Abstract

BackgroundThe 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.MethodsUsing 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.ResultsThe 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.ConclusionsThe 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.

Highlights

  • The report of the fifth national tuberculosis (TB) epidemiological survey in P

  • Results of cross-validation For smear positive pulmonary TB (PTB) prevalence, the best geostatistical method was K-Bessel model of ordinary cokriging with global detrending, with true anisotropy and with Human development index (HDI) and elevation as covariables

  • For Mycobacterium positive PTB prevalence, the best one was J-Bessel model of ordinary cokriging with global detrending, with true anisotropy and with HDI and elevation as covariables

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Summary

Introduction

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. 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. In 2010, Disease Control Bureau of the Ministry of Health, People’s Republic of China R. China) and Chinese Center for Disease Control and Prevention implemented the fifth national tuberculosis (TB) epidemiological survey, TB prevalence relative to another. It is necessary to understand the patterns on spatial heterogeneity of PTB prevalence using statistic data sampled from the fifth national TB epidemiological survey and explore factors of spatial heterogeneity in P.

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