OBJECTIVE: To analyze the spatial distribution of hemorrhagic fever with renal syndrome (HFRS) in China by geographic information system, and to draw up a map on HRFS risk areas. METHODS: A set of database was set up using the information collected and linked to electronic maps of China in a software ArcGIS 8.01 from 41 HFRS surveillance sites during 1995 - 1998. A HFRS spatial distribution model was developed using inverse distance weighted interpolation of ArcGIS's spatial analysis method. The normalized difference vegetation index (NDVI) in each HFRS surveillance site was extracted from SPOT4 satellite vegetation imagery. Correlation analysis was performed through SPSS 10.0 to analyze the association between NDVI and HFRS incidence, HFRS risk areas were mapped under different colors. RESULTS: Spatial distribution model from HFRS surveillance sites showed that HFRS foci mainly presented in the Heilongjiang River drainage, the middle and lower reaches of the Yellow River, the middle and lower reaches of the Yangtze River, and the Jinghang grant Canal-Huaihe River drainage. It was consistent with HFRS distribution map derived from national infectious disease reporting system. Correlation analysis indicated that HFRS incidence rates were significantly associated with NDVI (r = 0.417, P < 0.01). The HFRS risk areas was mapped according to NDVI of each surveillance site. CONCLUSION: It is promising to apply GIS technology in predication of the distribution of HFRS by establishing this prediction model.
OBJECTIVE: To analyze the spatial distribution of hemorrhagic fever with renal syndrome (HFRS) in China by geographic information system, and to draw up a map on HRFS risk areas. METHODS: A set of database was set up using the information collected and linked to electronic maps of China in a software ArcGIS 8.01 from 41 HFRS surveillance sites during 1995 - 1998. A HFRS spatial distribution model was developed using inverse distance weighted interpolation of ArcGIS's spatial analysis method. The normalized difference vegetation index (NDVI) in each HFRS surveillance site was extracted from SPOT4 satellite vegetation imagery. Correlation analysis was performed through SPSS 10.0 to analyze the association between NDVI and HFRS incidence, HFRS risk areas were mapped under different colors. RESULTS: Spatial distribution model from HFRS surveillance sites showed that HFRS foci mainly presented in the Heilongjiang River drainage, the middle and lower reaches of the Yellow River, the middle and lower reaches of the Yangtze River, and the Jinghang grant Canal-Huaihe River drainage. It was consistent with HFRS distribution map derived from national infectious disease reporting system. Correlation analysis indicated that HFRS incidence rates were significantly associated with NDVI (r = 0.417, P < 0.01). The HFRS risk areas was mapped according to NDVI of each surveillance site. CONCLUSION: It is promising to apply GIS technology in predication of the distribution of HFRS by establishing this prediction model.
Authors: Shujuan Li; Hongyan Ren; Wensheng Hu; Liang Lu; Xinliang Xu; Dafang Zhuang; Qiyong Liu Journal: Int J Environ Res Public Health Date: 2014-11-25 Impact factor: 3.390