Spatio-Temporal Pattern and Socio-economic Influencing Factors of Tuberculosis Incidence in Guangdong Province: A Bayesian Spatiotemporal Analysis

Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR ), 0.91; 95% Confidence Interval ( CI ): 0.86-0.98], more the ratio of licensed physicians and physician ( RR , 0.94; 95% CI : 0.90-0.98), and higher per capita public expenditure ( RR , 0.94; 95% CI : 0.90-0.97), with a marginal effect of population density ( RR , 0.86; 95% CI : 0.86-1.00). Conclusion The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.