ArticleBMC public health2025
Spatiotemporal distribution and detection of spatial clusters of tuberculosis in Hubei Province, China using FleXScan (2017-2023).
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Epidemiological Distribution Characteristics of Tuberculosis Among Older Adults in Chongqing (2020-2024): Spatial-Temporal Analysis.JMIR public health and surveillance · 2026Article
- Integrating disease mapping and flexible scan statistics to identify and visualize spatial clusters.PloS one · 2026Article
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6 authors.
Funding
Abstract
backgroundThis study investigates the spatiotemporal distribution and spatial clustering of tuberculosis(TB) in 103 counties of Hubei Province, China, using spatial scan statistics. By identifying high-risk areas and temporal trends, the findings will provide a scientific foundation for targeted TB prevention and control strategies.
methodsThis study employed the FleXScan method to detect spatial clusters of pulmonary tuberculosis cases in Hubei Province and identify statistically significant high-risk areas. Combined with Geographic Information System (GIS) spatial analysis techniques, we visualized the spatiotemporal distribution patterns and dynamic changes of these high-risk tuberculosis clusters.
resultsBetween 2017 and 2023, the incidence rate of Hubei Province decreased from 68.28 to 54.54 per 100,000 population. Using the FleXScan method, significant spatial clustering of TB cases was identified. The most likely clusters (MLCs) were primarily located in the western and southwestern regions, including Enshi Prefecture, the Shennongjia Forestry District, and parts of Yichang City. Notably, Enshi Prefecture maintained a persistently high average annual incidence of 110.78 per 100,000 with no significant temporal decline, highlighting the urgent need for targeted prevention and control measures.
conclusionTB in Hubei Province exhibits significant spatiotemporal heterogeneity. Its epidemiology is influenced by multiple factors, including economic conditions, geographical environment, healthcare access, and social determinants. Control strategies should take into account differences both between regions and within individual regions to accurately identify high-risk areas.
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