湖北省钉螺分布规律及血吸虫病防控策略的研究

发布时间：2018-06-25 15:35

本文选题：钉螺孳生地类型 + 钉螺分布　；参考：《武汉大学》2013年博士论文

【摘要】：在中国,血吸虫病是一个重要的公共卫生问题。但近年来我国血.吸虫病的控制情况并不乐观,部分地区疫情有了回升的趋势。因此,对于钉螺的控制以及综合防控策略的相关研究是现阶段研究的重点。本文采用混合线性模型、时间序列分析模型、广义相加模型和广义估计方程,系统地分析了湖北省不同类型(洲滩亚型、洲垸亚型和丘陵亚型)的钉螺分布特点,时间变化规律,建立了不同类型的活螺密度预测模型。探讨了不同尺度上钉螺分布的影响因素,以及钉螺分布与因素之间的复杂关系。最后,评估了在公安县实施的一项以传染源控制为主的血吸虫病防控策略的效果。本文的主要内容分为四个部分。第一部分湖北省钉螺分布特点的初步分析目的：了解湖北省不同类型钉螺孳生地钉螺分布的差别和时间变化趋势。方法：通过回顾性调查方法,收集整理了湖北省的汉南区等30个县市1980年至2009年每隔5年(最后一个时间段是间隔4年)的钉螺数据,提取钉螺面积和活螺密度两个指标。根据当地钉螺孳生的主要环境,将研究地区分为洲滩亚型、洲垸亚型和丘陵亚型三种类型,应用混合线性模型分析不同类型钉螺分布(钉螺面积和活螺密度)的差别和和时间变化趋势。结果：洲垸亚型和洲滩亚型地区钉螺面积高于丘陵亚型(P=0.0179和P0.0001),并且整体上钉螺面积随调查年份有下降的趋势(P=0.0139)。洲垸业型地区活螺密度高于丘陵亚型(P=0.0098),并且洲垸亚型活螺密度随时问有下降的趋势(P=0.0005)。结论：湖北省不同类型钉螺分布有差别,并且随时间变化趋势不一样。第二部分湖北省钉螺分布的时间特点及预测模型研究目的：分析湖北省三种环境类型钉螺分布的时间特点,并建立不同环境类型的活螺密度预测模型。方法：根据钉螺孳生的主要环境类型,通过回顾性凋查方法,收集整理了湖北省3个县市(代表三种类型)1980年至2009年(连续年份)钉螺监测资料,提取螺点尺度上的活螺密度。应用时间序列分析方法(ARIMA模型),建立不同类型的活螺密度预测模型。同时,收集了3个县市1980年至2009年的气候数据,在ARIMA模型中加入气候因子,建立带输入变量的预测模型(ARIMAX模型)。结果：洲垸亚型、洲滩亚型和和丘陵亚型活螺密度的ARIMA模型依次为：(1-B)(1-0.867B6)d1=ε1,(1-B)(1+1.014B+0.776B2)d1=ε1,(1-B)d1=(1-0.475B)ε1。洲垸亚型和丘陵亚型活螺密度的ARIMAX模型依次为：d1=16.363+(-0.501-0.380B)tem1+(1+0.535B)v1其中,d1,tem1,sun1分别为t时的活螺密度,每日平均温度和日照时数；ε1和vt为白噪声序列,B为延迟算子。ARIMA模型和ARIMAX模型均有较好的效果,绝大多数实测值均落在预测值的95%可信区间内。结论：实际工作中,ARIMA模型和ARIMAX模型可以用来预测钉螺密度,但是需要根据不同的环境特点建立模型。第三部分湖北省不同尺度下钉螺分布的影响因素研究目的：探讨不同尺度下湖北省钉螺分布的影响因素,重点探讨小尺度下钉螺分布与因素间的复杂非线性关系。方法：在较大尺度下(县级尺度),通过回顾性调查方法,收集整理了湖北省的汉南区等30个县市2000年,2005年和2009年钉螺数据,提取活螺密度作为因变量。同时收集了30个县市当年和上年度的气候因子,利用线性混合模型探讨气候因子与活螺密度的关系。在小尺度下(螺点尺度),通过现场调查收集整理了嘉鱼县等5个县市2010年的钉螺资料,提取活螺密度和每个螺点阳性钉螺只数两个指标。利用3S技术获取螺点的环境、地形信息,并且收集了螺点上年度的水文资料,应用广义相加模型探讨小尺度下钉螺分布与相关因子的复杂非线性关系。结果：较大尺度下,整体上平均温度对活螺密度是正向影响,活螺密度随温度的上升而上升(P=0.0150)。降雨量对不同类型地区的活螺密度影响不一样,在洲垸业型和洲滩业型地区降雨量对活螺密度有正向影响(两个P0.0001),而丘陵亚型地区降雨量对活螺密度无影响(P=0.6259)。小尺度下,坡度对活螺密度有负相影响(P=0.0303),螺点的上一年上水天数、高程、地表温度与活螺密度间存在复杂的非线性关系(分别为P0.0001,P=0.0462,P=0.0031)。上年上水天数为90天,高程为29米,地表温度为26度的螺点活螺密度最高。阳性钉螺数方面,高程对阳性钉螺数有负相影响(P0.0001),上一年上水天数、坡度、地表温度与活螺密度间存在复杂的非线性关系(分别为P0.0001,P=0.0026,P0.0001)。结论：在较大尺度下,气候对不同环境类型的活螺密度有影响,但并不完全一致。在小尺度下,水文、环境和地形因子与钉螺分布之间有复杂的非线性关系。第四部分湖北省湖沼型地区血吸虫病防控策略的研究目的：评估以传染源控制为主的血吸虫病综合防控策略在湖北省湖沼型地区的实施效果,并提出符合湖北省实际情况的具体措施。方法：采用整群随机对照设计,从2008年至2011年在湖北省公安县的12个村庄实施了一项以控制传染源为主的综合防控策略。对照组实施常规干预措施：人畜同步化疗和火螺措施。干预组除了常规干预措施外,增加了新的干预措施：围栏封洲禁牧和建立安全牧场,完善村血防室的建设和加强健康教育,改善居民卫生设施和卫生条件。测量了五个结局指标：人群、牛、钉螺、牛粪以及哨鼠血吸虫感染率。采用广义估计方程评估主要结局指标(人群血吸虫感染率)在两组间的差异。结果：从2008年至2011年在干预组中,人群、牛、钉螺、牛粪以及哨鼠血吸虫感染率分别从3.41%下降到0.81%,从3.3%下降到0,从11/6219(0.177%)下降到0,从3.9%下降到0,从31.7%下降到1.7%(所有P0.01)。广义估计方程分析结果显示,对照组研究对象血吸虫病感染率的风险高于干预组(OR=1.250,P=0.001),并且在整个研究期间,两组研究对象血吸虫病感染率风险有下降的趋势(P0.001)。结论：以控制传染源为主(重点控制耕牛)的血吸虫病综合防控策略在湖北省的湖沼型流行区的效果比较好。围栏封洲禁牧和建立安全牧场相结合的措施符合湖北省的实际情况,在实际血防工作中可以推广。
[Abstract]:In China, schistosomiasis is an important public health problem. However, in recent years, the control of blood fluke disease in China is not optimistic. In some areas, the epidemic situation has been rising. Therefore, the research on the control of Oncomelania and the comprehensive prevention and control strategy is the important point at the present stage. This paper uses a mixed linear model, time series. The distribution characteristics of Oncomelania snails in different types of Hubei Province, such as subtypes of continental subtypes, subtypes of embankment and hilly subtype, were analyzed systematically by analyzing the distribution characteristics of Oncomelania snails in