The Impact of Susceptible Human Immigrants on the Spread and Dynamics of Malaria Transmission
American Journal of Applied Mathematics
Volume 6, Issue 3, June 2018, Pages: 117-127
Received: May 25, 2018; Accepted: Jun. 26, 2018; Published: Aug. 2, 2018
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Authors
Alemu Geleta Wedajo, Department of Mathematics, Wollega University, Nekemte, Ethiopia
Boka Kumsa Bole, Department of Mathematics, Wollega University, Nekemte, Ethiopia
Purnachandra Rao Koya, Department of Mathematics, Hawassa University, Hawassa, Ethiopia
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Abstract
Malaria is one of infectious diseases and has become the most public health issue especially in developing countries. Mathematically, the spread of malaria can be modeled to predict the dynamics of the outbreak of the disease. The present research studies the impact of migration of susceptible population on the dynamics of malaria transmission. In this paper an improved mathematical model is constructed based on a set of reasonable assumptions. Validity of the model is proved by verifying positivity of the solution. Mathematical analysis is carried out including equilibrium point analysis. Basic reproduction number of the model is determined so as to study the effect of migration parameter on the malaria outbreak. It has been observed that the migration parameter is directly proportional to the malaria outbreak. Hence, it is suggested that in order to keep the malaria outbreak under control, the migration parameter is required to be minimized. That is, migration of populations is recommended to reduce so as to reduce the impact of malaria outbreak.
Keywords
Malaria Outbreak, Reproduction Number, Migration Parameter, Numerical Simulation
To cite this article
Alemu Geleta Wedajo, Boka Kumsa Bole, Purnachandra Rao Koya, The Impact of Susceptible Human Immigrants on the Spread and Dynamics of Malaria Transmission, American Journal of Applied Mathematics. Vol. 6, No. 3, 2018, pp. 117-127. doi: 10.11648/j.ajam.20180603.13
Copyright
Copyright © 2018 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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