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The goal of this study was to use frequentist and Bayesian methodologies
to adjust some probability distributions for survival time in HIV/AIDS patients in Mato Grosso do Sul, Brazil, followeds from 2009 to 2018. The influence of explanatory variables on the response variable can be calculated using regression models. The Log-Normal distribution was shown to be the most parsimonious for the data using the Akaike information criterion (AIC) values and the maximum likelihood logarithm.
Two regression models were built based on the described methodologies, converging to the same interpretation of the explanatory variables: sex, race, education, and injecting drug use. The median time to death from HIV/AIDS is approximately: 2.1 higher for females, 1.8 higher for white people, 5.4 higher for individuals with more than 8 years of education, 5.5 higher for individuals who do not use injecting drugs, according to the study. Based on the interpretations of the coefficients of the model parameters, the need for prevention and early diagnosis policies focused on groups that have a shorter median survival time after notification of HIV infection can be discussed.
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