Spatial clustering analysis of varicella public health emergency events in Nanjing City from 2017 to 2022
10.19485/j.cnki.issn2096-5087.2024.03.008
- Author:
ZHU Lanlan
;
ZHANG Zhong
;
BIAN Zenghui
;
XU Yangting
;
SUN Hongmin
;
LIU Ting
- Publication Type:Journal Article
- Keywords:
varicella;
public health emergency event;
spatial clustering
- From:
Journal of Preventive Medicine
2024;36(3):215-218
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the spatial clustering characteristics of varicella public health emergency events in Nanjing City from 2017 to 2022, so as to provide the evidence for the development of varicella prevention and control strategies.
Methods:Data of varicella public health emergency events in Nanjing City from 2017 to 2022 were collected through Emergency Public Health Management Information System of Chinese Disease Prevention and Control Information System. The software ArcGIS 10.2 was employed for trend-surface analysis, spatial autocorrelation analysis and hotspot analysis to understand the spatial clustering characteristics of varicella public health emergency events.
Results:A total of 84 varicella public health emergency events were reported in Nanjing City from 2017 to 2022, with an average attack rate of 2.53% (2 558 cases). Ⅳ-level events were predominant, accounting for 90.48% (76 events). The trend-surface analysis showed lower incidence of varicella public health emergency events in the west of Nanjing City and higher in the east, and lower in the north and higher in the south. The global spatial autocorrelation analysis showed that there was a positive spatial correlation in varicella public health emergency events in 2017 and 2019, indicating spatial clustering (P<0.05). The hot spots were Jiangning District, Gaochun District, Yuhuatai District and Jianye District.
Conclusion:The incidence of varicella public health emergency events in Nanjing City from 2017 to 2022 has spatial aggregation, with a concentration in suburban areas such as Jiangning District and Gaochun District.
- Full text:2024072311113498442017—2022年南京市水痘突发公共卫生事件的空间聚集特征分析.pdf
