KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 8 of 8

Some of the metrics are blocked by your
consent settings
Mathematical modeling and optimal control analysis of classical and fractional order SVEITR model for TB infection disease in KPK Province of Pakistan
(2026-08-01)
Aalam, Balal
;
Pongsumpun, Puntani
In Pakistan, tuberculosis (TB) is still a significant public health concern. To address the socioeconomic and healthcare issues in the Khyber Pakhtunkhwa (KPK) province, this study offers a novel mathematical model of tuberculosis transmission. To the best of my knowledge, this is the first optimal control study of SVEITR-TB dynamics in KPK, Pakistan, incorporating both classical and fractional-order modeling frameworks to capture memory effects and complex disease behavior. Model validity is ensured through existence and uniqueness analysis, and the basic reproduction number is used to predict future disease dynamics. Model stability is assessed using Routh-Hurwitz criteria, Castillo–Chavez theorem, and Lyapunov functions for disease-free and endemic scenarios. In addition, backward bifurcation analysis is discussed near the bifurcation point. A sensitivity analysis is conducted to identify the key parameters that affect disease spread. The Nonstandard Finite Difference (NSFD) technique is used for numerical simulations of the deterministic model, and the fractional RK2 approach is used to simulate the fractional-order formulation, showing the disease can be controlled over time. The findings show that the fractional RK2 scheme successfully captures the memory effects present in the fractional-order dynamics and improves numerical accuracy. Furthermore, optimal control strategies, including enhanced vaccination and enhanced treatment, are assessed using Pontryagin’s maximum principle. Simulations using the RK4 forward-backward sweep method show that strategy A is the most reliable for controlling TB among the control measures, with a highest cumulative efficiency index. This demonstrates that strategy A is the most suitable control measure, providing the greatest reduction in disease burden. Thus, we conclude that stockholders and policymakers can use strategy A to control TB in the future.
Some of the metrics are blocked by your
consent settings
Fractional-order Modeling and Optimal Control of Dengue-Malaria Co-infection with Local and Advanced Treatment Strategies
(2026-01-01)
Pongsumpun, Puntipa
;
Ud Din, Rahim
;
Ullah, Atta
;
Pongsumpun, Puntani
Abstract: This study presents a novel fractional-order co-infection model describing the joint transmission dynamics of dengue and malaria using the generalized fractional derivative. The total human population is divided into eight epidemiological compartments that account for single infections, co-infection, treatment stages, and recovery. The proposed framework incorporates memory effects and nonlocal behavior, offering a more realistic representation of disease progression compared to classical integer-order models. Local and advanced treatment strategies are introduced based on infection severity, allowing targeted intervention for both mild and co-infected cases. The fundamental mathematical properties of the model, including positivity, boundedness, existence, and uniqueness of solutions, are rigorously established. The basic reproduction number is derived, and both local and global stability of the disease-free equilibrium are analyzed using suitable Lyapunov functions. A statistical sensitivity analysis is performed to identify key parameters influencing disease transmission. Furthermore, optimal control strategies are formulated to minimize co-infection prevalence while reducing treatment and implementation costs. Numerical simulations validate the theoretical findings and demonstrate that fractional-order dynamics provide deeper insights into long-term disease behavior. The results offer valuable guidance for policymakers in designing effective and cost-efficient strategies to control dengue and malaria co-infection. Graphic Abstract: (Figure presented.) The
Some of the metrics are blocked by your
consent settings
Optimal control and stability analysis of influenza transmission dynamics with quarantine interventions
(2025-08-01)
Lamwong, Jiraporn
;
Pongsumpun, Puntani
Seasonal flu results from infection by influenza viruses of either type A or B. Common symptoms include a rapid rise in body temperature, coughing, headaches, muscle and joint aches, throat discomfort, and nasal congestion. This research addresses the need for effective modeling and control of seasonal influenza, which remains a significant health concern globally due to its high transmissibility and potential to cause severe illness. Current approaches to understanding and managing influenza focus on various mathematical models exploring transmission dynamics and control strategies. This study contributes to the field by introducing a Susceptible-Exposed-Infectious-Quarantined-Recovered (SEIQR) model, which uniquely incorporates quarantine as a key intervention, reflecting realistic disease management practices. The methodology utilized involves formulating the SEIQR model to simulate the transmission of influenza and analyze its stability. The stability of both the disease-free and endemic equilibrium points is examined using Lyapunov functions and LaSalle’s invariance principle, ensuring the rigorous validation of the model's behavior. To enhance the model's utility, optimal control theory is applied, incorporating control variables such as vaccination, social measures, and treatment for both infected and quarantined populations. The application of Pontryagin’s Maximum Principle enables the derivation of optimal control strategies that balance epidemiological impact with cost-effectiveness. Numerical simulations provide key results that demonstrate the efficacy of control interventions. Specifically, scenarios implementing control measures reveal a significant reduction in the peak and overall spread of infections. The analysis of different control policies indicates that a combined approach—employing both vaccination and social distancing—is the most effective for curbing the spread of influenza. Sensitivity analysis further underscores the critical influence of parameters like quarantine rate and infection rate on the basic reproduction number, R<inf>0</inf>, reinforcing the importance of targeted interventions. The study’s findings emphasize the importance of timely and multifaceted control measures for achieving the global asymptotic stability of the influenza model. The implications suggest that integrated strategies, particularly those involving vaccination and social controls, are crucial for public health policy to manage and prevent influenza outbreaks effectively. Future research could expand the model to include demographic variations, virus mutations, and interactions with other respiratory diseases, enhancing its predictive power and practical relevance for disease control.
