The primary aim of this research is to estimate the proportion of long-term survivors among HIV/AIDS patients receiving Antiretroviral therapy (ART). A cure fraction model has been used to accomplish the same. Although, cure fraction models are extensively being used in oncology for modeling survival time data with long-term survivors, but there are minimal research that considers this model in HIV/AIDS set up. Here, we have defined survival time under the purview of CD4 cell counts. CD4 is considered to be disease marker for HIV/AIDS patients. Bayesian Analysis of the various mixture and non-mixture cure fraction models under exponential, generalized exponential. Raleigh, Weibull, Exponentiated Weibull distributions are exemplified using a real data set. Effect of prognostic factors like baseline CD4, age, sex, medication on cure fraction are studied. The MLE’s are obtained using Gibbs sampling techniques with MCMC method in Open BUGS package. Convergence diagnostic (like trace plots, density plots & MC errors) are used to detect in any unexpected anomalies in MCMC output. The DIC (Deviance information criterion) has been utilized to compare the efficiency of different models. A real-life data set from the ART center of RML hospital, Delhi, India are taken for this study
