Abstract
Profiting from a series of anti-tuberculosis programs in China, the number of tuberculosis (TB) cases has diminished dramatically in the past decades. However, long-term spatial-temporal variations, regional trends of prevalence, and mechanisms of determinant factors remain unclear. Age-period-cohort analysis and Bayesian space-time hierarchy statistics were conducted to identify high-risk populations and areas in mainland China, and the geographical detector model was used to evaluate the important drivers of the disease. The prevalence of pulmonary TB has declined from 73.3/100,000 in 2004 to 55.45/100,000 in 2018. A bimodal distribution was found in age groups, and the birth cohorts before 1978 had relative higher risk. The high-risk areas were mainly distributed in western China and south-central China, and several provinces in eastern China showed a potential increasing trend, including Beijing, Shanghai, Liaoning, and Guangdong province. The index of night light (Q = 0.46), the population density (Q = 0.41), PM10 (Q = 0.38), urbanization rate (Q = 0.32), and PM 2.5 (Q = 0.31) contributed substantially to the spatial distribution of pulmonary tuberculosis. The identifications of epidemic patterns, high-risk areas and influence factors would help design targeted intervention measures to achieve milestones of the end TB strategy.
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Data availability
Data and materials will be made available on request to the corresponding author of Kun Liu.
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This work was supported by the National Natural Science Foundation of China (grant number: 82273689 and 81803289).
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Xiao Wei, Ting Fu, Di Chen, Wenping Gong, Shuyuan Zhang, Yong Long, and Xubin Wu. The first draft of the manuscript was written by Xiao Wei, Zhongjun Shao, and Kun Liu. All authors commented on previous versions of the manuscript, and all authors read and approved the final manuscript.
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Wei, X., Fu, T., Chen, D. et al. Spatial-temporal patterns and influencing factors for pulmonary tuberculosis transmission in China: an analysis based on 15 years of surveillance data. Environ Sci Pollut Res 30, 96647–96659 (2023). https://doi.org/10.1007/s11356-023-29248-4
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DOI: https://doi.org/10.1007/s11356-023-29248-4