On the New Trend of Modeling the Impact of Interacting Rate on the Vulnerability to Ebola Infection
- November 24, 2020
- Posted by: RSIS Team
- Categories: IJRIAS, Mathematics
International Journal of Research and Innovation in ed Applied Science (IJRIAS) | Volume IV, Issue X, October 2020 | ISSN 2454–6186
On the New Trend of Modeling the Impact of Interacting Rate on the Vulnerability to Ebola Infection
Peters Nwagor* , Jim-George Frimabo* & Joyce Adaobi Okoro**
*Department of Mathematics/Statistics,
Ignatius Ajuru University of Education, Port Harcourt
**Department of Mathematics, Federal College of Education (Technical) Omoku, Rivers State
Abstract- By using an appropriate numerical method to model the impact of interacting rate of virus and uninfected cells, we have found that a bifurcation in the quantification of the impact of the disease condition has occurred between a decreased variation value of β at 99.8% and increased variation value of 105% and also the lower limit of the bifurcation interval to be 0.001188 and the upper limit of the bifurcation interval to be 0.00126 which is a vital intervention information in our bid to mitigate against the Ebola disease condition. The novel results that we have obtained which we have not seen elsewhere are fully presented and discussed quantitatively.
Key words: Numerical Method, Population Depletion, Mathematical Modeling, Parallel Data, Bifurcation Interval
1.0 Introduction
One of the process of understanding the dynamics of Ebola virus depends on the application a deterministic interacting system of a dynamical system that describes the growth of the density of uninfected cells at time t, the growth of the density of the infected cells at time t, the growth of the density of the virus at time t, the growth of the density of cytotoxic T-lymphocytes at time t, and existence of a solution, local stability, and stability analysis to mention but a few, there remain other open research questions yet to be fully explored. One of such research questions of concern bothers on the selection of the best fit parallel data which can be used to validate construction of the mathematical model on the spread of Ebola virus, as this idea is highly likely to provide a stronger mitigation measure. Other related mathematical contributions can be seen as read in works of [5] [1] [2] [7] [8] [3] [4]
