Background: China has one of the highest tuberculosis (TB) burdens in the world. However, the unbalanced spatial and temporal trends of TB risk at a fine level remain unclear.
Objective: We aimed to investigate the unbalanced risks of pulmonary tuberculosis (PTB) at different levels and how they evolved from both temporal and spatial aspects using PTB notification data from 2851 counties over a decade in China.
Methods: County-level notified PTB case data were collected from 2009 to 2018 in mainland China. A Bayesian hierarchical model was constructed to analyze the unbalanced spatiotemporal patterns of PTB notification rates during this period at subnational scales. The Gini coefficient was calculated to assess the inequality of the relative risk (RR) of PTB across counties.
Results: From 2009 to 2018, the number of notified PTB cases in mainland China decreased from 946,086 to 747,700. The average number of PTB cases in counties was 301 (SD 26) and the overall average notification rate was 60 (SD 6) per 100,000 people. There were obvious regional differences in the RRs for PTB (Gini coefficient 0.32, 95% CI 0.31-0.33). Xinjiang had the highest PTB notification rate, with a multiyear average of 155/100,000 (RR 2.3, 95% CI 1.6-2.8; P<.001), followed by Guizhou (117/100,000; RR 1.8, 95% CI 1.3-1.9; P<.001) and Tibet (108/100,000; RR 1.7, 95% CI 1.3-2.1; P<.001). The RR for PTB showed a steady downward trend. Gansu (local trend [LT] 0.95, 95% CI 0.93-0.96; P<.001) and Shanxi (LT 0.94, 95% CI 0.92-0.96; P<.001) experienced the fastest declines. However, the RRs for PTB in the western region (such as counties in Xinjiang, Guizhou, and Tibet) were significantly higher than those in the eastern and central regions (P<.001), and the decline rate of the RR for PTB was lower than the overall level (P<.001).
Conclusions: PTB risk showed significant regional inequality among counties in China, and western China presented a high plateau of disease burden. Improvements in economic and medical service levels are required to boost PTB case detection and eventually reduce PTB risk in the whole country.
Keywords: Bayesian; China; TB; cases; disease burden; incidence; infectious disease; notification data; notification rates; pattern; public health; pulmonary tuberculosis; regional inequality; risk; spatial data; spatiotemporal pattern; trend; tuberculosis; unbalanced.
©Maogui Hu, Yuqing Feng, Tao Li, Yanlin Zhao, Jinfeng Wang, Chengdong Xu, Wei Chen. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 01.07.2022.