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dc.contributor.authorBarrera, Antonio
dc.contributor.authorRomán Román, Patricia 
dc.contributor.authorSerrano Pérez, Juan José 
dc.contributor.authorTorres Ruiz, Francisco De Asís 
dc.date.accessioned2021-10-18T10:18:33Z
dc.date.available2021-10-18T10:18:33Z
dc.date.issued2021
dc.identifier.citationBarrera, A.; Román-Román, P.; Serrano-Pérez, J.J.; Torres-Ruiz, F. Two Multi-Sigmoidal Diffusion Models for the Study of the Evolution of the COVID-19 Pandemic. Mathematics 2021, 9, 2409. https://doi.org/ 10.3390/math9192409es_ES
dc.identifier.urihttp://hdl.handle.net/10481/70930
dc.description.abstractA proposal is made to employ stochastic models, based on diffusion processes, to represent the evolution of the SARS-CoV-2 virus pandemic. Specifically, two diffusion processes are proposed whose mean functions obey multi-sigmoidal Gompertz and Weibull-type patterns. Both are constructed by introducing polynomial functions in the ordinary differential equations that originate the classical Gompertz and Weibull curves. The estimation of the parameters is approached by maximum likelihood. Various associated problems are analyzed, such as the determination of initial solutions for the necessary numerical methods in practical cases, as well as Bayesian methods to determine the degree of the polynomial. Additionally, strategies are suggested to determine the best model to fit specific data. A practical case is developed from data originating from several Spanish regions during the first two waves of the COVID-19 pandemic. The determination of the inflection time instants, which correspond to the peaks of infection and deaths, is given special attention. To deal with this particular issue, point estimation as well as first-passage times have been considered.es_ES
dc.description.sponsorshipMinisterio de Economía, Industria y Competitividad, Spain, under Grant MTM2017-85568-Pes_ES
dc.description.sponsorshipFEDER, Consejería de Economía y Conocimiento de la Junta de Andalucía, Spain under Grant A-FQM-456-UGR18es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectCOVID-19es_ES
dc.subjectDiffusion processeses_ES
dc.subjectMulti-sigmoidal curveses_ES
dc.subjectInference on diffusion processeses_ES
dc.subjectFirst-passage timeses_ES
dc.titleTwo Multi-Sigmoidal Diffusion Models for the Study of the Evolution of the COVID-19 Pandemices_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/math9192409


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España