Determination of Hazard State of Non-Communicable Diseases Using Semi-Markov Model

Abstract: Background: The developed Semi-Markov model with Kumaraswamy Exponentiated Inverse Rayleigh distribution examined patients with hypertension, heart diseases, smoking habits and Stroke, is measured from one state to another. Materials and Methods: Patients with Non-Communicable disease described through Kumaraswamy Exponentiated Inverse Rayleigh distribution. Results: The estimated parameters of Semi-Markov model with this distribution predicted by the maximum likelihood estimation for each successive state observed significant abnormality. The data noted predicts established model is a good fit for many attributes that prevailed in studied data. The developed Semi-Markov model is a best fit for non-Communicable disease in the long run of patient’s data. Through different Exponential family distribution, one can look at for further perfect fit of patient data, which is to be estimated. Conclusion: This model can be an alternative method to estimate the effect of patient in survival analysis, where it will be effective in time consumption in medical field. Keywords: heart diseases, hypertension, Semi-Markov processes, smoking, stroke.Original Articl