Browsing by Author "Okyere, Eric"

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    Fractal-Fractional Caputo Maize Streak Virus Disease Model
    (MDPI, 2023-02) Ackora-Prah, Joseph; Seidu, Baba; Okyere, Eric; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    Maize is one of the most extensively produced cereals in the world. The maize streak virus primarily infects maize but can also infect over 80 other grass species. Leafhoppers are the primary vectors of the maize streak virus. When feeding on plants, susceptible vectors can acquire the virus from infected plants, and infected vectors can transmit the virus to susceptible plants. However, because maize is normally patchy and leafhoppers are mobile, leafhoppers will always be foraging for food. Therefore, we want to look at how leafhoppers interact on maize farms using Holling’s Type III functional response in a Caputo fractal-fractional derivative sense. We show that the proposed model has unique positive solutions within a feasible region. We employed the Newton polynomial scheme to numerically simulate the proposed model to illustrate the qualitative results obtained. We also studied the relationship between the state variables and some epidemiological factors captured as model parameters. We observed that the integer-order versions of the model exaggerate the impact of the disease. We also observe that the increase in the leafhopper infestation on maize fields has a devastating effect on the health of maize plants and the subsequent yield. Furthermore, we noticed that varying the conversion rate of the infected leafhopper leads to a crossover effect in the number of healthy maize after 82 days. We also show the dynamics of varying the maize streak virus transmission rates. It indicates that when preventive measures are taken to reduce the transmission rates, It will reduce the low-yielding effect of maize due to the maize streak virus disease.
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    Fractal-Fractional SIRS Epidemic Model with Temporary Immunity Using Atangana-Baleanu Derivative
    (Commun. Math. Biol. Neurosci., 2022-05) Okyere, Eric; Seidu, Baba; Nantomah, Kwara; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    The basic SIRS deterministic model is one of the powerful and important compartmental modeling frameworks that serve as the foundation for a variety of epidemiological models and investigations. In this study, a nonlinear Atangana-Baleanu fractal-fractional SIRS epidemiological model is proposed and analysed. The model’s equilibrium points (disease-free and endemic) are studied for local asymptotic stability. The existence of the model’s solution and its uniqueness, as well as the Hyers-Ulam stability analysis, are established. Numerical solutions and phase portraits for the fractal-fractional model are generated using a recently constructed and effective Newton polynomial-based iterative scheme for nonlinear dynamical fractal-fractional model problems. Our numerical simulations demonstrate that fractal-fractional dynamic modeling is a very useful and appropriate mathematical modeling tool for developing and studying epidemiological models.
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    Mathematical modelling of earlier stages of COVID-19 transmission dynamics in Ghana
    (Elsevier, 2022-01) Acheampong, Edward; Okyere, Eric; Iddi, Samuel; Bonney, Joseph H.K.; Asamoah, Joshua Kiddy K.; Wattis, Jonathan A.D.; Gomes, Rachel L.; 0000-0002-7066-246X
    In late 2019, a novel coronavirus, the SARS-CoV-2 outbreak was identified in Wuhan, China and later spread to every corner of the globe. Whilst the number of infection-induced deaths in Ghana, West Africa are minimal when compared with the rest of the world, the impact on the local health service is still significant. Compartmental models are a useful framework for investigating transmission of diseases in societies. To understand how the infection will spread and how to limit the outbreak. We have developed a modified SEIR compartmental model with nine compartments (CoVCom9) to describe the dynamics of SARS-CoV-2 transmission in Ghana. We have carried out a detailed mathematical analysis of the CoVCom9, including the derivation of the basic reproduction number, 0. In particular, we have shown that the disease-free equilibrium is globally asymptotically stable when 0 < 1 via a candidate Lyapunov function. Using the SARS-CoV-2 reported data for confirmed-positive cases and deaths from March 13 to August 10, 2020, we have parametrised the CoVCom9 model. The results of this fit show good agreement with data. We used Latin hypercube sampling-rank correlation coefficient (LHS-PRCC) to investigate the uncertainty and sensitivity of 0 since the results derived are significant in controlling the spread of SARS-CoV-2. We estimate that over this five month period, the basic reproduction number is given by 0 = 3.110, with the 95% confidence interval being 2.042 ≤ 0 ≤ 3.240, and the mean value being 0 = 2.623. Of the 32 parameters in the model, we find that just six have a significant influence on 0, these include the rate of testing, where an increasing testing rate contributes to the reduction of 0.
