Abstract:

 Objective   To explore the sensitive temperature index in order to predict the distribu-
tion of Oncomelania hupensis. Methods   Sixty-one weather stations, distributed in Shanghai, Jiang-
su. Zhejiang, Anhui, Jiangxi, Hubei, Hunan, Hebei, Henan: Shandong, Shanxi, Shaanxi,
Sichuan provinces (municipality) , were selected as research stations.  North latitude 34^。 was set as
the boundary of Oncomelan,ia hupensis's distribution. The differences of yearly extreme low temper-
ature and mean temperature in a year between snail areas and no snail areas were tested respectively
by using t test to show their respective significance on the prediction of Oncomelania hupensis's dis-
tribution. Finally, unconditional logistic regression analysis was used to determine which tempera-
ture index had the better effect to predict the distribution of Oncomelan,ia hupensis. Results  Both
the yearly extreme low temperature and mean temperature in a year had significant effect on the dis-
 tribution of Oncomelania hupensis under the t test (t= - 6. 49,  P<0.01; t= - 3. 93,  P<0. 01).
 The differences of the yearly extreme low temperature and mean temperature in a year between snail
 areas and no snail areas were 6. 72 'C and 3. 02 'C respectivcly, and the degree of their differences
 was about 2. 23 times.  The impact of yearly extreme low temperature was more important than that
of mean temperature in a year because mean temperature in a year became no longer statistically sig-
nificant if they were tested simultaneously by using unconditional logistic regression analysis. Con-
clusion  Yearly extreme low temperature may be more sensitive on predicting the distribution of  Oncomelania hupensis than mean temperature in a year.

Key words:  Temperature, Oncomelania hupensis, Distribution, Schistosomiasis

摘要：

目的探索预测湖北钉螺分布的敏感温度指标。方法  选取上海、江苏、浙江、安徽、江西、湖北、湖南、河北、河南、山东、山西、陕西、四川13个相邻有螺省（市）与无螺省（市）的61个气象站作为研究对象，以北纬34度为界，以北编码为温度不适合钉螺生存的地区，以南编码为温度适合钉螺生存的地区，分别用t检验和logistic回归分析确定影响钉螺分布的敏感温度指标。结果有螺区和无螺区的年极端低气温和年平均温度的t检验结果均显示差异有统计学意义（t=-6. 49、-3. 93，P均<0.01）。无螺区年极端低气温和年平均温度均低于有螺区，差值分别为6.72℃和3. 02℃，年极端低气温的差值约为年平均温度差值的2.23倍；logistic回归分析仅显示年极端低气温对钉螺分布的影响有统计学意义(OR =1. 48，P<0.01)，年平坞温度未进入模型。结论年极端低气温可能是预测湖北钉螺分布的敏感温度指标。

关键词: 温度；湖北钉螺；分布；血吸虫病