Modeling of COVID-19 Transmission under Markov Chains in Uganda
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Date
2022Author
Naryongo, Raphael
Onyango, Joab
Njagi, Loyford
Nakirya3, Margaret
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In this research study, we have modeled 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 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.