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Author: search.filters.author.Olumuyiwa James Peter

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    Mathematical model for control of tuberculosis epidemiology
    (Springer Science and Business Media LLC, 2022-04-22) Mayowa M. Ojo; Olumuyiwa James Peter; Emile Franc Doungmo Goufo; Hasan S. Panigoro; Festus Abiodun Oguntolu
    Tuberculosis is an infectious disease caused by bacteria that most commonly affects the lungs. Due to its high mortality, it remains a global health issue, and it is one of the leading causes of death in the majority of sub-Saharan African countries. We formulate a six-compartmental deterministic model to investigate the impact of vaccination on the dynamics of tuberculosis in a given population. The qualitative behaviors of the presented model were examined, and the respective threshold quantity was obtained. The tuberculosis-free equilibrium of the system is said to be locally asymptotically stable when the effective reproduction number and unstable otherwise. Furthermore, we examined the stability of the endemic equilibrium, and the conditions for the existence of backward bifurcation are discussed. A numerical simulation was performed to demonstrate and support the theoretical findings. The result shows that reducing the effective contact with an infected person and enhancing the rate of vaccinating susceptible individuals with high vaccine efficacy will reduce the burden of tuberculosis in the population.
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    Mathematical model and analysis of the soil-transmitted helminth infections with optimal control
    (Springer Science and Business Media LLC, 2024-02) Festus Abiodun Oguntolu; Olumuyiwa James Peter; Abubakar Yusuf; B. I. Omede; G. Bolarin; T. A. Ayoola
    Soil-transmitted helminth diseases are highly prevalent in impoverished regions and pose a significant health burden on the global population. These diseases are primarily transmitted through the contamination of soil with human faces containing parasite eggs. This study presents a novel deterministic mathematical model to comprehensively investigate the dynamics of helminth infection transmission through the soil. The mathematical model exhibits two equilibrium points: the diseases-free equilibrium point (DFE) and the endemic equilibrium point (EEP). The DFE is proven to be locally and globally asymptotically stable when the basic reproduction number is less than one, indicating the potential for disease eradication. Conversely, the EEP is locally asymptotically stable when the basic reproduction number exceeds unity, representing a persistent endemic state. To explore effective intervention strategies for controlling the spread of these infections, optimal control theory is applied. The study incorporates two time-varying control variables derived from sensitivity analysis: the rate of hygiene consciousness in the susceptible class and the rate of hygiene consciousness in the infectious class. Numerical simulations demonstrate that implementing optimal control strategies can successfully curb and mitigate soil-transmitted helminth infections. Overall, this research highlights the importance of proactive and targeted interventions, emphasizing the significance of hygiene education and awareness campaigns. By implementing optimal control measures based on the proposed strategies, the burden of soil-transmitted helminth diseases can be significantly reduced, improving public health in affected regions.
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    Mathematical model for the control of lymphatic filariasis transmission dynamics
    (SCIK Publishing Corporation, 2021-02-23) Festus Abiodun Oguntolu; Gbolahan Bolarin; Olumuyiwa James Peter; Abdullah Idris Enagi; Kayode Oshinubi
    In this paper, a mathematical model for the transmission dynamics of lymphatic filariasis is presented by incorporating the infected without symptom, the infected with symptom and treatment compartments. The model is shown to have two equilibrium states: the disease-free equilibrium (DFE) and the endemic equilibrium states. An explicit formula for the effective reproduction number was obtained in terms of the demographic and epidemiological parameters of the model. Using the method of linearization, the disease-free equilibrium state was found to be locally asymptotically stable if the basic reproduction number is less than unity. By constructing a suitable Lyapunov function, the disease-free equilibrium state was found to be globally asymptotically stable. This means that lymphatic filariasis could be put under control in a population when the effective reproduction number is less than one. The endemic equilibrium state was found to be locally asymptotically stable. By constructing yet another Lyapunov function, the endemic equilibrium state was found to be globally asymptotically stable under certain conditions. Sensitivity analysis was carried out on the effective reproduction number, the most sensitive parameters were the treatment rate of human population and the infected rate of human population. Results from the simulation carried out showed that treatment level coverage of human population should target a success rate of 75% for LF to be under control in the population.
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    Enhanced Cuckoo Intelligence Search Algorithm
    (Research India Publications, 2021-06-30) Ibukun Isaac Aina; Olumuyiwa James Peter; Abayomi Ayotunde Ayoade; Festus Abiodun Oguntolu; Matthew Olanrewaju Oluwayemi
    Cuckoo Search (CS) algorithm is a meta-heuristic technique that displays several merits. For example, it is easier to apply and less tuning parameters also, it is suitable for solving optimization problems. However, easily fall into local optimum has been established and has a slow convergence rate as a result of the cuckoo search parameters being kept constant. Therefore to handle this issue, an Enhanced Cuckoo Intelligence Search (ECIS) algorithm was developed which is an upgraded CS algorithm. The efficiency of ECIS was tested by some benchmark constrained optimization test functions and it was shown that ECIS gives a better optimal value than CS.
