DE INTERES GENERAL/
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject.keywordCOVID-19 vaccines
dc.subject.keywordθ-SIR type model
dc.subject.keywordSARS-CoV-2 variants
dc.subject.ucmOptimización matemática
dc.subject.unesco12 Matemáticas
dc.titleModelling the COVID-19 pandemic: variants and vaccines
dc.typeconference paper
dc.type.hasVersionVoR
dspace.entity.typePublication
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relation.isAuthorOfPublication6d5e1204-9b8a-40f4-b149-02d32e0bbed2
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relation.isAuthorOfPublication.latestForDiscovery581c3cdf-f1ce-41e0-ac1e-c32b110407b1

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