Spatial aggregation of 438 human infections with avian influenza A (H7N9) in the mainland of China
10.3760/cma.j.issn.0254-6450.2014.11.021
- VernacularTitle:中国大陆地区438例人感染H7N9禽流感空间聚集性分析
- Author:
Jicheng XU
1
;
Shuiping HUANG
;
Weiwei XIAO
;
Jun HU
;
Hui SUN
Author Information
1. 221004,徐州医学院公共卫生学院
- Keywords:
Human infection with the H7N9 avian influenza;
Geographic information system;
Spatial analysis;
Trend surface analysis
- From:
Chinese Journal of Epidemiology
2014;35(11):1270-1274
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the spatial distribution and growing trend of 438 human infection with the H7N9 avian influenza virus in mainland China,and to provide evidence for developing scientific prevention and control strategies.Methods 438 human infection with the avian influenza A (H7N9) cases from February 2013 to May 2014 in mainland China were studied and data collected to establish a database for the development of geographic information system.Trend surface analysis and spatial autocorrelation analysis were used to study the spatial distribution.Descriptive epidemiological method was utilized to analyze the demographic characteristic.Results From June 2013 to May 2014,cases had an overall national increase,but significantly decreasing in Shanghai.A trend surface was established for human infection with avian influenza A (H7N9) in the mainland of China,showing that the incidence was increasing obviously from north to south and the line slope declined from west to east.Distribution pattern of the cases varied within different time series and regional levels.The overall Moran' s I coefficient of the provincial level from February to May in 2013 and the coefficient of the city level from June 2013 to May 2014 were 0.144 718 and 0.117 468,respectively,with the differences statistically significant (P＜0.05).According to the analysis of the local autocorrelation and hot spot,northern Zhejiang and southern Guangdong showed high spatial clusters of human infection with avian influenza A(H7N9) (Z＞2.58).Conclusion From February 2013 to May 2014,the spatial correlation at the provincial level decreased.However,the spatial correlation and the numbers of hot spots at the city level were both increasing.Effective measures should be taken accordingly,following the distributive characteristics.
