Abstract:

Objective Based on the data of the standardized incidence ratio (SMR) of smear-positive pulmonary tuberculosis (PTB) in 98 districts (counties) in Xinjiang Uygur Autonomous Region (Xinjiang) from 2011 to 2015, the spatial and temporal distribution pattern of PTB risk was explored using spatial epidemiological methods. Methods The information of 57 700 cases of smear-positive PTB in Xinjiang from 2011 to 2015 was obtained through the ‘China Disease Prevention and Control Information System and Infective Diseases Management Information System’. ArcGIS 10.2 software was used for geospatial analysis to create a TB SMR distribution map, the global Moran I index was calculated to explore the spatial autocorrelation effect of smear-positive PTB. The Kriging interpolation method was used to construct the prediction model. Results The SMR of smear-positive PTB in Xinjiang showed spatial autocorrelation. From 2011 to 2015, the values of Moran I were 0.261, 0.372, 0.376, 0.248 and 0.297, respectively, and Z values were 10.188, 14.424, 14.798, 9.762 and 11.594, respectively, with all P values <0.001. The Ordinary Kriging model and the Bayesian Kriging model predicted the distribution in line with the actual distribution law. After cross-validation, the fitting effect of the two models was ideal. The Bayesian Kriging model (RMSE ranged 0.382-0.484) was slightly higher than the Ordinary Kriging model (RMSE ranged 0.379-0.522). Conclusion The SMR of smear-positive PTB in Xinjiang from 2011 to 2015 showed spatial clustering at the district (county) level, and SMR showed a downward trend in volatility. Kriging interpolation analysis is helpful in estimating the risk of active PTB in Xinjiang.

Key words: Tuberculosis, pulmonary, Spatial autocorrelation analysis, Epidemiologic study characteristics as topic