dc.contributor.advisor | Khair, Nishat Zareen | |
dc.contributor.author | Hossain, Md.Murad | |
dc.date.accessioned | 2024-01-17T05:21:32Z | |
dc.date.available | 2024-01-17T05:21:32Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-03 | |
dc.identifier.other | ID 18346096 | |
dc.identifier.uri | http://hdl.handle.net/10361/22176 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2023. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 32-38). | |
dc.description.abstract | Dengue 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 outbreaks | en_US |
dc.description.statementofresponsibility | Md.Murad Hossain | |
dc.format.extent | 50 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac 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.subject | Dengue | en_US |
dc.subject | Mosquito-borne viral disease | en_US |
dc.subject | Aedes mosquito | en_US |
dc.subject | Prevention | en_US |
dc.subject | Mosquito traps | en_US |
dc.subject | Artificial Intelligence (AI) | en_US |
dc.subject | Machine learning(ML) | en_US |
dc.subject.lcsh | Dengue fever--Prevention. | |
dc.title | A review on the surveillance methods of the aedes aegypti mosquito for the prevention of dengue | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | School of Pharmacy, Brac University | |
dc.description.degree | B. Pharmacy | |