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: 2023

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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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    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.