达乌尔黄鼠疫源地动物鼠疫预测预警初步研究

发布时间：2018-03-05 21:08

  本文选题：达乌尔黄鼠疫源地　切入点：风险分级　出处：《中国疾病预防控制中心》2013年硕士论文　论文类型：学位论文

【摘要】：鼠疫是严重危害人类健康的烈性传染病,其发生和流行不仅威胁公众的生命,而且会对经济发展产生严重的影响。预测预警技术是以早期发现传染病异常为目的,为控制疫情的发展和传播赢得了宝贵时间的一个新兴技术和方法,我国传染病预测预警技术正处于起步阶段,但已逐渐成为一个研究的热点领域。 我国的鼠疫流行已久,且疫源地种类多,面积大,疫情常年发生,因此其预测预警技术的研究就显得十分必要。达乌尔黄鼠疫源地在我国的起源较早,经历了东北鼠疫的两次大流行,虽然近年来疫情明显减弱,但是发生动物及人间鼠疫流行的风险依然存在。 本文主要利用Matlab软件,应用回归分析中最优回归子集法及时间序列分析中指数平滑的方法对达乌尔黄鼠疫源地及疫源地内6个国家级监测点扎鲁特旗、科右中旗、正白旗乌宁巴图、建平县、镇赉县及哈尔滨市的监测数据进行风险分级及预测预警。文中主要利用达乌尔黄鼠疫源地内蒙古整体数据建立总体回归方程模型并进行风险分级,回归方程考虑以下7项作为影响鼠疫流行的因素：达乌尔黄鼠密度、达乌尔黄鼠鼠体染蚤率、达乌尔黄鼠鼠体蚤指数、巢穴蚤染蚤率、巢穴蚤蚤指数、洞干蚤染蚤率及洞干蚤蚤指数,结果显示当选取达乌尔黄鼠密度、达乌尔黄鼠鼠体染蚤率、达乌尔黄鼠鼠体蚤指数及巢穴蚤染蚤率这4项指标和选取多于这4项指标对预测鼠疫发生的影响基本相同。风险分级为将检出鼠疫菌视为流行,取值为1,未检出菌视为不流行,取值为0,对待判数据的预报方法是将风险分为三级,若预报值y2/3,则将该疫点预报为流行；若预报值y1/3,则预报为不流行；若1/3y2/3,则预报为高风险地区,风险分级后利用实际数据进行拟合,当y2/3时预报流行的符合率均为100%；当y1/3,回归因子选取≥4个时预报流行的符合率均为100%；当1/3y2/3时,回归因子选取≥4个时预报流行的拟合率大约为50%。对内蒙古整体数据利用指数平滑方法预测2012年达乌尔黄鼠疫源地动物鼠疫不流行,6个国家级监测点数据的验证预测也不流行,达乌尔黄鼠疫源地2012年实际情况未检出鼠疫菌,检出血凝阳性材料1份,预测和实际情况基本符合。
[Abstract]:Plague is a severe infectious disease that seriously endangers human health. Its occurrence and prevalence not only threaten the lives of the public, but also have a serious impact on economic development. In order to control the development and spread of epidemic situation, it is a new technology and method that has won precious time. The prediction and early warning technology of infectious disease in China is in its infancy, but it has gradually become a hot field of research. Yersinia pestis has been prevalent for a long time in our country, and there are many kinds of foci, the area is large, and the epidemic occurs all the year round, so it is necessary to study the prediction and early warning technology of Yersinia pestis in our country. After two pandemics of plague in Northeast China, although the epidemic situation has weakened obviously in recent years, the risk of plague epidemic in animals and humans still exists. Using Matlab software, the optimal regression subset method in regression analysis and the exponential smoothing method in time series analysis were applied to the Zhalutte Banner and the middle flag of the family right in the foci of the Daour yellow rat and the 6 national monitoring points in the foci. The monitoring data of Zhengbai Banner, Wuning Gbatu, Jianping County, Zhenlai County and Harbin City were used to classify the risk and predict the risk. In this paper, the overall regression equation model was established and the risk classification was carried out by using the overall data of Daour yellow rat foci in Inner Mongolia. The regression equation considered the following seven factors as the factors influencing the plague epidemic: the density of Daour yellow rat, the flea rate of Daour rat, the flea index of Daour rat, the flea rate of nest flea and the flea index of nest flea. The results showed that when the density of Daour yellow rat was selected, the flea rate of Daour was determined. The body flea index of Daour rat and the flea infection rate of nest flea were basically the same. The risk classification was that the detected Yersinia pestis was regarded as epidemic, the value was 1, and the undetected bacteria was not epidemic. If the forecast value is zero, the forecast method for the judgment data is to divide the risk into three levels. If the forecast value is y2 / 3, the epidemic spot will be predicted as epidemic; if the predicted value is y1 / 3, the forecast will be non-epidemic; if the forecast value is y1 / 3 / 3, then the forecast will be a high-risk area. After risk classification, the coincidence rate of forecasting epidemic was 100 when y2 / 3:00, when y1 / 3, when regression factor 鈮，

本文编号：1571894