中国血吸虫病防治杂志 ›› 2018, Vol. 30 ›› Issue (1): 18-21,36.

• 论著 • 上一篇    下一篇

东洞庭湖秋冬季节钉螺生存状态及其影响因素的研究

程婉婷1|潘翔1|杨亚1|杨宇1|李林瀚1|何忠2|蔡斌2|万伟2|姜杰2|姜庆五1|周艺彪1*   

  1. 1复旦大学公共卫生学院流行病学教研室、公共卫生安全教育部重点实验室、热带病学研究中心(上海 200032);2湖南省岳阳市君山区血吸虫病防治站
  • 出版日期:2018-03-05 发布日期:2018-03-05
  • 通讯作者: 周艺彪
  • 作者简介:程婉婷|女|硕士研究生。研究方向:疾病预防与控制
  • 基金资助:
    国家自然科学基金(81673236);上海市第四轮公共卫生三年行动计划重点学科建设项目(15GWZK0101)

Research on living status of Oncomelania hupensis in autumn and winter and its correlates in Eastern Dongting Lake area

CHENG Wan-ting1| PAN Xiang1| YANG Ya1| YANG Yu1| LI Lin-han1| HE Zhong2| CAI Bin2| WAN Wei2| JIANG Jie2| JIANG Qing-wu1| ZHOU Yi-biao1*   

  1. 1 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; 2 Station for Schistosomiasis Prevention of Junshan County| Hunan Province| China
  • Online:2018-03-05 Published:2018-03-05
  • Contact: ZHOU Yi?biao

摘要: 目的 研究秋冬季节钉螺种群的动态变化及水位和气象因素与钉螺消长的关系。方法 选择2007-2014年10-12月,以东洞庭湖区的草滩为现场,系统抽样查螺,同时测量调查点的高程以及收集水位和气象资料,计算各年水淹天数和开始水淹时间。描述钉螺及可能影响因素的分布情况,用多元回归模型研究水位和气象因素与钉螺密度的关系。结果 钉螺密度呈波动变化,最高值在2012年10月,为41.88只/0.1 m2;最低值在2008年11月,为1.23只/0.1 m2。死亡率最高出现在 2008年11月,为73.72 %;最低出现在2012年10月,为1.09%。多元回归模型拟合发现1月平均最低温度和开始水淹时间与ln(钉螺密度)之间存在线性关系。利用该模型计算得到的ln(钉螺密度)的预测值与实际值的相关系数为0.927(P = 0.001)。 结论 在东洞庭湖,1月份平均最低温度和开始水淹时间对当年秋冬季的钉螺密度有一定的影响。

关键词: 钉螺;生态;开始水淹时间;1月平均最低温度;洞庭湖

Abstract: Objective To explore the dynamic changes of Oncomelania hupensis snail densities in autumn and winter and the relationship between hydrological and meteorological factors and snail growth and decline. Methods 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. Results The snail density was highest in October 2012 (41.88 per 0.1 m2) and lowest in November 2008 (1.23 per 0.1 m2). 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 (P = 0.001). Conclusion The average minimum temperature in January and time of starting flood have an obvious influence on the snail densities in autumn and winter.

Key words: Oncomelania hupensis; Ecology; Time of starting flood; Average minimum temperature in January; Dongting Lake

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