Journal of Public Health and Diseases

This study adopts Markov chain to simulate some infectious diseases in two States (Ekiti and Oyo) of southwestern Nigeria, to describe the situations where the outcome of infectious diseases depends only on the outcome of the previous cases of the diseases. The next state of the process depends only on the present state, not on the preceding states. The main objective of this research is to model infectious diseases in Nigeria using Markov chain approach, determine the transition pattern and the fundamental matrix of the diseases, test for Markovian property of the data and how stationary the process is over time and predict the future prevalence of infectious diseases in the states. Transition probability matrix of how patients move from one state (exposed, infected, immune, recovered and dead) of the diseases to another state revealed that the inhabitants of the two States were highly exposed to infectious diseases. The estimated probabilities, p, of being infected with infectious diseases were higher (0≤p≤1) in Ekiti State than Oyo State (0≤p≤1). This indicates that higher proportions of people in Ekiti State were more infected with infectious diseases than those people living in Oyo State. The future transient state and the probability of reaching the absorption state indicate that about 98% of the populations will be exposed to infectious diseases in the future and about 50% of the dwellers will be immunized and as many that are infected will be recovered if necessary precautions are taken. The study advocates for renewed efforts in the area of prevention, environmental sanitation, vaccination and control of infectious diseases instead of spending billions of naira on curtailing the spread of diseases and medical tourism.