Ku, Yew Sheng (2023) Optimal control strategies for dengue transmission in Selangor, Malaysia. Final Year Project, UTAR.
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Abstract
Dengue is a mosquito-borne viral disease transmitted by Aedes aegypti mosquito. In Malaysia, dengue remains a public health threat. Based on previous dengue data and trends, Ministry of Health Malaysia identified a high increase in dengue cases every four to five years with the surges recorded in 2010, 2015 and 2019. The dengue cases are expected to increase again in 2024 or 2025, with the cases expected to be higher than that recorded in 2019 (130,101 cases). Hence, there is a need to identify effective dengue control strategies to prevent such increase in dengue cases in the future. This study aims to apply optimal control theory to determine the optimal control strategy for reducing dengue cases. For this purpose, a dengue model that links human SIR framework with mosquito ecology is formulated. This model is used to simulate the dengue transmission in Selangor, Malaysia, where suitable modelling data are available and where dengue is prevalent. Curve fitting of dengue data is then performed by using forward difference method to estimate important parameter value such as mosquito biting rate. Next, optimal control theory is applied to illustrate the effects of larvicide, insecticide and vaccination in reducing dengue cases. Seven scenarios, namely i) larvicide, ii) insecticide, iii) vaccination, iv) larvicide and insecticide, v) larvicide and vaccination, vi) insecticide and vaccination, vii) larvicide, insecticide, and vaccination are analyzed by means of numerical simulations in MATLAB. Based on the simulation results, a combination of larvicide, insecticide and vaccination is identified as the optimal control strategy in Selangor. The simulation results would provide insights on the optimal dengue control strategy in Selangor to assist decision makers in implementing dengue control strategies.
| Item Type: | Final Year Project / Dissertation / Thesis (Final Year Project) |
|---|---|
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences H Social Sciences > HT Communities. Classes. Races Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Science > Bachelor of Science (Honours) Statistical Computing and Operations Research |
| Depositing User: | ML Main Library |
| Date Deposited: | 18 Sep 2023 15:09 |
| Last Modified: | 18 Sep 2023 15:09 |
| URI: | http://eprints.utar.edu.my/id/eprint/5397 |
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