论文部分内容阅读
目的探索应用GIS预测模型来预测不同区域血吸虫病流行程度的可能性和正确性。方法在FAOCLIM数据库中，选择江苏省境内及边缘地区的气象观察点资料，以改良Malone公式计算血吸虫传播指数值。以1995年AVHRR遥感资料4个季度及流行季节（3～10月）的复合图为背景得出不同季节的流行强度预测图。以Logistic回归方程分析各观察点的传播指数值与现场血吸虫病流行率的关系，并判别预测正确率。结果18个气象观察点资料分析结果显示：所有血吸虫流行区的观察点传播指数值均在900以上。空间分析所得的血吸虫传播区域分布图与江苏省血吸虫病流行区吻合，可划分出不同区域的流行强度。一月份平均最低气温为－4℃的恒值线与传播区域的北边界相吻合。AVHRR卫片图叠加分析后，得出不同区域和不同季节的流行强度预测图。预测总正确率为88．89％。结论应用改良Malone模型能预测和划分流行区域和传播强度。当与卫星遥感NDVI资料结合应用时，对现场防治及时掌握流行情况更为实用。－4℃作为流行区临界温度的发现，提出了全球气候变暖能否造成血吸虫病向中国北方扩散的问题值得研究。
Objective To explore the possibility and correctness of using GIS prediction model to predict the prevalence of schistosomiasis in different regions. Methods The FAOCLIM database was used to select meteorological observation data in the territory of Jiangsu Province and its marginal areas. The improved Malone formula was used to calculate the schistosomiasis transmission index. Taking the composite map of AVHRR remote sensing data of 4 quarters and epidemic season (March to October) in 1995 as the background, the epidemic intensity forecast map of different seasons was drawn. Logistic regression equation was used to analyze the relationship between the spread index and the prevalence of schistosomiasis at each observation point and to determine the correctness of prediction. Results The data analysis of 18 meteorological observation points showed that the spread index values of observation points in all endemic areas of schistosomiasis were more than 900. Spatial analysis of schistosomula transmission area distribution and schistosomiasis prevalence area of Jiangsu Province anastomosis, can be divided into different areas of the epidemic intensity. The constant line of January with an average minimum temperature of -4 ° corresponds to the northern boundary of the propagation area. After the AVHRR satellite patch superimposed analysis, we can get the prediction of the popular intensity in different regions and different seasons. The prediction accuracy is 88.89%. Conclusions The improved Malone model can predict and classify the epidemic area and propagation intensity. When used in conjunction with satellite remote sensing NDVI data, it is more practical to have on-the-spot prevention and control of epidemics in a timely fashion. -4 ℃ as a result of the discovery of the critical temperature in the endemic area, it is worth to study whether global warming can cause the spread of schistosomiasis to the north of China.