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Fractional insights into Zika virus transmission: Exploring preventive measures from a dynamical perspective

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dc.citedby4
dc.contributor.authorJan R.en_US
dc.contributor.authorRazak N.N.A.en_US
dc.contributor.authorBoulaaras S.en_US
dc.contributor.authorRehman Z.U.en_US
dc.contributor.authorid57205596279en_US
dc.contributor.authorid37059587300en_US
dc.contributor.authorid36994353700en_US
dc.contributor.authorid58095489000en_US
dc.date.accessioned2024-10-14T03:19:34Z
dc.date.available2024-10-14T03:19:34Z
dc.date.issued2023
dc.description.abstractMathematical models for infectious diseases can help researchers, public health officials, and policymakers to predict the course of an outbreak. We formulate an epidemic model for the transmission dynamics of Zika infection with carriers to understand the intricate progression route of the infection. In our study, we focused on the visualization of the transmission patterns of the Zika with asymptomatic carriers, using fractional calculus. For the validity of the model, we have shown that the solutions of the system are positive and bounded. Moreover, we conduct a qualitative analysis and examine the dynamical behavior of Zika dynamics. The existence and uniqueness of the solution of the system have been proved through analytic skills. We establish the necessary conditions to ensure the stability of the recommended system based on the Ulam�Hyers stability concept (UHS). Our research emphasizes the most critical factors, specifically the mosquito biting rate and the existence of asymptomatic carriers, in increasing the complexity of virus control efforts. Furthermore, we predict that the asymptomatic fraction has the ability to spread the infection to non-infected regions. Furthermore, treatment due to medication, the fractional parameter or memory index, and vaccination can serve as effective control measures in combating this viral infection. � 2023 the author(s), published by De Gruyter.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo20220352
dc.identifier.doi10.1515/nleng-2022-0352
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85185199461
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85185199461&doi=10.1515%2fnleng-2022-0352&partnerID=40&md5=808357b6c449324d8ac8ec532608eddb
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34406
dc.identifier.volume12
dc.publisherWalter de Gruyter GmbHen_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofGold Open Access
dc.sourceScopus
dc.sourcetitleNonlinear Engineering
dc.subjectdynamical behavior
dc.subjectfractional calculus
dc.subjectmathematical model
dc.subjectstability analysis
dc.subjectvaccination and treatment
dc.subjectZika virus infection
dc.subjectDisease control
dc.subjectDynamics
dc.subjectTransmissions
dc.subjectVaccines
dc.subjectDynamical behaviors
dc.subjectFractional calculus
dc.subjectInfectious disease
dc.subjectPolicy makers
dc.subjectPreventive measures
dc.subjectStability analyze
dc.subjectVaccination and treatment
dc.subjectVirus infection
dc.subjectVirus transmission
dc.subjectZika virus infection
dc.subjectViruses
dc.titleFractional insights into Zika virus transmission: Exploring preventive measures from a dynamical perspectiveen_US
dc.typeArticleen_US
dspace.entity.typePublication
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