Risk estimate of COVID-19 spread between poverty clusters in Africa using Markov chain modeling

From the beginning of COVID-19 pandemic in 2020, countries around the world are taking measures to control it. Africa continent is less impacted and this is an element that many researchers have been working on. In addition, many people in those countries doubt of conspiracy about the pandemic and are quite hesitant for the vaccine. This situation needs deeper checking to know if they are still at risk. In this work, a Markov chain model is used to understand the behavior of COVID-19 spread among poverty classes in Africa.We used data sets of new cases and poverty level from ”Our World In Data” and ”IndexMundi” data portal. The findings revealed that rich countries are likely to face higher number of cases. However, the poorest countries are still at risk to experience that very high number of cases. In addition, the forecasts of COVID-19 spread in long run term among those countries have been computed.