Browsing by Author "Addai, Emmanuel"

Now showing 1 - 7 of 7
  • No Thumbnail Available
    Item
    A fractional order age-specific smoke epidemic model
    (Elsevier, 2023) Addai, Emmanuel; Asamoah, Joshua Kiddy K.; Zhang, Lingling; Essel, John Fiifi; 0000-0002-7066-246X
    This paper presents a nonlinear fractional mathematical model for the smoke epidemic that includes two age groups. To solve the smoke epidemic, the Atangana-Baleanu-Caputo fractional derivative is used. The Banach and Krasnoselskii type fixed point theorem is used to determine existence and uniqueness. We explored model stability using the Hyers-Ulam form of stability. Using Lagrange interpolation, the behaviour of the smoke epidemic of the 2-age group model is generated. The numerical simulation shows that the model has po- tential for both groups, and that age-specific interventions can be used to reduce smoking rates in the general population.
  • No Thumbnail Available
    Item
    A nonlinear fractional epidemic model for the Marburg virus transmission with public health education
    (Scientific Reports, 2023) Addai, Emmanuel; Adeniji, Adejimi; Ngungu, Mercy; Tawiah, Godfred Kuffuor; Marinda, Edmore; Asamoah, Joshua Kiddy K.; Khan, Mohammed Altaf; 0000-0002-7066-246X
    In this study, a deterministic model for the dynamics of Marburg virus transmission that incorporates the impact of public health education is being formulated and analyzed. The Caputo fractional-order derivative is used to extend the traditional integer model to a fractional-based model. The model’s positivity and boundedness are also under investigation. We obtain the basic reproduction number R0 and establish the conditions for the local and global asymptotic stability for the disease-free equilibrium of the model. Under the Caputo fractional-order derivative, we establish the existenceuniqueness theory using the Banach contraction mapping principle for the solution of the proposed model. We use functional techniques to demonstrate the proposed model’s stability under the Ulam-Hyers condition. The numerical solutions are being determined through the Predictor- Corrector scheme. Awareness, as a form of education that lowers the risk of danger, is reducing susceptibility and the risk of infection. We employ numerical simulations to showcase the variety of realistic parameter values that support the argument that human awareness, as a form of education, considerably lowers susceptibility and the risk of infection.
  • No Thumbnail Available
    Item
    Fractal-fractional order dynamics and numerical simulations of a Zika epidemic model with insecticide-treated nets
    (2022-06) Addai, Emmanuel; Zhang, Lingling; Ackora-Prah, Joseph; Gordon, Joseph Frank; Asamoah, Joshua Kiddy K.; Essel, John Fiifi; 0000-0002-7066-246X
    Fractional order and fractal order are mathematical tools that can be used to model realworld problems. In order to demonstrate the usefulness of these operators, we develop a new fractal-fractional model for the propagation of the Zika virus. This model includes insecticide-treated nets and the generalized fractal-fractional Mittag-Leffler kernel. The existence, uniqueness, and Ulam–Hyres stability conditions for the given system are determined. Using the Newton polynomial, the numerical scheme is described. From the numerical simulations, we notice that a change in the fractal-fractional order directly affects the dynamics of the Zika virus. We also notice that the use of fractal order only converges to faster than the use of fractional order only. Testing the inherent potency of insecticide-treated nets when the fractal-fractional order is 0.99 indicates that increased use of insecticide-treated nets increases the number of healthy humans. The fractalfractional analysis captures the geometric pattern of the Zika virus that is repeated at every scale, which cannot be captured by classical geometry. This backs up the idea that the best way to control the disease is to know enough about how it spread in the past.
  • No Thumbnail Available
    Item
    Fractal–fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics
    (Elsevier, 2022-09) Addai, Emmanuel; Zhang, Lingling; Asamoah, Joshua Kiddy K.; Preko, Ama Kyerewaa; Arthur, Yarhands Dissou; 0000-0002-7066-246X
    This paper proposes a new fractal–fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo–Fabrizio fractional order derivative. Caputo–Fabrizio fractal–fractional order is particularly successful in modelling real-world phenomena due to its repeated memory effect and ability to capture the exponentially decreasing impact of disease transmission dynamics. We consider two age groups, the first of which has a population under 50 and the second of a population beyond 50. Our results show that at a population dynamics level, there is a high infection and recovery of omicron SARS-CoV-2 variant infection among the population under 50 (Group-1), while a high infection rate and low recovery of omicron SARS-CoV-2 variant infection among the population beyond 50 (Group-2) when the fractal–fractional order is varied.
