Industrial Mathematics

Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/189

Industrial Mathematics

Browse

Author: search.filters.author.Olumuyiwa James PeterSubject: search.filters.subject.Stability analysis

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    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.
  • No Thumbnail Available
    Item
    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.