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dc.contributor.authorGabriel Kuniyoshi, Maria Laura [UNESP]
dc.contributor.authorPio dos Santos, Fernando Luiz [UNESP]
dc.date.accessioned2018-12-11T17:13:06Z
dc.date.available2018-12-11T17:13:06Z
dc.date.issued2017-07-06
dc.identifierhttp://dx.doi.org/10.1186/s40409-017-0123-x
dc.identifier.citationJournal of Venomous Animals and Toxins Including Tropical Diseases, v. 23, n. 1, 2017.
dc.identifier.issn1678-9199
dc.identifier.issn1678-9180
dc.identifier.urihttp://hdl.handle.net/11449/174839
dc.description.abstractBackground: Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. Methods: Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. Results: Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. Conclusion: The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.en
dc.language.isoeng
dc.relation.ispartofJournal of Venomous Animals and Toxins Including Tropical Diseases
dc.sourceScopus
dc.subjectEpidemiology
dc.subjectInsecticides
dc.subjectNumerical simulation
dc.subjectODE system
dc.subjectPopulation genetics
dc.subjectTheoretical modelling
dc.subjectTropical diseases
dc.titleMathematical modelling of vector-borne diseases and insecticide resistance evolutionen
dc.typeArtigo
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationDepartment of Biostatistics Institute of Biosciences of Botucatu São Paulo State University (UNESP - Universidade Estadual Paulista), Dr.Irina Delanova Gemtchujnicov, Rubiao Junior, PO box 510
dc.description.affiliationUnespDepartment of Biostatistics Institute of Biosciences of Botucatu São Paulo State University (UNESP - Universidade Estadual Paulista), Dr.Irina Delanova Gemtchujnicov, Rubiao Junior, PO box 510
dc.identifier.doi10.1186/s40409-017-0123-x
dc.identifier.scieloS1678-91992017000100321
dc.rights.accessRightsAcesso aberto
dc.identifier.scopus2-s2.0-85021774948
dc.identifier.fileS1678-91992017000100321.pdf
dc.relation.ispartofsjr0,573
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