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Updated: Mar 18, 2026
The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
[Spatial distribution characteristics analysis on multidrug-resistant tuberculosis cases in Zhejiang province,
1Department of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Collaborative Innovation Center of Social Risk Governance in Health, Shanghai 200032, China.
Objective:
To analyze the spatial distribution characteristics of multidrug-resistant (MDR) tuberculosis (TB) cases in Zhejiang province in 2010-2012.
Methods:
Data on MDR-TB cases in Zhejiang province were collected and linked to the digital map at the county and district levels. ArcGIS 10.0 software was used for spatial analysis.
Results:
RESULTS from the spatial autocorrelation analysis showed that spatial aggregation appeared in MDR-TB distribution during 2010-2012 while local Moran's I spatial autocorrelation analysis identified several "high incidence regions" (Wuxing, Deqing, Yuhang, Gongshu, Jianggan, Xiaoshan, Yuecheng, Shaoxing Shengzhou, Changshan, Kecheng), and "low incidence region" (Haishu). Through Getis-Ord General G spatial autocorrelation analysis, 18 "positive hotspots" (Wuxing, Nanxun, Deqing, Yuhang, Shangcheng, Xiacheng, Gongshu, Jianggan, Binjiang Xiaoshan Xihu, Haining, Yuecheng, Shaoxing, Zhuji, Shengzhou, Kecheng and Suichang) and 11 "negative hotspots" (Nanhu, Haiyan, Cixi, Dinghai, Zhenhai, Jiangbei, Jiangdong, Beilun, Yinzhou, Fenghua, and Yueqing) were identified.
Conclusions:
Spatial analysis on MDR-TB incidence implied the spatial aggregation in Zhejiang province. Data showed that the hotspots with high population density and human movement were under progressive expansion.
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