Revisiting connections of social, economic, and environmental factors on PM2.5 and NO2 concentrations regarding tuberculosis cases using Gaussian Bayesian network

Environmental health degradation continues to pose serious threats to human well-being, driven by intricate interplays among social, economic, and environmental determinants. West Java, Indonesia, exemplifies this crisis as a region burdened by severe air pollution and the highest incidence of tuberculosis (TB) in the country. This study investigates how key indicators across the three pillars of sustainable development contribute to air pollution levels and TB case in the region. Utilizing a Gaussian Bayesian Network model with data from satellite imagery and official statistics, we unravel the probabilistic and causal interconnections among variables such as industrial output, income level, private vehicle ownership, wind speed, ambient temperature, and population density also air pollutions and TB case. Our findings reveal that air pollutants—specifically NO2 and PM2.5—are primarily driven by industrial activity, number of private motor vehicles, and population density, which in turn have both direct and mediated effects on TB incidence. Through policy simulation scenarios, we demonstrate that coordinated and moderate reductions in industrial emissions, vehicle density, and population density can lead to measurable improvements in air quality and public health outcomes. These insights offer evidence-based pathways to inform integrated environmental and health policy for sustainable urban development.