International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2017, Vol. 2, Issue 2, Part A

A statistical modelling for viral replication in the CD4+T cells dynamic by bayesian methodology


Author(s): Dr. G Meenakshi and S Lakshmi Priya

Abstract: A proper treatment or effective vaccine for HIV positive patients is still a dream to the doctors and Scientist although several drugs have been used for the chemotherapy of HIV infections. Monitoring the patients CD4+T count and viral load for every period is expensive and also has some practical difficulties. For avoiding this kind of problem, the prediction of viral load is very much essential for the treatment of patients. In the existing HIV Replication models, most of them are non- linear mixed effects models. Some of the models are developed by the differential equations. From these models finding the solution of the parameters are very difficult. Some of the researchers used the Bayesian methodology in which selection of prior distribution is improper. So, an attempt has been made in this research, finding the predictive distribution of viral load for the future period using Exponential Distribution as Prior by the Bayesian methodology.

Pages: 43-49 | Views: 812 | Downloads: 28

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How to cite this article:
Dr. G Meenakshi, S Lakshmi Priya. A statistical modelling for viral replication in the CD4+T cells dynamic by bayesian methodology. Int J Stat Appl Math 2017;2(2):43-49.
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International Journal of Statistics and Applied Mathematics