Year: 2025
Type: dissertation
Abstract: Existing dengue forecasting approaches in Malaysia are constrained by two main limitations: deterministic models typically assume a constant mosquito biting rate, neglecting its climate-driven variability, while statistical time series models are usually effective only for short-term forecasts. These constraints hinder the accurate prediction of outbreak dynamics and limit the utility of earlywarning systems. This study develops two integrated approaches: (i) coupled Susceptible-Infective for vector populations and Susceptible-Infective-Recovered for human populations (SI-SIR) and Autoregressive Integrated Moving Average with eXogenous variables (ARIMAX) model, and (ii) SISIR with Multiple Linear Regression and Long Short-Term Memory (MLR-LSTM) model.
Author: Lu, Xinyi
Institution: Universiti Sains Malaysia
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7160684209