Changpuek, Thurdkwan

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Analysis of mathematical model for swine flu transmission by age group
(2013-02-01)
Changpuek, T.
;
Pongsumpun, P.
;
Tang, I. Ming
Effect of age group in the human population is considered for the transmission of swine flu. Susceptible-Exposed-Infected-Quarantined-Recovered (SEIQR) model is used for describing the transmission of this disease. From the swine flu data in Thailand, age of patients is influenced to the transmission of this disease. The human population is separated into three groups such as 1-10 years, 11-20 years, and more than 20 years, respectively. The transmission rates of the disease in all age groups are assumed to be different. Local stability analysis of this model is given. Four equilibrium states are found and the conditions for stability of these four equilibrium states are established. Numerical solutions are shown to confirm the analytical results. The bifurcation diagrams are shown. The basic reproductive number is found and the alternative way to control the disease is discussed. © 2013 Pushpa Publishing House.
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Global stability of the age structural transmission model for swine flu
(2013-09-01)
Changpuek, T.
;
Pongsumpun, P.
;
Tang, I. Ming
In this paper, we examine the global stability of swine flu transmission model incorporated the age structure of human population based on SEIQR (susceptible-exposed-infected-quarantined-recovered) model. The human population is divided into three groups such as 1-10 years, 11-20 years and more than 20 years, respectively. We obtain four equilibrium states and then construct Lyapunov functions with the conditions for global stability of these four equilibrium states. © 2013 Pushpa Publishing House, Allahabad, India.
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Analysis of swine flu network model
(2016-11-01)
Pongsumpun, P.
;
Changpuek, T.
In this paper, we propose a SEIQR network model incorporating the age structure of human population for swine flu to study an epidemic network distribution. The human population is divided into three groups such as 1-10 years, 11-20 years and more than 20 years, respectively. The SEIQR network model contains people and public places, we suppose that the people move to any public places by random process. The numerical simulation of the disease transmission is presented with assumptions that there is one exposed person and one infected person in each age group at the first day. The results show the time distribution of exposed, infected and quarantined human dealing with different situations.
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Changpuek, Thurdkwan

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