ArticleBMJ open2024
Spatiotemporal patterns and socioeconomic determinants of pulmonary tuberculosis in Dongguan city, China, during 2011-2020: an ecological study.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Spatial distribution, clustering patterns, and economic burden of comorbidities among hospitalised pulmonary tuberculosis patients in Guangdong province: a spatial epidemiological study based on inpatient big data.Journal of global health · 2026Article
- Spatiotemporal Patterns and Socioeconomic Determinants of Pulmonary Tuberculosis in Piauí, Northeast Brazil, 2001-2024.Tropical medicine & international health : TM & IH · 2026Article
- Observational
- Global, regional, and national burden of tuberculosis and attributable risk factors for 204 countries and territories, 1990-2021: a systematic analysis for the Global Burden of Diseases 2021 study.BMC public health · 2024Article
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Authors and funding
8 authors.
Funding
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Abstract
objectivePulmonary 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/
designAn 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 measuresThe number of new PTB cases.
participantsWe collected 35 756 new PTB cases, including 23 572 males and 12 184 females.
resultsThe 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).
conclusionsThese 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.
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