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作 者:代培芳[1] 赵俊英[1] 刘美德[2] 孔祥盛[1] 翟如芳[1] 王海娇[1] 程璟侠[1]
机构地区:[1]山西省疾病预防控制中心病媒生物防控科/免疫规划科,山西太原030012 [2]军事医学科学院微生物流行病研究所病原微生物生物安全国家重点实验室
出 处:《中国媒介生物学及控制杂志》2011年第6期547-549,共3页Chinese Journal of Vector Biology and Control
基 金:山西省自然科学基金(2008011070);山西省卫生厅科技攻关计划项目(200759;20100140)~~
摘 要:目的探讨山西省运城市某流行性乙型脑炎(乙脑)高发县蚊虫密度与气象因素之间的关系,筛选适合因子预测蚊虫密度变化趋势。方法监测2007-2009年5-10月运城市某县蚊虫密度并收集同期气象资料,气象数据经膨化处理,用SPSS 17.0软件分析两者相关性,并用逐步回归分析建立蚊虫密度的气象因子拟合模型。结果蚊虫季节消长曲线为单峰型,5月出现,8月达高峰,10月消亡。蚊虫密度与月平均温度、月平均气压等相关,与月日照、相对湿度无关。逐步回归分析得出蚊虫密度的气压回归方程,ap_(02)(当月及前2个月的平均气压)和ap_1(提前1个月的平均气压)有良好的拟合效果,两者相比ap_1具有更好的实际操作性。结论气象因素对蚊虫密度有重要影响,可以利用气压拟合模型预测蚊虫密度变化趋势。Objective To identify the relationship between mosquito density and meteorological parameters for selection of appropriate predicting factors for the change of mosquito density in Yuncheng, Shanxi. Methods Spearman' s rank correlation was used in the analysis of the correlation between meteorological parameters and mosquito density per month from 2007 to 2009. Stepwise regression analysis was performed to model the mosquito density change regarding meteorological parameters. Results Single wave was observed in the mosquito seasonal succession curve, indicating that mosquitoes arose early in July, reached a peak in August, and disappeared in October. It was found that mosquito density was correlated with temperature and atmospheric pressure other than sunshine time and relative humidity. Stepwise regression analysis showed that ap0~ and apl could be used for predicting mosquito density, though ap~ was more practical. Ap02 reflected the average atmospheric pressure of the present month as well as the last two months, and ap1 indicated the atmospheric pressure in the last month. Conclusion Since mosquito density was correlated with meteorological parameters, its change could be predicted by an atmospheric pressure fitting model.
分 类 号:R384.1[医药卫生—医学寄生虫学]
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