Abstract:

Objective To analyze the spatial distribution characteristics of tuberculosis (TB) at the street/township level in Guangzhou from 2014 to 2018. Methods The information of 54213 TB patients who reported on the TB infectious disease report card in Guangzhou City from 2014 to 2018 was collected through “China Disease Prevention and Control Information System and Infective Diseases Management Information System”. Based on the street/township level, the spatial distribution map was drawn, and then the trend analysis as well as the global and local spatial autocorrelation analysis were conducted to explore the spatial distribution pattern and hot areas of TB. Results The average annual reported incidence rate of TB was 79.87/100000 (54213/67876663) in Guangzhou from 2014 to 2018. The three-dimensional trend analysis chart showed that the average annual reported incidence of TB in Guangzhou from 2014 to 2018 gradually decreased from the west to the east, and showed a weak “n” shape in the north-south distribution, that was, high in the middle and low in the north and south. At the street/township level, the overall incidence of TB in Guangzhou from 2014 to 2018 showed spatial clustering. The values of Moran’s I were 0.093, 0.275, 0.137, 0.091 and 0.107, respectively, and Z values were 2.028, 5.879, 2.949, 2.156 and 2.619, respectively, with P values of 0.034, 0.001, 0.008, 0.027, and 0.005, respectively. General Getis-Ord G index was 0.006, Z value was 2.632, and P value was 0.008, which suggested that the spatial distribution of the annual reported incidence of TB in Guangzhou presented a “high-high” clustering. According to the local spatial autocorrelation index aggregation map, the high-high clusters included 7 streets as follows: Zhuguang, Hongqiao, Datang and Beijing Streets in Yuexiu District, Zhuji, Xintang and Chebei Streets in Tianhe District. Partial hot/cold spot analysis showed that there were 29 hotspot streets, mainly concentrated in Tianhe and Yuexiu Districts. Conclusion Incidence rates of TB displayed spatial clustering at the street/township level in Guangzhou during 2014 to 2018, with the overall performance of “high-high” clustering pattern, and the incidence hotspots were mainly concentrated in Tianhe and Yuexiu Districts.

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