Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.]

• Main Authors: Wan Mohamad, Wan Munirah, Mohd Salleh, Syazwani, Tengku Nadzion, Tengku Farah Busyra, Mohd Riza, Abdul Latif, Ashaari, Azmirul
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA 2024
• Subjects: Mathematical statistics. Probabilities; Public health. Hygiene. Preventive Medicine
• Online Access: https://ir.uitm.edu.my/id/eprint/61898/1/61898.pdf; https://ir.uitm.edu.my/id/eprint/61898/

The emergence of COVID-19 in Malaysia in January 2020 marked the beginning of a significant public health challenge. Despite the transition to the endemic phase on April 1, 2022, the global impact of the virus remains substantial. This research aims to forecast the cumulative number of detected cases and deaths by employing a state-space model derived from the Susceptible-Infectious-Recovered (SIR) model, capturing the multi-wave dynamics of COVID-19. The modeling focuses on estimating the trends within the time interval spanning from week 1 to week 12, commencing in mid-June 2022. Real-time data sourced from the Ministry of Health in Malaysia serve as the basis for model development and validation, utilizing MATLAB and Simulink for simulation purposes. The findings of the simulation reveal a direct correlation between the number of detected cases and deaths, suggesting a positive relationship with the real-life situation. This mathematical representation contributes to a deeper understanding of the ongoing dynamics of COVID-19 and provides a tool for predicting future trends, aiding in public health planning and response efforts.