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Joab Odhiambo, Weke P, Ngare P. "Modeling Kenyan economic impact of corona virus in Kenya using discrete-time Markov chains." Journal of Finance and Economics. 2020;8(2):, 80-85. AbstractWebsite

Since the outbreak of pandemic COVID-19 (Corona virus), many countries have continued to suffer
economically leading to massive losses in terms of trillions of dollars globally in terms of trade loses. In reaction to
this effect, many countries in the world have taken emergency measures to ensure that the impact does not lead to
huge economic and financial implications in terms of rapid recession. In Africa, where many countries have taken
measures to deal with global recession to the citizens especially through fiscal and monetary policies, which includes
Kenya. In addition, the social economic statues have continued to change instantaneously and stochastically
more so after huge number of populations losing their daily informal jobs with new measures to stop the spread of
COVID-19 virus. This paper seeks to model the effect of COVID-19 pandemic on Kenyan Gross Domestic Product
(GDP) contributors using a Discrete-time Markov Chain Analysis. In addition, the paper seeks to find the ultimate
effect of the Covid-19 to the top five key sectors of the Kenyan economy that contributes massively to GDP growth
by looking at the proportion of the contributors at steady state. Moreover, the results from this paper should help the
government of Kenya as well as global investors to understand different economic stimulus planning packages to
launch in the “hard-hit” sectors of the economy to reduce the impact of the potential economic recession. Ultimately,
the information should be help in formulating a post COVID-19 economic recovery plan for the Kenyan economy
but also act as a benchmark strategy for many other countries in Africa that has economic and financial dynamics
similar to that of Kenya

Joab O Odhiambo, Ngare P, Weke P, Otieno RO. "Modelling of covid-19 transmission in kenya using compound poisson regression model." Journal of Advances in Mathematics and Computer Science. 2020; 35(2):101-111. AbstractWebsite

Since the inception of the novel Corona Virus Disease-19 in December in China, the spread has been massive leading World Health Organization to declare it a world pandemic. While epicenter of COVID-19 was Wuhan city in China mainland, Italy has been affected most due to the high number of recorded deaths as at 21st April, 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. The Kenyan government need to make necessary plans for those who have tested positive through self-quarantine beds at Mbagathi Hospital as a way of containing the spread of the virus. In addition, 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 regression 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 would 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 capital city but also in the other 47 Kenyan counties.

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