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Journal of Applied Mathematics and Computation

ISSN Print: 2576-0645 Downloads: 126125 Total View: 1655966
Frequency: quarterly ISSN Online: 2576-0653 CODEN: JAMCEZ
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Article http://dx.doi.org/10.26855/jamc.2022.03.002

Modeling of COVID-19 Transmission under Markov Chains in Uganda

Raphael Naryongo1,*, Joab Onyango2, Loyford Njagi2, Margaret Nakirya3

1Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.

2Department of Mathematics, Meru University of Science and Technology, Meru, Kenya. 

3Department of Mathematics, Kampala International University, Kampala, Uganda.

*Corresponding author: Raphael Naryongo

Published: January 4,2022

Abstract

In this research study, we have modelled the transmission of COVID-19 in Uganda using a discrete-time Markov chain. Most of the already used epidemiological or infectious disease transmission models consist of partial differential equations that do not generalize the determinants of transition at discrete-time intervals when estimating the probability transition matrix. However, using the historical data provided by the Ugandan government through daily press statements, the model has revealed the state of transmission within the population. Furthermore, our model had shown that it is easier to deal with the disease at a latency stage than when the transmission had grown explosively among the healthy Ugandans. In addition, the findings of the research study should enable the Ugandan government to take appropriate preventive disease control measures when combating this life-threatening global pandemic.

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How to cite this paper

Modeling of COVID-19 Transmission under Markov Chains in Uganda

How to cite this paper: Raphael Naryongo, Joab Onyango, Loyford Njagi, Margaret Nakirya. (2022) Modeling of COVID-19 Transmission under Markov Chains in Uganda. Journal of Applied Mathematics and Computation6(1), 4-12.

DOI: https://dx.doi.org/10.26855/jamc.2022.03.002