Industrial Mathematics

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Industrial Mathematics

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    A Mathematical Model Analysis of Meningitis with Treatment and Vaccination in Fractional Derivatives
    (Springer Science and Business Media LLC, 2022-04-26) Olumuyiwa James Peter; Abdullahi Yusuf; Mayowa M. Ojo; Sumit Kumar; Nitu Kumari; Festus Abiodun Oguntolu
    In this paper, we develop a new mathematical model based on the Atangana Baleanu Caputo (ABC) derivative to investigate meningitis dynamics. We explain why fractional calculus is useful for modeling real-world problems. The model contains all of the possible interactions that cause disease to spread in the population. We start with classical differential equations and extended them into fractional-order using ABC. Both local and global asymptotic stability conditions for meningitis-free and endemic equilibria are determined. It is shown that the model undergoes backward bifurcation, where the locally stable disease-free equilibrium coexists with an endemic equilibrium. We also find conditions under which the model’s disease-free equilibrium is globally asymptotically stable. The approach of fractional order calculus is quite new for such a biological phenomenon. The effects of vaccination and treatment on transmission dynamics of meningitis are examined. These findings are based on various fractional parameter values and serve as a control parameter for identifying important disease-control techniques. Finally, the acquired results are graphically displayed to support our findings.
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    Modeling the impact of control strategies on malaria and COVID-19 coinfection: insights and implications for integrated public health interventions
    (Springer Science and Business Media LLC, 2023-12-27) Adesoye Idowu Abioye; Olumuyiwa James Peter; Emmanuel Addai; Festus Abiodun Oguntolu; Tawakalt Abosede Ayoola
    This work discusses the challenge posed by the simultaneous occurrence of malaria and COVID-19 coinfection on global health systems. We propose a novel fractional order mathematical model malaria and COVID-19 coinfection. To assess the impact of control strategies on both diseases, we consider two control strategies which are, personal protection against mosquito bites ($$u_{1}(t)$$) and preventive measures for COVID-19 ($$u_{2}(t)$$). Numerical simulations demonstrate that consistent application of these measures leads to significant reductions in disease transmission. Using insecticide-treated nets and repellents during day and night effectively reduces malaria transmission, while implementing facial masks and hand hygiene controls COVID-19 spread. The most substantial impact is observed when both sets of protection measures are simultaneously adopted, highlighting the importance of integrated strategies. The study provides valuable insights into malaria and COVID-19 coinfection dynamics and emphasizes the impact of the control measures. of individual behavior and consistent adoption of personal protection measures to control both diseases. It underscores the need for integrated public health interventions to combat the dual burden of malaria and COVID-19, contributing to the development of targeted and efficient control measures.
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    Semi-analytical solution for the mathematical modeling of yellow fever dynamics incorporating secondary host
    (Communication in Mathematical Modeling and Applications (CMMA), 2019-04-15) Samuel Abu Somma; Ninuola Ifeoluwa Akinwande; Roseline Toyin Abah; Festus Abiodun Oguntolu; Florence Dami Ayegbusi
    In this paper we use Differential Transformation Method (DTM) to solve the mathematical modeling of yellow fever dynamics incorporating secondary host. The DTM numerical solution was compared with the MAPLE RungeKutta 4-th order. The variable and parameter values used for analytical solution were estimated from the data obtained from World Health Organization (WHO) and UNICEF. The results obtained are in good agreement with Runge-Kutta. The solution was also presented graphically and gives better understanding of the model. The graphical solution showed that vaccination rate and recovery rate play a vital role in eradicating the yellow fever in a community.
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    Stability and optimal control analysis of an SCIR epidemic model
    (SCIK Publishing Corporation, 2020-10-16) Olumuyiwa James Peter; Ratchada Viriyapong; Festus Abiodun Oguntolu; Pensiri Yosyingyong; Helen Olaronke Edogbanya; Michael Oyelami Ajisope
    In this paper, we proposed a deterministic model of SCIR governed by a system of nonlinear differential equations. Two equilibria (disease-free and endemic) are obtained and the basic reproduction number R0 is calculated. If R0 is less than one, then the disease-free equilibrium state is globally stable i.e. the disease will be eradicated eventually. However, when R0 is greater than unity, the disease persists and the endemic equilibrium point is globally stable. Furthermore, the optimal control problem is applied into the model. The focus of this study is to determine what control method can be implemented to significantly slow the incidence of the epidemic disease, therefore we take into account various possible combinations of such three controls which are prevention via proper hygiene, screening of the infected carriers which enable them to know their health conditions and to go for early treatment and treatment of the infected individuals. The possible strategies of using combinations of the three controls on the spread of the disease, one at a time or two at a time is also discussed. Our numerical analysis of the optimal approach suggests that the best method is to incorporate all three controls in order to control the disease epidemic.
