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dc.contributor.advisorKhair, Nishat Zareen
dc.contributor.authorHossain, Md.Murad
dc.date.accessioned2024-01-17T05:21:32Z
dc.date.available2024-01-17T05:21:32Z
dc.date.copyright2023
dc.date.issued2023-03
dc.identifier.otherID 18346096
dc.identifier.urihttp://hdl.handle.net/10361/22176
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2023.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 32-38).
dc.description.abstractDengue fever is a significant public health concern worldwide. It is a vector-borne disease caused by the dengue virus and transmitted to humans through the bites of infected Aedes mosquitoes. There is currently no specific treatment or vaccine for dengue fever, and prevention remains the most effective strategy for controlling the disease. The review aims to provide a comprehensive overview of the various prevention methods available for detecting Aedes aegypti mosquito. In this review, various surveillance techniques were analyzed for each method and evaluating their effectiveness, feasibility, and sustainability in various settings. The review also explores the challenges and opportunities for implementing these prevention strategies, particularly in Bangladesh. Larval Survey method might be one of the most effective techniques for Bangladesh for its case of work, feasibility and cost effectiveness but it is time consuming. For this reason, In Bangladesh, the implementation of artificial intelligence and machine learning algorithms in dengue surveillance will be a promising development that could provide faster and more accurate information on outbreaksen_US
dc.description.statementofresponsibilityMd.Murad Hossain
dc.format.extent50 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectDengueen_US
dc.subjectMosquito-borne viral diseaseen_US
dc.subjectAedes mosquitoen_US
dc.subjectPreventionen_US
dc.subjectMosquito trapsen_US
dc.subjectArtificial Intelligence (AI)en_US
dc.subjectMachine learning(ML)en_US
dc.subject.lcshDengue fever--Prevention.
dc.titleA review on the surveillance methods of the aedes aegypti mosquito for the prevention of dengueen_US
dc.typeThesisen_US
dc.contributor.departmentSchool of Pharmacy, Brac University
dc.description.degreeB. Pharmacy


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