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COVID-19 infection and risk analysis: a short introduction

dc.contributor.authorTeodoro, M. Filomena
dc.contributor.authorOliveira, Teresa
dc.contributor.authorTaero, Élio
dc.date.accessioned2024-02-01T11:26:10Z
dc.date.available2024-02-01T11:26:10Z
dc.date.issued2023-08-14
dc.description.abstractThis work is part of a study about COVID-19 pandemic in Mozambique. Here we reproduce the first part of such study where a general introduction about the background and motivational aspects of COVID-19 in the world is made. Also, the relevance of mathematical and statistical modeling, the concepts of risk, risk analysis and spatial epidemiology are detailed. An introductory briefing on risk measures in epidemiology is performed. In the present work, we deal with risk assessment in epidemiology, we address aspects such as uncertainty and variability, types of risk assessment and its steps, methods, and relevant conditions for the quality of risk assessment. At the moment, the considered data set is still incomplete, only preliminary estimated models and preliminary results were obtained. A continuation of this manuscript will illustrate the models estimated and applied to the modeling of infectious diseases, presenting those with a mathematical and statistical approach to COVID-19 infection. Also, we will present the mapping of diseases. The preliminary results obtained with the provisional data set agree with similar performed studies.pt_PT
dc.description.sponsorshipThis work was supported by Portuguese funds through the Center of Naval Research (CINAV), Portuguese Naval Academy, Portugal and The Portuguese Foundation for Science and Technology (FCT), through the Center for Computational and Stochastic Mathematics (CEMAT), University of Lisbon, Portugal, project UID/Multi/04621/2019. Also, this research was partially funded by FCT—Fundação para a Ciência e a Tecnologia under the project— UIBD/00006/2020”pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTeodoro MF, Oliveira TA, Taero E. COVID-19 infection and risk analysis: a short introduction. Biom Biostat Int J. 2023;12(4):121‒125. DOI: 10.15406/bbij.2023.12.00395pt_PT
dc.identifier.doi10.15406/bbij.2023.12.00395pt_PT
dc.identifier.eissn2378-315X
dc.identifier.eissn2378-315X
dc.identifier.urihttp://hdl.handle.net/10400.2/15624
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMedCravept_PT
dc.relationCenter for Computational and Stochastic Mathematics
dc.relation.publisherversionhttps://medcraveonline.com/BBIJ/BBIJ-12-00395.pdfpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectCOVID-19pt_PT
dc.subjectRisk analysispt_PT
dc.subjectSpatial epidemiologypt_PT
dc.titleCOVID-19 infection and risk analysis: a short introductionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter for Computational and Stochastic Mathematics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMulti%2F04621%2F2019/PT
oaire.citation.endPage125pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage121pt_PT
oaire.citation.titleBiometrics & Biostatistics International Journalpt_PT
oaire.citation.volume12pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAlves Teodoro
person.familyNameOliveira
person.givenNameMaria Filomena
person.givenNameTeresa Azinheira
person.identifier1155497
person.identifier.ciencia-id1412-1F70-A634
person.identifier.ciencia-id8814-A54B-12DE
person.identifier.orcid0000-0002-7944-0134
person.identifier.orcid0000-0003-3283-9946
person.identifier.ridJ-3077-2019
person.identifier.scopus-author-id54403540300
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication59d954cd-0988-4109-bbb6-c0b2805b2a32
relation.isAuthorOfPublication82b3cd70-88cc-4d31-b4b0-4705f8496c67
relation.isAuthorOfPublication.latestForDiscovery82b3cd70-88cc-4d31-b4b0-4705f8496c67
relation.isProjectOfPublication6cbeb87b-7161-4400-8a36-ab654bd50286
relation.isProjectOfPublication.latestForDiscovery6cbeb87b-7161-4400-8a36-ab654bd50286

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