A Markov model of COVID-19 susceptibilities, infections, recoveries and fatalities: evidence from Nigeria

Purpose - The purpose of this study is to determine the proportion of the population that will be susceptible to the COVID-19 pandemic, as well as the proportions of infections, recoveries and fatalities from the COVID-19 pandemic. Design/methodology/approach - The design was a longitudinal survey of COVID-19 infections, recoveries and fatalities in Nigeria using the data on the daily updates of the Nigeria Centre for Disease Control for the period 1 May to 23 August 2020. Markov chain analysis was performed on the data. Findings - The results showed that in the long run, 8.4% of the population will be susceptible to COVID-19 infections, 26.4% of them will be infected, 61.2% of the infected will recover and 4% will become fatal. Thus, if this pattern of infections and recoveries continue, the majority of the infected people in Nigeria will recover whilst a very small proportion of the infected people will die. Research limitations/implications - A dearth of the extant literature on the problem, especially from the management science perspective. Practical implications - Results of the study will facilitate policymakers' response to the curtailment of the pandemic in Nigeria. Social implications Curtailing the pandemic through the results of this study will assist in easing the social consequences of the pandemic. Originality/value - The proposed adjustment to the susceptibilities, infections and recoveries model through the introduction of a fourth state (fatality) to get the susceptibilities, infections, recoveries and fatalities model, signalling a point of departure from previous studies.