Abstract:
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CD4 cells progression rate and patients' death rate are key indicators of the progression of HIV disease. There are two facts about CD4 cell counts; first, there is a substantial measurement error due to imprecise measurement techniques. Second, the number of CD4 cells varies over time because of the short-term variations in the immune system. These two factors lead to uncertainty about the progression state of HIV disease and make a hidden Markov model (HMM) an appropriate approach to uncover the disease progression. We use an HMM framework and devise a new MCMC estimation method to determine transition probabilities across different states of disease progression. We apply the model to a dataset of a panel of more than 30000 Chinese patients over 7 years. We gain insights about HIV progression, treatment effect, and death rate across various subgroups of patients based on demographic information.
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