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[Objective] To the principles and methods of application of spatial epidemiology to describe and analyze the characteristics and developing variation Dali schistosomiasis, the spatial distribution of the snails, explore the impact of environmental factors, and provide technical support for schistosomiasis control and monitoring. [Material] 1. Collected in Yunnan Province from 1998 to 2008, Dali City from 2002 to 2008 and 2001 2008 Eryuan County schistosomiasis illness and snail status information. Buy the afternoon of April 22, 2008 4 points cover both Landsat TM satellite imagery and basic electronic map of Yunnan Province. 【Methods】 1. Geographic Information System (GIS) database to establish using Envi4.2 software to extract vegetation index, soil moisture, land use types using Erdas9.2 software to extract the surface temperature environment, alternative indicators, four indicators in ArcGIS9.2 software created raster database of schistosomiasis illness and snail status information in Excel, enter into a spreadsheet and electronic maps together to create a vector database. descriptive analysis of the descriptive analysis using GIS Yunnan Dali City from 2002 to 2008 schistosomiasis between distribution. Statistical analysis utilize ArcGIS9.2. Spss16 Satscan7.0 statistical analysis software to analyze the characteristics space distribution of of Dali City schistosomiasis and snail distance to the water system, and the infection rate of snails farm cattle infection rates, the popular village and the infection rate and environmental alternative indicators of vegetation index, soil moisture and snail density for analysis spss correlation. Kriging analysis of simulation-based sampling point interpolation geospatial statistical methods to predict the distribution of snail. Weight weight suitability model to extract survival of snails range using GIS suitability model to determine the most suitable for the survival of snails, times suitable for the survival of snails range and not suitable for the survival of snails range. [Results] 1, visualization of geographic information systems describe Dali City, Yunnan Province from 2002 to 2008 Eryuan County from 2001 to 2008, schistosomiasis, snail distribution situation, such as snails area, the number of cases, the infection rate . 2, the establishment of Yunnan Province from 2002 to 2008 the schistosomiasis geographic information system database. 3, statistical analysis of the results: the concentration of cases, the distribution of the town of Dali Yunfeng basic Dali City, popular village along the river system distribution the snail distribution has obvious geographical, temporal and spatial aggregation. Infection rate of snails (X1), the farm cattle infection rate (X2), the infection rate (y) was positively related to negative correlation with the distance from the water system, the regression model: y = x X1 0.232 3.723 0.687 × X2, F = 39.166, P lt; 0.001, coefficient of determination, R2 = 0.471, water system distance did not enter the model. This model only explained 47.1% of the total variance, is not enough to just above factors modeling. 4, by means of remote sensing images to extract vegetation index, soil moisture and surface temperature and other environmental alternative indicators, drawn snail density vegetation index (correlation coefficient 0.45) and positively correlated with soil moisture (correlation coefficient 0.412) into a negative correlation (correlation with surface temperature coefficient -0.325) and p lt; 0.05 5 snails do not meet the required sample statistically uniform, independent distribution of features, has a strong geographical, temporal and spatial aggregation, so using GIS kriging interpolation of geostatistical The snail density method to simulate and predict snail density distribution of the entire study area, after the validation of the semi-difference function can be explained 74.55% of the total variance, the average standard error of 13.13%. Determined by the weight of the land information system suitability model most suitable for survival of snails, suitable for the survival of snails range and not suitable for the survival of snails range. [Conclusion] The research shows that geographic information system can be more intuitive, the image dynamically show the prevalence of schistosomiasis and snail distribution. Vegetation index, surface temperature, soil moisture, and snail density strong, can be applied to the hilly regions snails monitoring. Geographic information system the Kriging modeling and the right weight suitability models and high reliability, the reaction to some extent on the actual distribution of the snails, the local schistosomiasis prevention has some significance.
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