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    Forecasting of COVID-19 pandemic in Nigeria using real statistical data
    (SCIK Publishing Corporation, 2021) Adesoye Idowu Abioye; Mfon David Umoh; Olumuyiwa James Peter; Helen Olaronke Edogbanya; Festus Abiodun Oguntolu; Oshinubi Kayode; Sylvanus Amadiegwu
    In this paper, we used data released by Nigeria Center for Disease Control (NCDC) every 24 hours for the past consecutive two months to forecast the Coronavirus disease 2019 (COVID-19) cases for the months (September – October 2020). The linear regression forecasting model and R software package are used for the forecast and simulations respectively. The COVID-19 cases in Nigeria is on a decreasing trend and the forecast result show that in the next two months, there is going to be a decrease in new COVID-19 cases in Nigeria. COVID-19 in Nigeria can be drastically reduced if the organizations, management, government or policymakers are constantly proactive concerning these research findings.
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    Direct and indirect transmission of typhoid fever model with optimal control
    (Elsevier BV, 2021-08) Olumuyiwa James Peter; Mohammed Olanrewaju Ibrahim; Helen Olaronke Edogbanya; Festus Abiodun Oguntolu; Kayode Oshinubi; Abdullahi Adinoyi Ibrahim; Tawakalt Abosede Ayoola; John Oluwasegun Lawal
    In this paper, a model for direct and indirect transmission dynamics of typhoid fever with three control interventions is analyzed. Optimal control strategies are proposed to minimize both the disease burden and the intervention cost. We proved the existence and uniqueness of optimal control paths and obtained these optimal paths analytically using Pontryagin’s Maximum Principle. We analyzed our results numerically to compare various strategies of proposed controls. It is observed that the implementation of the three controls among all strategies is most successful. Thus, we conclude that in order to reduce typhoid fever threat, all the three controls must be taken into consideration concurrently.
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    Time-delayed modelling of the COVID-19 dynamics with a convex incidence rate
    (Elsevier BV, 2022) Oluwatosin Babasola; Oshinubi Kayode; Olumuyiwa James Peter; Faithful Chiagoziem Onwuegbuche; Festus Abiodun Oguntolu
    COVID-19 pandemic represents an unprecedented global health crisis which has an enormous impact on the world population and economy. Many scientists and researchers have combined efforts to develop an approach to tackle this crisis and as a result, researchers have developed several approaches for understanding the COVID-19 transmission dynamics and the way of mitigating its effect. The implementation of a mathematical model has proven helpful in further understanding the behaviour which has helped the policymaker in adopting the best policy necessary for reducing the spread. Most models are based on a system of equations which assume an instantaneous change in the transmission dynamics. However, it is believed that SARS-COV-2 have an incubation period before the tendency of transmission. Therefore, to capture the dynamics adequately, there would be a need for the inclusion of delay parameters which will account for the delay before an exposed individual could become infected. Hence, in this paper, we investigate the SEIR epidemic model with a convex incidence rate incorporated with a time delay. We first discussed the epidemic model as a form of a classical ordinary differential equation and then the inclusion of a delay to represent the period in which the susceptible and exposed individuals became infectious. Secondly, we identify the disease-free together with the endemic equilibrium state and examine their stability by adopting the delay differential equation stability theory. Thereafter, we carried out numerical simulations with suitable parameters choice to illustrate the theoretical result of the system and for a better understanding of the model dynamics. We also vary the length of the delay to illustrate the changes in the model as the delay parameters change which enables us to further gain an insight into the effect of the included delay in a dynamical system. The result confirms that the inclusion of delay destabilises the system and it forces the system to exhibit an oscillatory behaviour which leads to a periodic solution and it further helps us to gain more insight into the transmission dynamics of the disease and strategy to reduce the risk of infection.
