The spatio-temporal distribution characteristics and influencing factors of pulmonary tuberculosis in China based on a Bayesian spatio-temporal model.

Abstract

We collected data on tuberculosis incidence and influencing factors (demographic factors, socioeconomic factors, medical resources, population mobility, and air pollutants) in 31 provinces of China from 2012 to 2020. Using a Bayesian spatio-temporal model, we studied the spatio-temporal distribution and its influencing factors of tuberculosis in various regions of China from 2012 to 2020. The spatial clustering effect of tuberculosis incidence in China showed an overall increasing trend during the study period, but there was a significant decline in 2018, followed by a continued increase. High-risk areas for tuberculosis incidence are primarily concentrated in the northwest and southwest regions, while low-risk areas are mainly distributed in the eastern coastal provinces. The number of healthcare institutions (NHI), illiteracy rate (IR), rural residents' disposable income (PDIR), passenger flow (PRV), and sulfur dioxide emissions (SO2) are statistically correlated with tuberculosis incidence. The IR,PRV, and SO2 are positively correlated with tuberculosis incidence, with relative risks of 2.191, 1.759, and 1.126, respectively.