Logo do repositório

Applying a multi-strain dengue model to epidemics data

dc.contributor.authorde Araújo, Robert G.S.
dc.contributor.authorJorge, Daniel C.P. [UNESP]
dc.contributor.authorDorn, Rejane C.
dc.contributor.authorCruz-Pacheco, Gustavo
dc.contributor.authorEsteva, M. Lourdes M.
dc.contributor.authorPinho, Suani T.R.
dc.contributor.institutionUniversidade Federal da Bahia (UFBA)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidad Autónoma de México
dc.contributor.institutionInstituto Nacional de Ciência e Tecnologia - Sistemas Complexos
dc.date.accessioned2023-07-29T13:54:30Z
dc.date.available2023-07-29T13:54:30Z
dc.date.issued2023-06-01
dc.description.abstractDengue disease transmission is a complex vector-borne disease, mainly due to the co-circulation of four serotypes of the virus. Mathematical models have proved to be a useful tool to understand the complexity of this disease. In this work, we extend the model studied by Esteva et al., 2003, originally proposed for two serotypes, to four circulating serotypes. Using epidemic data of dengue fever in Iquitos (Peru) and San Juan (Puerto Rico), we estimate numerically the co-circulation parameter values for selected outbreaks using a bootstrap method, and we also obtained the Basic Reproduction Number, R0, for each serotype, using both analytical calculations and numerical simulations. Our results indicate that the impact of co-circulation of serotypes in population dynamics of dengue infection is such that there is a reduced effect from DENV-3 to DENV-4 in comparison to no-cross effect for epidemics in Iquitos. Concerning San Juan epidemics, also comparing to no-cross effect, we also observed a reduced effect from the predominant serotype DENV-3 to both DENV-2 and DENV-1 epidemics neglecting the very small number of cases of DENV-4.en
dc.description.affiliationInstituto de Física Universidade Federal da Bahia
dc.description.affiliationInstituto de Física Teórica Universidade Estadual Paulista
dc.description.affiliationInstituto de Investigaciones en Matemáticas Aplicadas y en Sistemas Universidad Autónoma de México
dc.description.affiliationFacultad de Ciencias Universidad Autónoma de México
dc.description.affiliationInstituto Nacional de Ciência e Tecnologia - Sistemas Complexos
dc.description.affiliationUnespInstituto de Física Teórica Universidade Estadual Paulista
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado da Bahia
dc.description.sponsorshipIdFAPESP: 2020/15643-8
dc.description.sponsorshipIdFundação de Amparo à Pesquisa do Estado da Bahia: INT0002/2016
dc.identifierhttp://dx.doi.org/10.1016/j.mbs.2023.109013
dc.identifier.citationMathematical Biosciences, v. 360.
dc.identifier.doi10.1016/j.mbs.2023.109013
dc.identifier.issn1879-3134
dc.identifier.issn0025-5564
dc.identifier.scopus2-s2.0-85159081374
dc.identifier.urihttp://hdl.handle.net/11449/248814
dc.language.isoeng
dc.relation.ispartofMathematical Biosciences
dc.sourceScopus
dc.subjectEpidemics data
dc.subjectMulti-strain dengue modeling
dc.subjectNumerical simulations
dc.subjectReproduction number
dc.titleApplying a multi-strain dengue model to epidemics dataen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0003-1404-3485 0000-0003-1404-3485[6]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulopt

Arquivos