Tuberculosis (TB) remains one of the major infectious diseases requiring serious attention in regional health policy planning. This study aims to model the number of TB cases in North Sumatra Province using a non-linear regression approach with a Negative Binomial distribution to address overdispersed count data. Secondary data from 33 districts/cities in 2023 were analyzed, with the number of TB cases as the dependent variable and the number of poor population, GDP per capita, number of public health centers, and open unemployment rate as independent variables. The results indicate that the model is statistically significant overall; however, at the individual level, only the open unemployment rate shows a positive effect that approaches statistical significance. These findings highlight the complexity of TB determinants and suggest the need for cross-sectoral strategies focusing on employment expansion and the strengthening of primary health care services.
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