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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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    Modeling prevalence of meningitis control strategies through evaluating with available data on meningitis cases reported in Nigeria
    (Springer Science and Business Media LLC, 2025-05-14) O.J. Peter; F.A. Oguntolu; N. Nyerere; A. El-Mesady
    Meningitis is a major public health concern, especially in developing nations, due to its devastating consequences for human health. Although modeling studies have examined disease transmission dynamics, little attention has been paid to how control strategies affect the behavior of different population groups, including carriers, symptomatic individuals, hospitalized patients, and those in intensive care. This study proposes a computational framework that compares the effectiveness of vaccination of people at risk of the disease versus treating symptomatic infected persons. The basic reproduction number is used to evaluate the equilibrium points. Assess the precision of the proposed model’s illustration to data. We fit the meningitis model using the information at our disposal on meningitis cases reported in Nigeria from the first week of January to the last week of December 2023; this was obtained from the Nigerian Center for Disease Control (NCDC) database. We also performed a sensitivity analysis using a normalized forward sensitivity index to see which parameters had significant effects on the effective reproduction number. The results of both analytical techniques and numerical simulations reveal that recruitment rate, vaccination, progression from carrier to symptomatic stages, and disease-induced death all significantly reduce the incidence and prevalence of meningitis in the community. The study findings could be used to inform decisions about meningitis control initiatives.
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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.