Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia
Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to si...
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| Format: | Article |
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Nature Publishing Group
2021
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| author | Ariffin, Muhammad Rezal Kamel Gopal, Kathiresan Krishnarajah, Isthrinayagy Che Ilias, Iszuanie Syafidza Adam, Mohd Bakri Arasan, Jayanthi Abd Rahman, Nur Haizum Mohd Dom, Nur Sumirah Mohammad Sham, Noraishah |
| author_facet | Ariffin, Muhammad Rezal Kamel Gopal, Kathiresan Krishnarajah, Isthrinayagy Che Ilias, Iszuanie Syafidza Adam, Mohd Bakri Arasan, Jayanthi Abd Rahman, Nur Haizum Mohd Dom, Nur Sumirah Mohammad Sham, Noraishah |
| author_sort | Ariffin, Muhammad Rezal Kamel |
| collection | UPM |
| description | Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia. |
| first_indexed | 2024-03-06T10:58:57Z |
| format | Article |
| id | upm.eprints-94101 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T10:58:57Z |
| publishDate | 2021 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | upm.eprints-941012023-03-29T02:06:43Z http://psasir.upm.edu.my/id/eprint/94101/ Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia Ariffin, Muhammad Rezal Kamel Gopal, Kathiresan Krishnarajah, Isthrinayagy Che Ilias, Iszuanie Syafidza Adam, Mohd Bakri Arasan, Jayanthi Abd Rahman, Nur Haizum Mohd Dom, Nur Sumirah Mohammad Sham, Noraishah Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia. Nature Publishing Group 2021-10-20 Article PeerReviewed Ariffin, Muhammad Rezal Kamel and Gopal, Kathiresan and Krishnarajah, Isthrinayagy and Che Ilias, Iszuanie Syafidza and Adam, Mohd Bakri and Arasan, Jayanthi and Abd Rahman, Nur Haizum and Mohd Dom, Nur Sumirah and Mohammad Sham, Noraishah (2021) Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia. Scientific Reports, 11. art. no. 20739. pp. 1-10. ISSN 2045-2322 https://www.nature.com/articles/s41598-021-99541-0 10.1038/s41598-021-99541-0 |
| spellingShingle | Ariffin, Muhammad Rezal Kamel Gopal, Kathiresan Krishnarajah, Isthrinayagy Che Ilias, Iszuanie Syafidza Adam, Mohd Bakri Arasan, Jayanthi Abd Rahman, Nur Haizum Mohd Dom, Nur Sumirah Mohammad Sham, Noraishah Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title | Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title_full | Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title_fullStr | Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title_full_unstemmed | Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title_short | Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia |
| title_sort | mathematical epidemiologic and simulation modelling of first wave covid 19 in malaysia |
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