2010—2018年南宁市农村地区结核病空间分布特征分析

Analysis on spatial distribution of tuberculosis in rural areas of Nanning from 2010 to 2018

摘要:

目的：分析南宁市农村地区2010-2018年结核病的空间分布模式，探索聚集区域，为结核病防治提供科学依据。方法：利用ArcGIS 10.8 建立南宁市农村地区2010-2018年结核病疫情数据库，绘制空间分布地图，并进行全局自相关、局部自相关及热点分析。结果：南宁市农村地区2010-2018年年均报告发病率空间分布图显示：年均报告发病率高的乡镇为金钗镇和洋桥镇。全局自相关分析显示：2010-2018年Moran’s I指数为0.18，（Z=2.33,P=0.02），提示南宁市农村地区结核病在区域分布中存在空间聚集性。局部自相关分析显示：南宁市农村地区结核病呈高-高聚集、低-低聚集、高-低聚集及低-高聚集模式，其中金钗镇、里当瑶族乡为高-高聚集区域，黎塘镇、新福镇及陶圩镇为低-低聚集区域。局部热点分析显示：金钗镇、洋桥镇和里当瑶族乡“热点”区域。 结论：南宁市农村地区结核病疫情存在空间聚集性，高发区域为金钗镇、洋桥镇和里当瑶族乡，低发区域为黎塘镇、新福镇及陶圩镇。

Abstract:

Objective To analyze the spatial distribution of tuberculosis in rural areas of Nanning City from 2010 to 2018,and to explore the clustering areas, and provide evidence for tuberculosis prevention and treatment. Methods The database of tuberculosis in rural areas of Nanning City from 2010 to 2018 was established by ArcGIS 10. 8 , the spatial distribution map was drawn and global autocorrelation, local autocorrelation and hotspot analysis was conducted. Results The spatial distribution map of the average annual reported incidence rates in rural areas of Nanning from 2010 to 2018 shows that the towns with high average annual incidence rates are Jinchai Town and Yangqiao Town. Global autocorrelation analysis showed that the Moran’s I index from 2010 to 2018 was 0.18 (Z=2.33, P=0.02), suggesting that tuberculosis in rural areas of Nanning had spatial clustering in the regional distribution. Local autocorrelation analysis showed that tuberculosis in rural areas of Nanning City showed high-high clustering, low-low clustering, high-low clustering and low-high clustering patterns. Among them, Jinchai Town and Lidang Yao Township were high-high clustering areas. Litang Town, Xinfu Town and Taoxu Town were low-low agglomeration areas. Local hotspot analysis showed: "hotspot" areas in Jinchai Town, Yangqiao Town and Lidang Yao Township. Conclusion There was a spatial clustering of tuberculosis epidemics in rural areas of Nanning. The high-incidence areas were Jinchai Town, Yangqiao Town and Lidang Yao Township, and the low-incidence areas were Litang Town, Xinfu Town and Taoxu Town.