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141-150

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- Department of Mathematical Sciences, BGSB University, Rajouri, J and K 185 234, India

author

- Department of Mathematics, S.V. Subharti University, Meerut, UP 250005, India

author

- Department of Mathematics, Govt. P.G. College Rajouri, J and K 185 131, India

References

- [1] Bature, R.S., Obiniyi, A.A., Absalom, E.E. and Sule, O.O. (2010). Markov chain simulation of HIV/AIDS movement pattern. International Journal of Computer Science and Information Security 8(2), pp.156-167.
- [2] Bortolussi, L. (2016). Hybrid behaviour of Markov population models. Information Computation 247, pp. 37-86.
- [3] Debanne, S.M., Bielefeld, R.A., Cauthen, G.M., Daniel, T.M. and Rowland, D.Y. (2000). Multivariate Markovian modeling of tuberculosis: Forecast for the United States. Emerging Infectious Diseases 6(2), pp. 148-157.
- [4] Gentleman, R.C., Lawless, J.F., Lindsey, J.C. and Yan, P. (1994). Multi-state Markov models for analyzing incomplete disease history data with illustrations for HIV disease. Statistics in Medicine 13(8), pp. 805-821.
- [5] Giamberardino, P.D. and Iacoviello, D. (2017). Optimal control of SIR epidemic model with state dependent switching cost index. Biomedical Signal Processing and Control 31, pp. 377-380.
- [6] Greenhalgh, D.Y. and Mao, L.X. (2016). Modelling the effect of telegraph noise in the SIRS epidemic model using Markovian switching. Physica A: Statistical Mechanics and its Applications 462, pp. 684-704.
- [7] Lee, S., Ko, J., Tan, X., Patel, I., Balkrishnan, R. and Chang, J. (2014). Markov chain modelling analysis of HIV/AIDS progression: A race-based forecast in the United State. Indian Journal of Pharmaceutical Sciences 76(2), pp. 107-15.
- [8] Longini, I.M.J., Clark, W.S., Byers, R.H., Ward, J.W., Darrow, W.W. and Lemp, G.F. (1989). Statistical analysis of the stages of HIV infection using a Markov model. Statistics in Medicine 8(7), pp. 831-843.
- [9] Oyewole, O.A. (2014). On the use of discrete-time Markov process for HIV/AIDs epidemic modeling. American Journal of Applied Mathematics 2(1), pp. 21-28.
- [10] Preeti. (2017). Queueing Modeling of a SAIS Model with Alert, Infection and Vaccination. Journal of Basic and Applied Engineering Research 4(1), pp. 81-84.
- [11] Shekhar, C., Raina, A.A. and Kumar, A. (2016). A brief review on retrial queue: Progress in 2010-2015. International Journal of Applied Sciences and Engineering Research 5(5), pp. 324-336.
- [12] Shekhar, C., Raina, A.A., Kumar, A. and Iqbal, J. (2017). A survey on queues in machining system: progress from 2010 to 2017. Yugoslav Journal of Operations Research 27(4), pp. 391-413.
- [13] Sweeting, M.J., Farewell, V.T., De, A.D. (2010). Multi-state Markov models for disease progression in the presence of informative examination times: An application to hepatitis C. Statistics in Medicine 29(11), pp. 1161-1174.
- [14] Tan, W.Y. and Tang, S.C. (1994). A general Markov model of the HIV epidemic in populations involving both sexual contact and IV drug use. Mathematical and Computer Modelling 19(10), pp. 83-132.
- [15] Trapman, P. and Bootsma, M.C.J. (2009). A useful relationship between epidemiology and queueing theory: The distribution of the number of infectives at the moment of the first detection. Mathematical Biosciences 219(1), pp. 15-22.

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bwmeta1.element.psjd-b984d68b-0c38-4556-ab29-b9c445ed20da