Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19
Issued Date
2024-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-85204249080
Journal Title
Scientific Reports
Volume
14
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.14 No.1 (2024)
Suggested Citation
Sungchasit R., Tang I.M., Pongsumpun P. Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19. Scientific Reports Vol.14 No.1 (2024). doi:10.1038/s41598-024-71009-x Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/101344
Title
Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19
Author(s)
Corresponding Author(s)
Other Contributor(s)
Abstract
This study employs a mathematical model to analyze and forecast the severe outbreak of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), focusing on the socio-economic ramifications within the Thai population and among foreign tourists. Specifically, the model examines the impact of the disease on various population groups, including susceptible (S), exposed (E), infected (I), quarantined (Q), and recovered (R) individuals among tourists visiting the country. The stability theory of differential equations is utilized to validate the mathematical model. This involves assessing the stability of both the disease-free equilibrium and the endemic equilibrium using the basic reproduction number. Emphasis is placed on local stability, the positivity of solutions, and the invariant regions of solutions. Additionally, a sensitivity analysis of the model is conducted. The computation of the basic reproduction number (R0) reveals that the disease-free equilibrium is locally asymptotically stable when R0 is less than 1, whereas the endemic equilibrium is locally asymptotically stable when R0 exceeds 1. Notably, both equilibriums are globally asymptotically stable under the same conditions. Through numerical simulations, the study concludes that the outcome of COVID-19 is most sensitive to reductions in transmission rates. Furthermore, the sensitivity of the model to all parameters is thoroughly considered, informing strategies for disease control through various intervention measures.