  • No Thumbnail Available
    Item
    Fractional order epidemiological model of SARS-CoV-2 dynamism involving Alzheimer’s disease
    (Elsevier, 2022-09) Addai, Emmanuel; Zhang, Lingling; Preko, Ama Kyerewaa; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    In this paper, we study a Caputo–Fabrizio fractional order epidemiological model for the transmission dynamism of the severe acute respiratory syndrome coronavirus 2 pandemic and its relationship with Alzheimer’s disease. Alzheimer’s disease is incorporated into the model by evaluating its relevance to the quarantine strategy. We use functional techniques to demonstrate the proposed model stability under the Ulam–Hyres condition. The Adams–Bashforth method is used to determine the numerical solution for our proposed model. According to our numerical results, we notice that an increase in the quarantine parameter has minimal effect on the Alzheimer’s disease compartment.
  • No Thumbnail Available
    Item
    Fractional-Order Ebola-Malaria Coinfection Model with a Focus on Detection and Treatment Rate
    (Hindawi, 2022-09) Zhang, Lingling; Addai, Emmanuel; Ackora-Prah, Joseph; Dissou Arthur, Yarhands; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    Coinfection of Ebola virus and malaria is widespread, particularly in impoverished areas where malaria is already ubiquitous. Epidemics of Ebola virus disease arise on a sporadic basis in African nations with a high malaria burden. An observational study discovered that patients in Sierra Leone’s Ebola treatment centers were routinely infected with malaria parasites, increasing the risk of death. In this paper, we study Ebola-malaria coinfections under the generalized Mittag-Leffler kernel fractional derivative. The Banach fixed point theorem and the Krasnoselskii type are used to analyse the model’s existence and uniqueness. We discuss the model stability using the Hyers-Ulam functional analysis. The numerical scheme for the Ebolamalaria coinfections using Lagrange interpolation is presented. The numerical trajectories show that the prevalence of Ebolamalaria coinfections ranged from low to moderate depending on memory. This means that controlling the disease requires adequate knowledge of the past history of the dynamics of both malaria and Ebola. The graphical dynamics of the detection rate indicate that a variation in the detection rate only affects the following compartments: individuals that are latently infected with the Ebola, Ebola virus afflicted people who went unnoticed, individuals who have been infected with the Ebola virus and have been diagnosed with the disease, and persons undergoing Ebola virus therapy.
  • No Thumbnail Available
    Item
    Modelling the dynamics of online food delivery services on the spread of food‑borne diseases
    (Springer, 2024-05) Addai, Emmanuel; Torres, Delfim F. M.; Abdul‑Hamid, Zalia; Mezue, Mary Nwaife; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    We propose and analyze a deterministic mathematical model for the transmission of food-borne diseases in a population consisting of humans and flies. We employ the Caputo operator to examine the impact of governmental actions and online food delivery services on the transmission of food-borne diseases. The proposed model investigates important aspects such as positivity, boundedness, disease-free equilibrium, basic reproduction number and sensitivity analysis. The existence and uniqueness of a solution for the initial value problem is established using Banach and Schauder type fixed point theorems. Functional techniques are employed to demonstrate the stability of the proposed model under the Hyers–Ulam condition. For an approximate solution, the iterative fractional order Predictor–Corrector scheme is utilized. The simulation of this scheme is conducted using Matlab as the numeric computing environment, with various fractional order values ranging from 0.75 to 1. Over time, all compartments demonstrate convergence and stability. The numerical simulations highlight the necessity for the government to implement the most effective food safety control interventions. These measures could involve food safety awareness and training campaigns targeting restaurant managers, staff members involved in online food delivery, as well as food delivery personnel.