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    Mathematical modelling for the transmission dynamics of Rift Valley fever virus with human host
    (Universitas Negeri Gorontalo, 2022-06-28) Festus Abiodun Oguntolu; Deborah W. Yavalah; Collins F. Udom; Olumuyiwa James Peter; Kayode Oshinubi
    Rift Valley Fever (RVF) is a viral zoonosis spread primarily by mosquitos that primarily affects livestock but has the potential to affect humans. Because of its potential to spread quickly and become an epidemic, it has become a public concern. In this article, the transmission dynamics of RVF with mosquito, livestock and human host using a compartmental model is studied and analyzed. The basic reproduction number R0 is computed using next generation matrix and the disease-free equilibrium state is found to be locally asymptotically stable if R0 < 1 which implies that rift valley fever could be put under control in a population where the reproduction number is less than 1. The numerical simulations give insightful results to further explore the dynamics of the disease based on the effect of three interventions; efficacy of vaccination, culling of livestock and trapping of mosquitoes introduced in the model.
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    Fractional order mathematical model of monkeypox transmission dynamics
    (IOP Publishing, 2022-07-15) Olumuyiwa James Peter; Festus Abiodun Oguntolu; Mayowa M Ojo; Abdulmumin Olayinka Oyeniyi; Rashid Jan; Ilyas Khan
    In this paper, we present a deterministic mathematical model of monkeypox virus by using both classical and fractional-order differential equations. The model includes all of the possible interactions that contribute to disease spread in the population. We investigate the model's stability results in the disease-free case when R0 < 1. When R0 < 1, we show that the model is stable, otherwise it is unstable. To obtain the best fit that describes the dynamics of this disease in Nigeria, the model is fitted using the nonlinear least square method on cumulative reported cases of monkeypox virus from Nigeria between January to December 2019. Furthermore, adequate conditions for the existence and uniqueness of the solution of the model have been proved. We run numerous simulations of the proposed monkeypox model with varied input parameters to investigate the intricate dynamics of monkeypox infection under the effect of various system input parameters. We investigate the system's dynamical behavior to develop appropriate infection control policies. This allows the public to understand the significance of control parameters in the eradication of monkeypox in the population. Lowering the order of fractional derivatives has resulted in significant modifications. To the community's policymakers, we offered numerous parameters for the control of monkeypox.
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    Mathematical Model of COVID-19 Pandemic with Double Dose Vaccination
    (Springer Science and Business Media LLC, 2023-03-06) Olumuyiwa James Peter; Hasan S. Panigoro; Afeez Abidemi; Mayowa M. Ojo; Festus Abiodun Oguntolu
    This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate, the rate of first vaccine dose, the second dose vaccination rate and the recovery rate due to the second dose of vaccination are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population.
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    Modeling tuberculosis dynamics with vaccination and treatment strategies
    (Elsevier BV, 2025-03-19) Olumuyiwa James Peter; Dipo Aldila; Tawakalt Abosede Ayoola; Ghaniyyat Bolanle Balogun; Festus Abiodun Oguntolu
    Tuberculosis (TB) remains a leading cause of morbidity and mortality worldwide, worsened by the emergence of drug-resistant strains. The implementation of vaccination and observed treatment still becomes the most popular intervention in many countries. This study develops a mathematical model to analyze TB dynamics by considering the impact of integrated intervention vaccination and treatment strategy, and also taking into account the possibility of treatment failure and drug–resistant. The model constructed by dividing the population into six compartments: susceptible S, vaccinated V, latent L, active TB (I), drug-resistant TB Dr, and recovered R. Through a mathematical analysis of the dynamical properties of the proposed model, we demonstrated that the disease-free equilibrium point is always locally asymptotically stable when the basic reproduction number is less than one and unstable when it exceeds one. Moreover, the endemic equilibrium point is shown to exist uniquely only when the basic reproduction number is greater than one, and once it exists, it is always locally stable. For better visualization of the stability properties, we perform continuation simulations to generate a bifurcation diagram of our model, utilizing various bifurcation parameters. The Partial Rank Correlation Coefficient (PRCC) approach is used to carry out sensitivity analyses to determine the most sensitive parameters to the disease control. Simulation results show that increased vaccination rates efficiently reduce the susceptible population to increase the vaccinated population, decreasing disease transmission and lowering the burden of active and drug-resistant tuberculosis. Recovery rates after second-line treatment have a substantial impact on the dynamics of drug-resistant tuberculosis. Higher recovery rates result in faster rises in the recovered population and improved disease control. The findings emphasize the need for integrated measures, such as vaccination campaigns and enhanced treatment procedures, to reduce tuberculosis incidence, minimize drug resistance, and improve public health outcomes. These findings lay the groundwork for enhancing tuberculosis control programs, especially in countries with limited resources.