The Human Immunodeficiency Virus (HIV) poses a significant challenge for every country and remains one of the primary issues in global health, requiring serious attention. HIV is a virus that attacks the human immune system, weakening the body’s ability to combat infections. This study aims to analyze the influence of various social factors on the mortality rate of HIV patients in Indonesia using Poisson regression and Negative Binomial regression. These models are chosen because they are well-suited for count data, such as mortality rates. The research data includes information on the number of HIV-related deaths across various provinces in Indonesia, with social variables as predictors, such as population density, the percentage of elderly population, inadequate sanitation access, education levels, and unemployment rates.
                        
                        
                        
                        
                            
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