BMJ open · 2024
Spatiotemporal patterns and socioeconomic determinants of pulmonary tuberculosis in Dongguan city, China, during 2011-2020: an ecological study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zhang Jingfeng, Zhong Minghao, Huang Jiayin, Deng Wenjun, Li Pingyuan, Yao ZhenJiang, Ye Xiaohua, Zhong Xinguang
Аннотация
OBJECTIVE: Pulmonary tuberculosis (PTB) is a critical challenge worldwide, particularly in China. This study aimed to explore the spatiotemporal transmission patterns and socioeconomic factors of PTB in Dongguan city, China.
METHODS/DESIGN: An ecological study based on the reported new PTB cases between 2011 and 2020 was conducted in Dongguan city, China. The spatiotemporal analysis methods were used to explore the long-term trend, spatiotemporal transmission pattern and socioeconomic factors of PTB.
MAIN OUTCOME MEASURES: The number of new PTB cases.
PARTICIPANTS: We collected 35 756 new PTB cases, including 23 572 males and 12 184 females.
RESULTS: The seasonal-trend decomposition indicated a significant downward trend for PTB with a significant peak in 2017 and 2018, and local spatial autocorrelation showed more and more high-high clusters in the central and north-central towns with high incidence. The multivariate spatial time series analysis revealed that the endemic component had a leading role in driving PTB transmission, with a high total effect value being 189.40 (95% CI: 171.65-207.15). A Bayesian spatiotemporal model revealed that PTB incidence is positively associated with the agricultural population ratio (relative risk (RR) =1.074), gender ratio (RR=1.104) and the number of beds in medical institutions (RR=1.028).
CONCLUSIONS: These findings revealed potential spatiotemporal variability and spatial aggregation of PTB, so targeted preventive strategies should be made in different towns based on spatiotemporal transmission patterns and risk factors.
METHODS/DESIGN: An ecological study based on the reported new PTB cases between 2011 and 2020 was conducted in Dongguan city, China. The spatiotemporal analysis methods were used to explore the long-term trend, spatiotemporal transmission pattern and socioeconomic factors of PTB.
MAIN OUTCOME MEASURES: The number of new PTB cases.
PARTICIPANTS: We collected 35 756 new PTB cases, including 23 572 males and 12 184 females.
RESULTS: The seasonal-trend decomposition indicated a significant downward trend for PTB with a significant peak in 2017 and 2018, and local spatial autocorrelation showed more and more high-high clusters in the central and north-central towns with high incidence. The multivariate spatial time series analysis revealed that the endemic component had a leading role in driving PTB transmission, with a high total effect value being 189.40 (95% CI: 171.65-207.15). A Bayesian spatiotemporal model revealed that PTB incidence is positively associated with the agricultural population ratio (relative risk (RR) =1.074), gender ratio (RR=1.104) and the number of beds in medical institutions (RR=1.028).
CONCLUSIONS: These findings revealed potential spatiotemporal variability and spatial aggregation of PTB, so targeted preventive strategies should be made in different towns based on spatiotemporal transmission patterns and risk factors.