Modelling Infectious Diseases Using Markov Chain

Authors

  • Kehinde Adigun Department of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363
  • Ayan Adeleke Department of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363
  • Oluwasesan Adewusi Department of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363
  • Oluwafunmilola Olubiyi fDepartment of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363
  • Omobolaji Halid Department of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363
  • Bayowa Babalola Department of Statistics, Ekiti State University, Ado-Ekiti, Ekiti State, P.M.B. 5363

Keywords:

Infectious Diseases, Markov Chain

Abstract

This study is one of the few that has dwell on the application of Markov Chain in modeling infectious diseases in Nigeria. The study takes a look at the environmental factors that leads to the spread of infectious diseases.  This research estimates the transition pattern of the diseases, Testing the Markovian property, and how stationary the process is over the study period, the study concluded that the past history of infectious diseases will affect the future through the present state and recommended that government still need to do more in the area of sensitization and fight against infectious diseases.

References

D. C. Lay, S. R. Lay and J. J. McDonald. "Finite-State Markov Chains" (Download Only) for Linear Algebra and Its Applications” in Linear Algebra and its Applications, 5th Edition, Pearson, United States; 2016.

C. H. Jackson, L. D. Sharples, S. G. Thompson, S. W. Duffy and E. Couto. “Multistate Models for Disease progression with classification error. Based on Markov Processes Method of Estimating Rates of Transition between Stages of Diseases”. Journal of the Royal Statistical Society Series, 52(2), pp.193-209, July, 2003.

J. V. Ross and T. Taimre. “The Analysis of Hospital Infection Data using Markov Chain Models” Kings College, Cambridge, U.K. and Department of Mathematics, University of Queensland, Queensland, Australia, 2006.

A. Eisenberg. “The Application of Markov Chain Monte Carlo to Infectious Diseases”. Journal of Statistical Planning and Inference, Vol.6 (7), March, 2011.

W.H.O. Manual; The public health management of chemical incidents (2009).

K. Arnand, Y. Kapil, K. Manmeet and K. Rajesh. “Epidemology to public health intervention for preventing cardiovascular diseases: the role of translational research” Indian Journal of Medical Research, 132(5): pp. 643-650, Nov., 2010.

Epidemic (August 4, 2019). in Wikipedia. Retrieved September 11, 2019 from http://en.wiki/Epidemic

Arnoldo and Bernd, Markov Chains: Department of Biostatistics, University of Oslo, Norway and Department of Econometrics, Vrije University, Amsterdam, The Netherlands, 2015.

Downloads

Published

2019-12-01

How to Cite

Adigun, K. ., Adeleke, A. ., Adewusi, O. ., Olubiyi, O. ., Halid, O. ., & Babalola, B. . (2019). Modelling Infectious Diseases Using Markov Chain. American Scientific Research Journal for Engineering, Technology, and Sciences, 61(1), 280–288. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/5345

Issue

Vol. 61 No. 1 (2019)

Section

Articles

License

Authors who submit papers with this journal agree to the following terms.