ArticleFrontiers in public health2026
Multidimensional analysis of pulmonary tuberculosis epidemiological characteristics in Jining City from 2010 to 2024: an integrated study based on spatial clustering, trend regression, and age-period-cohort modeling.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To understand the spatiotemporal distribution characteristics, epidemiological features, and long-term trends in the incidence of pulmonary tuberculosis in Jining City from 2010 to 2024, and to provide scientific evidence for the formulation of targeted prevention and control strategies. Methods: Spatial autocorrelation and spatiotemporal scan analyses were used to study the spatial distribution characteristics and spatiotemporal clustering of tuberculosis incidence in Jining City. The Joinpoint regression and age-period-cohort models were employed to analyze the long-term trends of tuberculosis incidence, as well as the impact of age, period, and birth cohort. Results: From 2010 to 2024, 43,816 tuberculosis cases were reported in Jining City, with an overall average annual incidence rate of 35.31 per 100,000. Global spatial autocorrelation showed that cases were randomly distributed in most years, with significant clustering only in 2010, 2016, and 2019. Local autocorrelation analysis indicated that the central and southwestern areas of Jining City exhibited low-low clustering, while the northern and northeastern areas showed high-low and high-high clustering. Spatiotemporal scan analysis further detected various spatiotemporal clusters in certain regions, including Sishui County, Qufu City, Wen Shang County, and Jiaxiang County. The Joinpoint regression model indicated a significant downward trend in incidence across all groups, with the fastest average decrease observed among males. The age-period-cohort model showed that age, period, and cohort all significantly influenced the incidence of tuberculosis. Net drift and local drift values confirmed a declining trend, with the slowest decrease in the 20-24 age group. The age effect demonstrated an initial rise followed by a decline in incidence rate, peaking in the 20-24-year age group; the period effect showed a declining trend in tuberculosis risk over time in Jining City; the cohort effect indicated that the later the birth cohort, the lower the risk of developing tuberculosis. Conclusion: Although the incidence of tuberculosis in Jining City is on a declining trend, localized hotspots and certain spatiotemporal clusters have been identified in specific counties and periods. Furthermore, the disease incidence is influenced by factors such as age, period, and cohort. Further targeted measures should be taken to curb disease spread.
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