Browsing by Author "S. A. Somma"

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A Mathematical Model of a Yellow Fever Dynamics with Vaccination
(Journal of the Nigerian Association of Mathematical Physics, 2015-11) F. A. Oguntolu; N. I. Akinwande; S. A. Somma; F. Y. Eguda; T. T. Ashezua
In this paper, a mathematical model describing the dynamics of yellow fever epidemics, which involves the interactions of two principal communities of Hosts (Humans) and vectors (mosquitoes) is considered. The existence and uniqueness of solutions of the model were examined by actual solution. We conduct local stability analysis for the model. The results show that it is stable under certain conditions. The system of equations describing the phenomenon was solved analytically using parameter-expanding method coupled with direct integration. The results are presented graphically and discussed. It is discovered that improvement in Vaccination strategies will eradicate the epidemics.
Local Stability Analysis of a River Blindness Disease Model with Control
(The Pacific Journal of Science and Technology, 2018-05) F. A. Oguntolu; G. Bolarin; S. A. Somma; A.O. Bello
In this paper, a mathematical model to study the dynamics of River Blindness is presented. The existence and uniqueness of solutions of the model were examined by actual solution. The effective reproduction number was obtained using the next generation matrix. The Disease Free Equilibrium (DFE) State was obtained and analysed for stability. It was found that, the DFE State is Locally Asymptotically Stable (LAS) if the effective reproduction number R0 < 1 and unstable if R0 > 1.
Mathematical model for the dynamics of COVID-19 Pandemic Incorporating Isolation and Non-Linear Recovery Rate
(ISEP Porto-Portugal, 2024-06-22) N. I. Akinwande; T. T. Ashezua; S. A. Somma; O. N. Abdurrahman; F. A. Oguntolu; O. M. Adetutu; R. I. Gweryina; R. O. Olayiwola; T. P. Adajime; F. A. Kuta; S. Abdulrahman; A. I. Enagi; G. A. Bolarin; M. D. Shehua; A. Usman.
COVID-19 has in recent times created a major health concern in both developed and developing parts of the world. In this wise, there is every need to theoretically explore ways that will provide some insights into curtailing the spread of the disease in the population. In this paper, we present a population model for COVID-19 pandemic incorporating isolation and nonlinear recovery rate. The reproduction number was obtained using the next generation method. The disease-free equilibrium (DFE) of the model (1) was found to be locally and globally asymptotically stable whenever the associated reproduction number is less than unity. Results from the sensitivity analysis of the model, using the reproduction number, RC show that the top parameters that largely drive the dynamics of COVID-19 in the population are COVID-19 transmission rate and the proportion of individuals progressing to the class of reported symptomatic infectious individuals. Numerical simulations of the model shows that increasing the recovery rate of infected patients in the population will lead to an initial decrease in the number of hospitalized patients before subsequent increase. The reason for this could be attributed to the number of unreported symptomatic infectious individuals who are progressing to reported symptomatic infectious stage of infection for immediate isolation.
Modelling fire spread reaction rate in atmospheric-weather condition
(Science World Journal, 2021-08-11) A. B. Zhiri; R. O. Olayiwola; S. A. Somma; F. A. Oguntolu
Fire spread in any fire environment is a thing of great concern as wind is arguably the most important weather factor that influences the spread of fire. In this paper, we present equations governing the phenomenon and assume the fire depends on the space variable x . Analytical solution is obtained via perturbation method, direct integration and eigenfunction expansion technique, which depicts the influence of parameters involved in the system. The effect of change in parameters such as Peclet mass number and Equilibrium wind velocity are presented graphically and discussed. The results obtained revealed that both Peclet mass number and Equilibrium wind velocity enhanced oxygen concentration during fire spread.