Muhammad Fahmi, Ahmad Zuber and Norhayati, Rosli and Noryanti, Muhammad (2024) Estimation of the Epidemiological Parameter for the COVID-19 Outbreak. In: AIP Conference Proceedings. ICOAIMS 2022: 3nd International Conference On Applied & Industrial Mathematics And Statistics 2022 , 24 - 26 August 2022 , Virtual, Online. pp. 1-11., 2895 (1). ISSN 0094-243X (Published)
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Abstract
The COVID-19 pandemic has affected worldwide with unprecedented catastrophes. Susceptible-Infected-Recovered-Death (SIRD) model is a well-known mathematical model to replicate the illness epidemic. Estimation of the epidemiological parameters of the SIRD model is crucial for understanding the virus's transmission and effect of the virus, thus, helping in making informed decisions about the required interventions. In this study, we propose a Metropolis-Hastings algorithm of the Markov Chain Monte Carlo (MCMC) method to estimate the epidemiological parameters of infectious rate, fatality rate, recovery rate, and reproduction numbers. An analysis is performed to investigate how the parameter changes throughout the lifespan of the pandemic. Numerical results show that the Metropolis-Hastings algorithm can adequately estimate the parameters of the COVID-19 pandemic, providing valuable insights into the spread of the virus and the changes in the pandemic behavior over time.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | epidemiological parameter; COVID-19; Markov Chain Monte Carlo; outbreak |
| Subjects: | Q Science > QA Mathematics |
| Faculty/Division: | Center for Mathematical Science Institute of Postgraduate Studies Centre of Excellence for Artificial Intelligence & Data Science |
| Depositing User: | Dr. Norhayati Rosli |
| Date Deposited: | 15 Aug 2024 00:18 |
| Last Modified: | 15 Aug 2024 00:18 |
| URI: | http://umpir.ump.edu.my/id/eprint/42344 |
| Download Statistic: | View Download Statistics |
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