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    Non-fractional and fractional mathematical analysis and simulations for Q fever
    (Elsevier, 2022-01) Asamoah, Joshua Kiddy K.; Okyere, Eric; Yankson, Ernest; Opoku, Alex Akwasi; Adom-Konadu, Agnes; Acheampong, Edward; Arthur, Yarhands Dissou; 0000-0002-7066-246X
    The purpose of analysing the transmission dynamism of Q fever (Coxiellosis) in livestock and incorpo- rating ticks is to outline some management practices to minimise the spread of the disease in livestock. Ticks pass coxiellosis from an infected to a susceptible animal through a bite. The faecal matter can also contain coxiellosis, thus contaminating the environment and spreading the disease. First, a nonlinear integer order mathematical model is developed to represent the spread of this infectious disease in live- stock. The proposed integer model investigates the positivity and boundedness, disease equilibria, basic reproduction number, bifurcation, and sensitivity analysis. Through mathematical analysis and numerical simulations, it shows that if the environmental transmission and the effective shedding rate of coxiella burnetii into the environment by both asymptomatic and symptomatic livestock are zero, then the usual threshold hold and it produces forward bifurcation. It is noticed that an increase in the recruitment rate of ticks produces backward bifurcation. And also, it is seen that an increase in the natural decay rate of the bacterial in the environment reduces the backward bifurcation point. Furthermore, to take care of the memory aspect of ticks on their host, we modified the initially proposed integer order model by introducing Caputo, Caputo-Fabrizio, Atangana-Baleanu fractional differential operators. The existence and uniqueness of these three newly developed fractional-order differential models are shown using the Banach fixed point theorem. Numerical trajectories are obtained for each of the fractional-order math- ematical models. The trajectory of some fractional orders converges to the same endemic equilibrium point as the integer order. Finally, it is seen that the Atangana-Baleanu fractional differential operator captures more susceptibilities and fewer infections than the other operators.
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    Optimal control and comprehensive cost-effectiveness analysis for COVID-19
    (Elsevier, 2022-01) Asamoah, Joshua Kiddy K.; Okyere, Eric; Abidemi, Afeez; Moore, Stephen E.; Sun, Gui-Quan; Jin, Zhen; Acheampong, Edward; Gordon, Joseph Frank; 0000-0002-7066-246X
    Cost-effectiveness analysis is a mode of determining both the cost and economic health outcomes of one or more control interventions. In this work, we have formulated a non-autonomous nonlinear deterministic model to study the control of COVID-19 to unravel the cost and economic health outcomes for the autonomous nonlinear model proposed for the Kingdom of Saudi Arabia. We calculated the strength number and noticed the strength number is less than zero, meaning the proposed model does not capture multiple waves, hence to capture multiple wave new compartmental model may require for the Kingdom of Saudi Arabia. We proposed an optimal control problem based on a previously studied model and proved the existence of the proposed optimal control model. The optimality system associated with the non-autonomous epidemic model is derived using Pontryagin’s maximum principle. The optimal control model captures four time-dependent control functions, thus, 𝑢1-practising physical or social distancing protocols; 𝑢2-practising personal hygiene by cleaning contaminated surfaces with alcohol-based detergents; 𝑢3-practising proper and safety measures by exposed, asymptomatic and symptomatic infected individuals; 𝑢4-fumigating schools in all levels of education, sports facilities, commercial areas and religious worship centres. We have performed numerical simulations to investigate extensive cost-effectiveness analysis for fourteen optimal control strategies. Comparing the control strategies, we noticed that; Strategy 1 (practising physical or social distancing protocols) is the most costsaving and most effective control intervention in Saudi Arabia in the absence of vaccination. But, in terms of the infection averted, we saw that strategy 6, strategy 11, strategy 12, and strategy 14 are just as good in controlling COVID-19.