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Zhonghua Liu Xing Bing Xue Za Zhi. 2017 Nov 10;38(11):1518-1522. doi: 10.3760/cma.j.issn.0254-6450.2017.11.016.

[Spatial-temporal distribution of smear positive pulmonary tuberculosis in Liangshan Yi autonomous prefecture, Sichuan province, 2011-2016].

[Article in Chinese; Abstract available in Chinese from the publisher]

Author information

1
Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610041, China,Department of Tuberculosis Control and Prevention.
2
Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610041, China,Department of Public Health Information Service.
3
Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610041, China,Administrative Office.

Abstract

in English, Chinese

Objective: To analyze the spatial and temporal distribution of smear positive pulmonary tuberculosis (PTB) in Liangshan Yi autonomous prefecture in Sichuan province from 2011 to 2016. Methods: The registration data of PTB in 618 townships of Liangshan from 2011 to 2016 were collected from "Tuberculosis Management Information System of National Disease Prevention and Control Information System" . Software ArcGIS 10.2 was used to establish the geographic information database and realize the visualization of the analysis results. Software OpenGeoda 1.2.0 was used to conduct the analyses on global indication of spatial autocorrelation (GISA) and local indication of spatial autocorrelation (LISA). Software SaTScan 9.4.1 was used for spatio-temporal scanning analysis. Results: From 2011 to 2016, the registration rate of smear positive PTB in Liangshan declined from 56.97/100 000 (2 666 cases) to 21.11/100 000 (1 038 cases). The global spatial autocorrelation coefficient Moran's I ranged from 0.25 to 0.45 and the difference was significant (all P=0.000). Local autocorrelation analysis showed that "high-high" area covered 43, 34, 37, 34, 42 and 61 townships from 2011 to 2016, respectively, mainly in Leibo county. Spatial temporal clustering analysis found one class Ⅰ clustering in the area around Bagu township of Meigu county and two class Ⅱ clustering in the areas around Liumin and Hekou township of Huili county, respectively (all P=0.000). Conclusion: Obvious spatial temporal clustering of smear positive PTB distribution was found in Liangshan from 2011-2016. Hot spot areas with serious smear positive PTB epidemic and high spread risk were mainly found in northeastern Liangshan, including townships in Leibo and Meigu counties. Targeted TB prevention and control should be conducted in these areas.

KEYWORDS:

Smear positive; Spatial autocorrelation; Temporal-spatial cluster; Temporal-spatial scan; Tuberculosis

[Indexed for MEDLINE]

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