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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.
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.
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.

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