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• W4206325055 abstract "<sec> <title>BACKGROUND</title> China has one of the highest tuberculosis burdens in the world. However, the unbalanced spatial and temporal trends of the tuberculosis risk at fine level remain unclear. </sec> <sec> <title>OBJECTIVE</title> We intend to investigate the unbalanced risks of PTB at different levels and how they evolved in both temporal and spatial aspects using PTB notification data from 2851 counties over a decade in China. </sec> <sec> <title>METHODS</title> County-level notified pulmonary tuberculosis (PTB) case data were collected from 2009 to 2018 in mainland China. A Bayesian hierarchical model was constructed to analyse the unbalanced spatio-temporal patterns of PTB notification rates from 2009 to 2018 at subnational scales. </sec> <sec> <title>RESULTS</title> From 2009 to 2018, the number of notified PTB cases in mainland China decreased from 946,086 to 747,700. Xinjiang had the highest PTB notification rate, with a multi-year average of 155/100,000, followed by Guizhou (117/100,000) and Tibet (108/100,000). The overall average notification rate in mainland China was 44 per 100,000 people. The relative risk (RR) for PTB showed a steady downward trend. The rates in Gansu and Shanxi decreased by more than 50%. However, the RR for PTB in the western region (such as counties in Xinjiang, Guizhou, and Tibet) was significantly higher than those in the eastern and central regions, and the decline rate of the RR for PTB was lower than the overall level. </sec> <sec> <title>CONCLUSIONS</title> PTB risk has significant regional inequality at counties in China, and the western China presents a high plateau of the disease burden. Improvements in economic and medical service levels are required to boost PTB cases detection and eventually reduce PTB risk in the whole country. </sec>" @default.
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• W4206325055 date "2022-01-06" @default.
• W4206325055 modified "2023-10-16" @default.
• W4206325055 title "The unbalanced risk of pulmonary tuberculosis in China at subnational scales (Preprint)" @default.
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• W4206325055 doi "https://doi.org/10.2196/preprints.36242" @default.
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