Exploring the impact of socioeconomic and natural factors on pulmonary tuberculosis incidence in China (2013–2019) using explainable machine learning: A nationwide study

Pulmonary tuberculosis (PTB) stands as a significant and prevalent infectious disease in China. Integrating 13 natural and socioeconomic factors, we conduct nine machine learning (ML) models alongside the Tree-Structured Parzen Estimator to predict the monthly PTB incidence rate from 2013 to 2019 in mainland China. With explainable ML techniques, our research highlights that population size, per capita GDP, and PM