School of Physical Sciences (SPS)

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School of Physical Sciences (SPS)

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Author: search.filters.author.Festus Abiodun OguntoluStart date: 2022

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    Mathematical model of measles transmission dynamics using real data from Nigeria
    (Informa UK Limited, 2022-05-25) Olumuyiwa James Peter; Mayowa M. Ojo; Ratchada Viriyapong; Festus Abiodun Oguntolu
    Measles is a highly contagious and life-threatening disease caused by a virus called morbillivirus, despite the availability of a safe and cost-effective vaccine, it remains a leading cause of death, especially in children. Measles spreads easily from person to person via infected people's coughs and sneezes. It can also be transmitted through direct contact with the mouth or contaminated surfaces. To have a better knowledge of measles epidemiology in Nigeria, we develop a deterministic mathematical model to study the transmission dynamics of the disease in the population. The boundary of the model solution is performed, both equilibrium points are calculated, and the basic reproduction number ℛ0 is determined. We have proved that when ℛ0<1, the disease-free equilibrium point is both locally and globally stable. When ℛ0>1, the endemic equilibrium point exists and is stable if it satisfies Routh–Hurwitz criteria. We demonstrate the model's effectiveness by using a real-life application of the disease spread in Nigeria. We fit the proposed model using available data from Nigeria Center for Disease Control (NCDC) from January to December 2020 to obtain the best fit, this help us to determine the accuracy of the proposed model's representation to the real-world data. We investigate the impact of vaccination rate and hospitalization of infected individuals on the dynamics of measles in the population. The result shows that the combined control strategies reduce the peak of infection faster than the single control strategy.
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    Modeling and optimal control of monkeypox with cost-effective strategies
    (Springer Science and Business Media LLC, 2022-11-22) Olumuyiwa James Peter; Chinwendu E. Madubueze; Mayowa M. Ojo; Festus Abiodun Oguntolu; Tawakalt Abosede Ayoola
    In this work, we develop and analyze a deterministic mathematical model to investigate the dynamics of monkeypox. We examine the local and global stability of the basic model without control variables. The outcome demonstrates that when the reproduction number , the model’s disease-free equilibrium would be locally and globally asymptotically stable. We further analyze the effective control of monkeypox in a given population by formulating and analyzing an optimal control problem. We extend the basic model to include four control variables, namely preventive strategies for transmission from rodents to humans, prevention of infection from human to human, isolation of infected individuals, and treatment of isolated individuals. We established the necessary conditions for the existence of optimal control using Pontryagin’s maximal principle. To illustrate the impact of different control combinations on the spread of monkeypox, we use the fourth-order Runge–Kutta forward–backward sweep approach to simulate the optimality system. A cost-effectiveness study is conducted to educate the public about the most cost-effective method among various control combinations. The results suggest that, of all the combinations considered in this study, implementing preventive strategies for transmission from rodents to humans is the most economical and effective among all competing strategies.
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    Mathematical model on the transmission dynamics of leptospirosis in human and animal population with optimal control strategies using real statistical data
    (Springer Science and Business Media LLC, 2024-12-07) Festus Abiodun Oguntolu; Olumuyiwa James Peter; Benjamin Idoko Omede; Ghaniyyat Bolanle Balogun; Tawakalt Abosede Ayoola
    Leptospirosis poses a significant public health challenge, with a growing incidence in both human and animal populations. The complex interplay between reservoir hosts, environmental factors, and human activities complicates efforts to curb the spread of the disease. Consequently, this paper presents a deterministic mathematical model for the transmission dynamics of leptospirosis within the intertwined human and animal populations. A comprehensive examination of the model revealed that the disease-free equilibrium is globally asymptotically stable when the basic reproduction number is below one. Utilizing center manifold theory, we demonstrated that the Leptospirosis model displays forward bifurcation. Consequently, the epidemiological significance of this forward bifurcation suggests that eradicating leptospirosis from the community is feasible, provided the reproduction number remains below one. We conducted a sensitivity analysis on the basic reproduction number of Leptospirosis to identify parameters that contribute positively to the disease’s spread. Furthermore, We validated our Leptospirosis model by fitting it with confirmed cases reported in Kerala State, India, covering the period from January 2021 to December 2022. This calibration process ensures the model’s accuracy and reliability in reflecting real-world epidemiological dynamics within the specified region and timeframe. In addition, we enhanced the Leptospirosis model by incorporating three time-dependent control measures. These controls encompass the vaccination of animals, environmental sanitation, and preventive actions such as using hand gloves and goggles when handling animals, as well as wearing rubber boots during periods of flooding or heavy rainfall. Results obtained from numerical simulations indicate that implementing the vaccination of animals as a standalone control strategy has no discernible effect on the number of infected humans or the bacteria population. However, when the three time-dependent control measures are combined, there is a substantial and meaningful impact on reducing the number of infected humans, infected animals, and the overall bacteria population within a relatively short timeframe. This underscores the effectiveness of the integrated approach in mitigating the spread of leptospirosis across both human and animal populations.
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    A fractional-order mathematical model for malaria and COVID-19 co-infection dynamics
    (Elsevier BV, 2023-12) Adesoye Idowu Abioye; Olumuyiwa James Peter; Hammed Abiodun Ogunseye; Festus Abiodun Oguntolu; Tawakalt Abosede Ayoola; Asimiyu Olalekan Oladapo
    This study proposes a fractional-order mathematical model for malaria and COVID-19 co-infection using the Atangana–Baleanu Derivative. We explain the various stages of the diseases together in humans and mosquitoes, and we also establish the existence and uniqueness of the fractional order co-infection model solution using the fixed point theorem. We conduct the qualitative analysis along with an epidemic indicator, the basic reproduction number R0 of this model. We investigate the global stability at the disease and endemic free equilibrium of the malaria-only, COVID-19-only, and co-infection models. We run different simulations of the fractional-order co-infection model using a two-step Lagrange interpolation polynomial approximate method with the aid of the Maple software package. The results reveal that reducing the risk of malaria and COVID-19 by taking preventive measures will reduce the risk factor for getting COVID-19 after contracting malaria and will also reduce the risk factor for getting malaria after contracting COVID-19 even to the point of extinction.
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    A non-linear differential equation model of COVID-19 and seasonal influenza co-infection dynamics under vaccination strategy and immunity waning
    (Elsevier BV, 2023-12) Rabiu Musa; Olumuyiwa James Peter; Festus Abiodun Oguntolu
    This study presents a mathematical model of the transmission dynamics of COVID-19 and influenza co-infection. The potential impacts of the influenza vaccine only on the co-infection dynamics and the potential impacts of both vaccines on the co-infection dynamics are thoroughly studied. The basic reproduction number for the two diseases using the next-generation matrix approach and the stability of the sub-model is examined. The model assessed the scenario whereby both diseases’ waning immunity occurs concurrently to check the epidemic peaks. The numerical simulation results show that the diseases would continue to be endemic in the population if the immunity waning rates increase. The epidemic peak can be reduced by increasing vaccination and vaccine efficacy rates. The results show that the COVID-19 contact rate significantly increases the epidemic level more than the co-infection contact rate. A similar result was obtained when it was observed that the COVID-19 post-recovery waning rate has more significant effects on the epidemic peak than the co-infection post-recovery waning rate. A possible reason for this counter-intuitive occurrence is that two infections cannot have the same viral load nor the same within-host competitiveness. This means an infectious co-infected person will transmit the infection with the highest within-host competitiveness. Here, it is suspected that COVID-19 has a within-host competitive advantage over influenza in the co-dynamics.