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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/60345
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dc.creatorArmando Gil Magalhães Nevespt_BR
dc.creatorGustavo Andres Guerrero Erasopt_BR
dc.date.accessioned2023-10-31T17:00:07Z-
dc.date.available2023-10-31T17:00:07Z-
dc.date.issued2020-
dc.citation.volume413pt_BR
dc.citation.spage1pt_BR
dc.citation.epage12pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.physd.2020.132693pt_BR
dc.identifier.issn1872-8022pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/60345-
dc.description.resumoThe presence of a large number of infected individuals with few or no symptoms is an important epidemiological difficulty and the main mathematical feature of COVID-19. The A-SIR model, i.e. a SIR (Susceptible–Infected–Removed) model with a compartment for infected individuals with no symptoms or few symptoms was proposed by Gaeta (2020). In this paper we investigate a slightly generalized version of the same model and propose a scheme for fitting the parameters of the model to real data using the time series only of the deceased individuals. The scheme is applied to the concrete cases of Lombardy, Italy and São Paulo state, Brazil, showing different aspects of the epidemic. In both cases we see strong evidence that the adoption of social distancing measures contributed to a slower increase in the number of deceased individuals when compared to the baseline of no reduction in the infection rate. Both for Lombardy and São Paulo we show that we may have good fits to the data up to the present, but with very large differences in the future behavior. The reasons behind such disparate outcomes are the uncertainty on the value of a key parameter, the probability that an infected individual is fully symptomatic, and on the intensity of the social distancing measures adopted. This conclusion enforces the necessity of trying to determine the real number of infected individuals in a population, symptomatic or asymptomatic.pt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE FÍSICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofPhysica D: Nonlinear Phenomena-
dc.rightsAcesso Abertopt_BR
dc.subjectCOVID-19pt_BR
dc.subjectEpidemicspt_BR
dc.subjectMathematical modelingpt_BR
dc.subjectSIR-type modelspt_BR
dc.subject.otherCOVID-19 (Doença)pt_BR
dc.subject.otherEpidemiaspt_BR
dc.subject.otherModelagem matemáticapt_BR
dc.titlePredicting the evolution of the COVID-19 epidemic with the A-SIR model: Lombardy, Italy and São Paulo state, Brazilpt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S0167278920303638pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-1602-6881pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-2671-8796pt_BR
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