Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.]
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 case...
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| Format: | Article |
| Language: | en |
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Universiti Teknologi MARA
2024
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| Online Access: | https://ir.uitm.edu.my/id/eprint/61898/1/61898.pdf https://ir.uitm.edu.my/id/eprint/61898/ |
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| author | Wan Mohamad, Wan Munirah Mohd Salleh, Syazwani Tengku Nadzion, Tengku Farah Busyra Mohd Riza, Abdul Latif Ashaari, Azmirul |
| author_facet | Wan Mohamad, Wan Munirah Mohd Salleh, Syazwani Tengku Nadzion, Tengku Farah Busyra Mohd Riza, Abdul Latif Ashaari, Azmirul |
| author_sort | Wan Mohamad, Wan Munirah |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. |
| format | Article |
| id | my.uitm.ir-61898 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2024 |
| publisher | Universiti Teknologi MARA |
| record_format | eprints |
| spelling | my.uitm.ir-618982024-08-17T23:28:49Z https://ir.uitm.edu.my/id/eprint/61898/ Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] mjoc Wan Mohamad, Wan Munirah Mohd Salleh, Syazwani Tengku Nadzion, Tengku Farah Busyra Mohd Riza, Abdul Latif Ashaari, Azmirul Mathematical statistics. Probabilities Public health. Hygiene. Preventive Medicine 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. Universiti Teknologi MARA 2024-04 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/61898/1/61898.pdf Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.]. (2024) Malaysian Journal of Computing (MJoC) <https://ir.uitm.edu.my/view/publication/Malaysian_Journal_of_Computing_=28MJoC=29/>, 9 (1): 1. pp. 1664-1672. ISSN 2600-8238 |
| spellingShingle | Mathematical statistics. Probabilities Public health. Hygiene. Preventive Medicine Wan Mohamad, Wan Munirah Mohd Salleh, Syazwani Tengku Nadzion, Tengku Farah Busyra Mohd Riza, Abdul Latif Ashaari, Azmirul Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title | Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title_full | Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title_fullStr | Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title_full_unstemmed | Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title_short | Modeling and predicting the dynamics of COVID-19 in Malaysia: a state-space approach / Wan Munirah Wan Mohamad ... [et al.] |
| title_sort | modeling and predicting the dynamics of covid-19 in malaysia: a state-space approach / wan munirah wan mohamad ... [et al.] |
| topic | Mathematical statistics. Probabilities Public health. Hygiene. Preventive Medicine |
| url | https://ir.uitm.edu.my/id/eprint/61898/1/61898.pdf https://ir.uitm.edu.my/id/eprint/61898/ |
| url_provider | http://ir.uitm.edu.my/ |