Nowcasting and forecasting COVID-19 waves: the recursive and stochastic nature of transmission

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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorALBANI, V. V. L.
dc.contributor.authorALBANI, R. A. S.
dc.contributor.authorMASSAD, E.
dc.contributor.authorZUBELLI, J. P.
dc.date.accessioned2022-10-26T14:27:25Z
dc.date.available2022-10-26T14:27:25Z
dc.date.issued2022
dc.description.abstractWe propose a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of Sao Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.eng
dc.description.indexPubMedeng
dc.description.sponsorshipFundacao Butantan
dc.description.sponsorshipFundacao de Amparo a Pesquisa e Inovacao do Estado de Santa Catarina [01/2020, 00002847/2021]
dc.description.sponsorshipFundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ) [E-26/202.932/2019, E-26/202.933/2019]
dc.description.sponsorshipConselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [305544/2011-0]
dc.description.sponsorshipFundacao Butantan [01/2020]
dc.description.sponsorshipKhalifa University [FSU-2020-09]
dc.description.sponsorshipCNPq [307873/2013-7]
dc.description.sponsorshipFundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro [E-26/202.927/2017]
dc.identifier.citationROYAL SOCIETY OPEN SCIENCE, v.9, n.8, article ID 220489, 13p, 2022
dc.identifier.doi10.1098/rsos.220489
dc.identifier.issn2054-5703
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/49259
dc.language.isoeng
dc.publisherROYAL SOCeng
dc.relation.ispartofRoyal Society Open Science
dc.rightsopenAccesseng
dc.rights.holderCopyright ROYAL SOCeng
dc.subjectepidemiological modelseng
dc.subjectnowcastingeng
dc.subjectforecastingeng
dc.subjectCOVID-19eng
dc.subjectmodel calibrationeng
dc.subject.otherdynamicseng
dc.subject.otherepidemiceng
dc.subject.wosMultidisciplinary Scienceseng
dc.titleNowcasting and forecasting COVID-19 waves: the recursive and stochastic nature of transmissioneng
dc.typearticleeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.affiliation.countryEmirados Árabes Unidos
hcfmusp.affiliation.countryisoae
hcfmusp.author.externalALBANI, V. V. L.:Univ Fed Santa Catarina, Dept Math, Florianopolis, Brazil
hcfmusp.author.externalALBANI, R. A. S.:Univ Estado Rio De Janeiro, Inst Politecn Rio de Janeiro, Nova Friburgo, Brazil
hcfmusp.author.externalZUBELLI, J. P.:Khalifa Univ, Math Dept, Abu Dhabi, U Arab Emirates
hcfmusp.citation.scopus5
hcfmusp.contributor.author-fmusphcEDUARDO MASSAD
hcfmusp.description.articlenumber220489
hcfmusp.description.issue8
hcfmusp.description.volume9
hcfmusp.origemWOS
hcfmusp.origem.pubmed36016918
hcfmusp.origem.scopus2-s2.0-85137725965
hcfmusp.origem.wosWOS:000844307900006
hcfmusp.publisher.cityLONDONeng
hcfmusp.publisher.countryENGLANDeng
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Artigos e Materiais de Revistas Científicas - FM/MLS
Artigos e Materiais de Revistas Científicas - COVID-19
Artigos e Materiais de Revistas Científicas - LIM/01
Artigos e Materiais de Revistas Científicas - ODS/03