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Modeling the Transmission and Dynamics of COVID-19 Using Self-protection and Isolation as Control Measures
Mathematical Modelling and Applications
Volume 5, Issue 3, September 2020, Pages: 191-201
Received: Jun. 8, 2020; Accepted: Jun. 28, 2020; Published: Sep. 16, 2020
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Demsis Dejene, Department of Mathematics, Wollega University, Nekemte, Ethiopia
Tesfaye Worku, Department of Mathematics, Wollega University, Nekemte, Ethiopia
Purnachandra Rao Koya, Department of Mathematics, Wollega University, Nekemte, Ethiopia
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In this paper, a deterministic five compartmental mathematical model is developed and conducted simulations to study the dynamics of COVID-19 with the inclusion of self-protection and isolation as control measures. The model is shown mathematically and biologically valid by verifying that the solutions are both positive and bounded. Using next generation matrix method, the reproduction number is formulated. The disease free equilibrium point is found and shown that it is conditionally locally and globally asymptotically stable. Further, following Lyapunov function method Endemic equilibrium point is found and shown that it is conditionally globally asymptotically stable. Numerical simulation study is conducted by assigning reasonable values to the parameters. It is concluded that the spread of the disease can be brought under control if the control measures like Self-protection including social distancing and Isolation are implemented affectively. The results and the discussion are presented in the body of the paper lucidly.
Covid-19, Self-Protection, Isolation, Equilibria, Stability, Numerical Simulations
To cite this article
Demsis Dejene, Tesfaye Worku, Purnachandra Rao Koya, Modeling the Transmission and Dynamics of COVID-19 Using Self-protection and Isolation as Control Measures, Mathematical Modelling and Applications. Vol. 5, No. 3, 2020, pp. 191-201. doi: 10.11648/
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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