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Modelling and Analysis of Effect of Awareness Programs by Media on the Spread of COVID-19 Pandemic Disease
Mathematics and Computer Science
Volume 5, Issue 5, September 2020, Pages: 93-102
Received: Oct. 21, 2020; Accepted: Nov. 4, 2020; Published: Dec. 11, 2020
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Author
Fekadu Tadege Kobe, Department of Mathematics, College of Natural and Computational Science, Wachemo University, Hossana, Ethiopia
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Abstract
This paper proposes and analyses a basic deterministic mathematical model to investigate Modeling and Analysis of effect of awareness program by media on the spread COVID-19 Pandemic Disease. The model has seven non-linear differential equations, which describe the effects of awareness programs by media on the spread of COVID-19 Pandemic diseases. Analytical study carried out to investigate the model analysis and existence of stability of system, given threshold parameters known as the basic reproduction number, which obtained using next generation matrix method. The equilibrium of COVID 19 models is determined. In addition to having a disease-free equilibrium, which is globally asymptotically stable when the basic reproduction number less than one, COVID 19 model manifest one's possession of (a quality of) the phenomenon of backward bifurcation where a stable disease-free equilibrium co-exists (at the same time) with a stable endemic equilibrium for a certain range of associated reproduction number less than one. The analysis and simulation results of the model suggested that the most effective strategies for controlling or eradicating the spread of COVID 19 pandemic were suggest using that awareness programs through the media campaigning are helpful in decreasing the spread of COVID 19 Pandemic diseases by isolating a fraction of susceptible from infective.
Keywords
COVID-19 Pandemic, Awareness Programs, Stability Analysis, SEIR Model and Reproduction Number
To cite this article
Fekadu Tadege Kobe, Modelling and Analysis of Effect of Awareness Programs by Media on the Spread of COVID-19 Pandemic Disease, Mathematics and Computer Science. Vol. 5, No. 5, 2020, pp. 93-102. doi: 10.11648/j.mcs.20200505.12
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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