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    Mathematical analysis on the vertical and horizontal transmission dynamics of HIV and Zika virus co-infection
    (Elsevier BV, 2024-03) Benjamin Idoko Omede; Bolarinwa Bolaji; Olumuyiwa James Peter; Abdullahi A. Ibrahim; Festus Abiodun Oguntolu
    The co-infection of HIV and Zika virus (ZIKV) poses a complex and understudied health challenge, requiring a comprehensive investigation into the synergistic effects, potential complications, and the impact on affected individuals. Consequently, This paper introduces a novel deterministic mathematical model that examines the transmission dynamics of HIV and Zika virus co-infection, considering both vertical and horizontal transmission. The analysis begins with two sub-models: one for HIV-only and another for ZIKV-only. Qualitative examination indicates that the HIV only sub-model achieves a globally asymptotically stable disease-free equilibrium when the associated reproduction number is below unity. In contrast, the ZIKV only sub-model exhibits a backward bifurcation phenomenon, where both stable disease-free and stable endemic equilibria co-exist when the associated reproduction number of the ZIKV only sub-model is less than unity. Thus, the backward bifurcation property makes effective control of ZIKV infection in the population difficulty when the associated reproduction number is less than unity. It is shown, using the center manifold theory that the full HIV-ZIKV co-infection model undergoes the phenomenon of backward bifurcation. We carried out the sensitivity analysis of the HIV and ZIKV basic reproduction numbers to determine the parameters that positively influence the spread of the two diseases. It is also revealed that an increase in HIV infection in the population will positively influence the transmission of ZIKV. We validated the ZIKV only sub-model by fitting the ZIKV only sub-model to the confirmed cases of ZIKV data in Brazil. The outcome of the numerical simulations of HIV-ZIKV co-infection model reveals that the two diseases co-exist when their basic reproduction number surpasses one. Furthermore, increasing HIV treatment rate significantly reduces the burden of co-infection with the Zika virus.
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    Optimizing tuberculosis control: a comprehensive simulation of integrated interventions using a mathematical model
    (Mathematical Modelling and Numerical Simulation with Applications, 2024-09-30) Olumuyiwa James Peter; Afeez Abidemi; Fatmawati Fatmawati; Mayowa M. Ojo; Festus Abiodun Oguntolu
    Tuberculosis (TB) remains a formidable global health challenge, demanding effective control strategies to alleviate its burden. In this study, we introduce a comprehensive mathematical model to unravel the intricate dynamics of TB transmission and assess the efficacy and cost-effectiveness of diverse intervention strategies. Our model meticulously categorizes the total population into seven distinct compartments, encompassing susceptibility, vaccination, diagnosed infectious, undiagnosed infectious, hospitalized, and recovered individuals. Factors such as susceptible individual recruitment, the impact of vaccination, immunity loss, and the nuanced dynamics of transmission between compartments are considered. Notably, we compute the basic reproduction number, providing a quantitative measure of TB transmission potential. Through this comprehensive model, our study aims to offer valuable insights into optimal control measures for TB prevention and control, contributing to the ongoing global efforts to combat this pressing health challenge.
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    Mathematical Modeling on the Transmission Dynamics of Diphtheria with Optimal Control Strategies
    (Department of Mathematics, Universitas Negeri Gorontalo, 2025-03-29) Festus Abiodun Oguntolu; Olumuyiwa James Peter; Benjamin Idoko Omede; Ghaniyyat Bolanle Balogun; Aminat Olabisi Ajiboye; Hasan S. Panigoro
    Diphtheria is an acute bacterial infection caused by Corynebacterium diphtheriae, characterized by the formation of a pseudo-membrane in the throat, which can lead to airway obstruction and systemic complications. Despite the availability of effective vaccines, diphtheria remains a significant public health concern in many regions, particularly in areas with low immunization coverage. In this study, we formulated and rigorously analyzed a deter ministic epidemiological mathematical model to gain insight into the transmission dynamics of Diphtheria infection, incorporating the concentration of Corynebacterium Diphtheriae in the environment. The analysis of the model begins with the computation of the basic reproduction number and the examination of the local stability of the disease-free equilibrium using the Routh-Hurwitz criterion. An in-depth analysis of the model reveals that the model undergoes the phenomenon of backward bifurcation. This characteristic poses significant hurdles in effectively controlling Diph theria infection within the population. However, under the assumption of no re-infection of Diphtheria infection after recovery, the disease-free equilibrium point is globally asymptotically stable whenever the basic reproduction num ber is less than one. Furthermore, the sensitivity analysis of the basic reproduction number was carried out in order to determine the impact of each of the model basic parameters that contribute to the transmission of the disease. Utilizing the optimal control theory to effectively curb the spread of Diphtheria, We introduced two time dependent control measures, to mitigate the spread of Diphtheria. These time dependent control measures represent preventive actions, such as public enlightenment campaign to sensitize and educate the general public on the dynamics of Diph theria and proper personal hygiene which includes regular washing of hands to prevent susceptible individuals from acquiring Diphtheria, and environmental sanitation practices such as cleaning of surfaces and door handle to reduced the concentration of Corynebacterium diphtheriae in the environment. The results from the numerical simulations reveal that Diphtheria infection can successfully be controlled and mitigated within the population if we can increase the vaccination rate and the decay rate of Corynebacterium Diphtheriae in the environment, as well as properly and effectively implementing these optimal control measures simultaneously.