Spatial variations of pulmonary tuberculosis prevalence co-impacted by socio-economic and geographic factors in People's Republic of China, 2010

被引:28
作者
Li, Xin-Xu [1 ,2 ]
Wang, Li-Xia [2 ]
Zhang, Hui [2 ]
Jiang, Shi-Wen [2 ]
Fang, Qun [2 ]
Chen, Jia-Xu [1 ]
Zhou, Xiao-Nong [1 ]
机构
[1] Chinese Ctr Dis Control & Prevent, WHO Collaborating Ctr Malaria, Natl Inst Parasit Dis, Key Lab Parasite & Vector Biol,Minist Hlth, Shanghai 200025, Peoples R China
[2] Chinese Ctr Dis Control & Prevent, Natl Ctr TB Control & Prevent, Beijing 102206, Peoples R China
关键词
Pulmonary tuberculosis; Spatial variations; Impact factor; Cokriging; China; HIGH-ALTITUDE; INFECTION; PATTERNS; AREA; PERU;
D O I
10.1186/1471-2458-14-257
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The report of the fifth national tuberculosis ( TB) epidemiological survey in P. R. China, 2010, roughly showed that pulmonary TB (PTB) prevalence was higher in western China than in central and eastern China. However, accurately estimating the continuous spatial variations of PTB prevalence and clearly understanding factors impacting on spatial variations of PTB prevalence are important for allocating limited resources of national TB programme (NTP) in P. R. China. Methods: Using ArcGIS Geostatistical Wizard (ESRI, Redlands, CA), an evaluation was performed to decide that which kriging and cokriging methods along with different combinations of types of detrending, semivariogram models, anisotropy and covariables (socio-economic and geographic factors) can accurately construct spatial distribution surface of PTB prevalence using statistic data sampled from the fifth national TB epidemiological survey in P. R. China, 2010, and then the evaluation results were used to explore factors of spatial variations. Results: The global cokriging with socio-economic and geographic factors as covariables proved to be the best geostatistical methods for accurately estimating spatial distribution surface of PTB prevalence. The final continuous surfaces of PTB prevalence distribution demonstrated that PTB prevalence were lower in Beijing, Tianjin, Shanghai and southeastern coast China, higher in western and southwestern China, and crossed between low and high in central China. Conclusions: The predicted continuous surface perspicuously illustrated the spatial variations of PTB prevalence that were co-impacted by socio-economic and geographic factors, which can be used to better allocate the always limited resources of NTP in P. R. China.
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页数:12
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