Some of the metrics are blocked by your
consent settings
Mathematical modeling and optimal control of the hand foot mouth disease affected by regional residency in Thailand
(2021-11-01)
Wongvanich, Napasool
;
Tang, I. Ming
;
Dubois, Marc Antoine
;
Pongsumpun, Puntani
Hand, foot and mouth disease (HFMD) is a virulent disease most commonly found in East and Southeast Asia. Symptoms include ulcers or sores, inside or around the mouth. In this research, we formulate the dynamic model of HFMD by using the SEIQR model. We separated the infection episodes where there is a higher outbreak and a lower outbreak of the disease associated with regional residency, with the higher level of outbreak occurring in the urban region, and a lower outbreak level occurring in the rural region. We developed two different optimal control programs for the types of outbreaks. Optimal Control Policy 1 (OPC1) is limited to the use of treatment only, whereas Optimal Control Policy 2 (OPC2) includes vaccination along with the treatment. The Pontryagin’s maximum principle is used to establish the necessary and optimal conditions for the two policies. Numerical solutions are presented along with numerical sensitivity analyses of the required control efforts needed as the control parameters are changed. Results show that the time t<inf>max</inf> required for the optimal control effort to stay at the maximum amount u<inf>max</inf> exhibits an intrinsic logarithmic relationship with respect to the control parameters.
Some of the metrics are blocked by your
consent settings
Local and global stability analysis of dengue disease with vaccination and optimal control
(2021-10-01)
Chamnan, Anusit
;
Pongsumpun, Puntani
;
Tang, I. Ming
;
Wongvanich, Napasool
Dengue fever is a disease that has spread all over the world, including Thailand. Dengue is caused by a virus and there are four distinct serotypes of the virus that cause dengue DENV‐1, DENV‐2, DENV‐3, and DENV‐4. The dengue viruses are transmitted by two species of the Aedes mosquitoes, the Aedes aegypti, and the Aedes albopictus. Currently, the dengue vaccine used in Thailand is chimeric yellow tetravalent dengue (CYD‐TDV). This research presents optimal control which studies the vaccination only in individuals with a documented past dengue infection (seropositive), regardless of the serotypes of infection causing the initial infection by the disease. The analysis of dengue transmission model is used to establish the local asymptotically stabilities. The property of symmetry in the Lyapunov function an import role in achieving this global asymptotically stabilities. The optimal control systems are shown in numerical solutions and conclusions. The result shows that the control resulted in a significant reduction in the number of infected humans and infected vectors.
Some of the metrics are blocked by your
consent settings
Optimal control of dengue transmission with vaccination
(2021-08-01)
Chamnan, Anusit
;
Pongsumpun, Puntani
;
Tang, I. Ming
;
Wongvanich, Napasool
Dengue disease is caused by four serotypes of the dengue virus: DEN-1, DEN-2, DEN-3, and DEN-4. The chimeric yellow fever dengue tetravalent dengue vaccine (CYD-TDV) is a vaccine currently used in Thailand. This research investigates what the optimal control is when only individuals having documented past dengue infection history are vaccinated. This is the present practice in Thailand and is the latest recommendation of the WHO. The model used is the Susceptible-Infected-Recovered (SIR) model in series configuration for the human population and the Susceptible-Infected (SI) model for the vector population. Both dynamical models for the two populations were recast as optimal control problems with two optimal control parameters. The analysis showed that the equilibrium states were locally asymptotically stable. The numerical solution of the control systems and conclusions are presented.
Some of the metrics are blocked by your
consent settings
Optimal control of the dengue dynamical transmission with vertical transmission
(2019-12-01)
Pongsumpun, Puntani
;
Tang, I. Ming
;
Wongvanich, Napasool
Dengue disease is found in tropical and subtropical regions around the world. Dengue virus is the cause of dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. It consists of 4 serotypes: DEN-1, DEN-2, DEN-3, and DEN-4. There are two modes of transmission for dengue virus in mosquito: horizontal transmission and vertical transmission. The mosquito can be infected when it bites an infectious human by horizontal transmission, but there can also be vertical transmission through sexual contact with an infected mosquito. This research presents a control mechanism based on our previously developed dengue model with vertical transmission. The two policies, namely vaccination and insecticide administration (Policy 1) and isolation and insecticide administration (Policy 2) are considered. The use of Pontryargin’s maximum principle allowed necessary and optimality conditions, thus facilitating the optimal control to be developed. Numerical solutions of our control systems and the conclusions of our two policies are presented.
Some of the metrics are blocked by your
consent settings
Optimal control-based integral servo controller for an overhead crane system
(2015-01-01)
Pannil, Pittaya
;
Kaeojaikla, Phattarapong
;
Trisuwannawat, Thanit
This paper presents an integral servo controller design in order to eliminate the steady-state tracking error of an overhead crane system according to the servo problem. The design technique uses optimal control approach which encourages to achieve the better performance of the controller for overhead crane system. The simulation results show that the designed integral servo controller can eliminate the errors and reduce the settling time of the responses according to the weight for the integral time. How to select the weights for control is also suggested.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results