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Stochastic Modeling and Prediction of the COVID-19 Spread in Kenya
Engineering Mathematics
Volume 4, Issue 2, December 2020, Pages: 31-35
Received: Apr. 11, 2020; Accepted: Aug. 24, 2020; Published: Sep. 3, 2020
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Joab Onyango Odhiambo, School of Pure and Applied Sciences, Meru University of Science and Technology, Meru, Kenya
Jacob Oketch Okungu, School of Pure and Applied Sciences, Meru University of Science and Technology, Meru, Kenya
Christine Gacheri Mutuura, School of Pure and Applied Sciences, Meru University of Science and Technology, Meru, Kenya
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Since the discovery of the novel Covid-19 in December in China, the spread has been massively felt across the world leading World Health Organization declaring it a global pandemic. Italy has been affected most due to the high number of recorded deaths as at 1st August, 2020 at the same time USA recording the highest number of virus reported cases. In addition, the spread has been experienced in many developing African countries including Kenya. While the Kenyan government have had plans for those who have tested positive through self-quarantine beds at Mbagathi Hospital, lack of a proper mathematical model that can be used to model and predict the spread of Covid-19 for adequate response security has been one of the main concerns for the government. Many mathematical models have been proposed for proper modeling and forecasting, but this paper will focus on using a generalized linear regression that can detect linear relationship between the risk factors. The paper intents to model and forecast the confirmed Covid-19 cases in Kenya as a Compound Poisson process where the parameter follows a generalized linear regression that is influenced by the number of daily contact persons and daily flights with the already confirmed cases of the virus. Ultimately, this paper should assist the government in proper resource allocation to deal with pandemic in terms of available of bed capacities, public awareness campaigns and virus testing kits not only in the virus hotbed within Nairobi county but also in the other remaining 46 Kenyan counties.
Covid-19, Stochastic Modeling, Compound Poison Process, Generalized Linear Regression, Contact Persons
To cite this article
Joab Onyango Odhiambo, Jacob Oketch Okungu, Christine Gacheri Mutuura, Stochastic Modeling and Prediction of the COVID-19 Spread in Kenya, Engineering Mathematics. Vol. 4, No. 2, 2020, pp. 31-35. doi: 10.11648/j.engmath.20200402.12
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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