Wan-Ting Cheng, Xiang Pan, Ya Yang, Yu Yang, Lin-Han Li, Zhong He, Bin Cai, Wei Wan, Jie Jiang, Qing-Wu Jiang, Yi-Biao Zhou
Department of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education; Tropical Disease Research Center, Fudan University, Shanghai 200032, China.
Station for Schistosomiasis Prevention of Junshan County, Hunan Province, China.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2017 Dec 11;30(1):18-21. doi: 10.16250/j.32.1374.2017121.
To explore the dynamic changes of snail densities in autumn and winter and the relationship between hydrological and meteorological factors and snail growth and decline.
From Octobers to Decembers of 2007 to 2014, a bottomland close to eastern Dongting Lake was selected as the study field. The snails and elevation of the points were surveyed, and the hydrological and meteorological data were collected. The snail densities and death rates of every month were calculated. The meteorological and hydrological data were described, and the relationship between the snail densities and associated factors were fitted by the multiple regression model.
The snail density was highest in October 2012 (41.88 per 0.1 m) and lowest in November 2008 (1.23 per 0.1 m). The snail mortality was highest in November 2008 (73.72%) and lowest in October 2012 (1.09%). The multiple regression model found a linear relationship between hydrological and meteorological factors and snail densities. The correlation coefficient between the prediction of ln (snail density) and its measurements by using this model was 0.927 ( = 0.001).
The average minimum temperature in January and time of starting flood have an obvious influence on the snail densities in autumn and winter.
探讨秋冬季节钉螺密度的动态变化以及水文气象因素与钉螺消长的关系。
选取2007年10月至2014年12月靠近东洞庭湖东部的一片滩地作为研究现场。对钉螺及各点高程进行调查，并收集水文气象数据。计算每月的钉螺密度和死亡率。对气象和水文数据进行描述，并用多元回归模型拟合钉螺密度与相关因素之间的关系。
钉螺密度在2012年10月最高（每0.1米41.88只），在2008年11月最低（每0.1米1.23只）。钉螺死亡率在2008年11月最高（73.72%），在2012年10月最低（1.09%）。多元回归模型发现水文气象因素与钉螺密度之间存在线性关系。利用该模型预测ln（钉螺密度）与其测量值之间的相关系数为0.927（P = 0.001）。
1月平均最低气温和开始涨水时间对秋冬季节钉螺密度有明显影响。
