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Author: search.filters.author.Sungchasit, Rattiya

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    Mathematical modeling and stability of SARS-CoV-2 transmission dynamics among domestic tourists in Thailand
    (2025-02-01)
    Sungchasit, Rattiya
    ;
    Pongsumpun, Puntani
    The defined epidemiological model system explaining the spread of infectious diseases characterized with SARS-CoV-2 is analysed. The resulting SEIQR model is analysed in a closed system. It considers the basic reproductive value, the equilibrium point, local subclinical stability of the disease-free equilibrium point and local subclinical stability of the endemic equilibrium point. This is examined and the asymptotic dynamics of the appropriate model system are investigated. Further, a sensitivity analysis supplemented by simulations is prepared in advance to impose how changes in parameters involve the dynamic behaviours of the model.
      3
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    Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19
    (2024-12-01)
    Sungchasit, Rattiya
    ;
    Tang, I. Ming
    ;
    Pongsumpun, Puntani
    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.
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    Mathematical Modeling: Global Stability Analysis of Super Spreading Transmission of Respiratory Syncytial Virus (RSV) Disease
    (2022-07-01)
    Sungchasit, Rattiya
    ;
    Tang, I. Ming
    ;
    Pongsumpun, Puntani
    In this paper, a model for the transmission of respiratory syncytial virus (RSV) in a constant human population in which there exist super spreading infected individuals (who infect many people during a single encounter) is considered. It has been observed in the epidemiological data for the diseases caused by this virus that there are cases where some individuals are super-spreaders of the virus. We formulate a simply SEI<inf>r</inf> I<inf>s</inf> R (susceptible–exposed–regular infected–super-spreading infected–recovered) mathematical model to describe the dynamics of the transmission of this disease. The proposed model is analyzed using the standard stability method by using Routh-Hurwitz criteria. We obtain the basic reproductive number (R<inf>0</inf>) using the next generation method. We establish that when R<inf>0</inf> < 1, the disease-free state is locally asymptotically stable and the disease endemic state is unstable. The reverse is true when R<inf>0</inf> > 1, the disease endemic state becomes the locally asymptotically stable state and the disease-free state becomes unstable. It is also established that the two equilibrium states are globally asymptotically stable. The numerical simulations show how the dynamics of the disease change as values of the parameters in the SEI<inf>r</inf> I<inf>s</inf> R are varied.
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    Mathematical Model of Dengue Virus with Primary and Secondary Infection
    (2019-05-01)
    Sungchasit, Rattiya
    ;
    Pongsumpun, Puntani
    In this study, we analyzed SEIR model for human and SEI model for mosquitoes. We considered the development of dengue infection from dengue fever (DF) to dengue hemorrhagic fever (DHF). The stability of the endemic equilibrium and the disease-free equilibrium states are incurred by Routh-Hurwitz criteria. Numerical simulations for the model are used to solve a system of differential equations. It showed that the local stability for disease free states and endemic states depended on the basic reproductive rate of the disease. The results of this study is recommended as an effective control measure for reducing the transmission of dengue disease.
      1
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    Environmental impact on the spread of dengue virus when two mosquito species circulate
    (2017-01-01)
    Sungchasit, Rattiya
    ;
    Pongsumpun, Puntani
    ;
    Ming Tang, I.
    We study the environmental impact on the dengue fever epidemic when two species of mosquitoes namely the Aedes aegypti and Aedes albopictus circulate. The infected populations of the humans and of mosquito species are each divided into two groups, the being infected but not infectious and the other infected and infectious (I). A SEIR model and SEI model are developed for the human and the two mosquito populations, respectively. The dynamical behaviors of the three populations are obtained by simulating the behaviors by numerically solving the differential equations which describe the models. Changes in the trajectories when the values of the environment dependent parameters are changed reveal the influence of the environment on the spread of the dengue virus. Often the values of the parameters in the two SEI models will depend on how a particular mosquito specie interacts with the environment and so the values of the parameters will be different in the two SEI models. This makes possible that the basic production numbers of the two species (S<inf>aegypti</inf> and S<inf>albopictus</inf>) will be different giving different S<inf>i</inf>‘s which give the following combinations (S<inf>aegypti</inf> > 1, S<inf>albopictus</inf> > 1), (S<inf>aegypti</inf> > 1, S<inf>albopictus</inf> < 1), (S<inf>aegypti</inf> < 1, S<inf>albopictus</inf> > 1) and (S<inf>aegypti</inf> < 1, S<inf>albopictus</inf> < 1). When the different conditions are satisfied, nature will have both species present, only one specie present or no species present.
      1