different types, such as the generalized phase addition model and the generalized estimation equation, and the prediction models of different types of living snail density were established. The influence factors on the distribution of Oncomelania snails at different scales were discussed, and the distribution and cause of Oncomelania snails were discussed. In the end, the effect of a schistosomiasis control strategy based on contagious source control in Gongan County was evaluated. The main contents of this paper were divided into four parts.
The first part is a preliminary analysis of distribution characteristics of Oncomelania hupensis in Hubei province.
Objective: to understand the difference and time change trend of Oncomelania Snail Distribution in different types of Oncomelania in Hubei province. Methods: through retrospective investigation, the data of Oncomelania snails in 30 counties, such as Hannan, Hubei Province, from 1980 to 2009, every 5 years (the last time interval of 4 years) were collected and collected, and the area of Oncomelania snails and the density of living snail were extracted and two. According to the main environment of the local Oncomelania Snail breeding, the research areas were divided into three types of subtypes of beach subtype, subtype of embankment subtype and hilly subtype. The difference and time change trend of the distribution of Oncomelania snails (snail area and living snail density) of different types of snails were analyzed by mixed linear model. Hilly subtype (P=0.0179 and P0.0001), and on the whole, the area of Oncomelania Snail decreased with the survey year (P=0.0139). The density of living snail in the area of the embankment is higher than that of the hilly type (P=0.0098), and the density of the living snails in the subtype of the embankment subtype has a decreasing trend at any time (P=0.0005). Conclusion: the distribution of different types of snails in Hubei province is different, and with time The changing trend is different.
The second part is about the temporal characteristics and prediction models of snail distribution in Hubei province.
Objective: to analyze the time characteristics of the distribution of Oncomelania snails in three environmental types in Hubei Province, and to establish a prediction model of the living snail density of different environmental types. Methods: according to the main environmental types of Oncomelania Snail breeding, through retrospective method, the monitoring of Oncomelania snails in 3 counties (representing three types) in Hubei province from 1980 to 2009 (in a continuous year) was collected and collected. Data were used to extract the density of the living snail on the snails scale. Using the time series analysis (ARIMA model), different types of living snail density prediction models were established. At the same time, the climate data of 3 counties and cities were collected, and the climate factors were added to the ARIMA model, and the prediction model with the input variable (ARIMAX model) was established. ARIMA (1-B) (1-0.867B6) d1= epsilon 1, (1-B) (1+1.014B+0.776B2) d1= epsilon 1, (1-B) d1= (1-B) d1= (1-B) d1= (1-0.475B) 1. embankment subtype and hilly subtype living snail density are in turn: d1=16.363+ Degree, daily average temperature and sunshine hours; epsilon 1 and VT as white noise sequence, B for delay operator.ARIMA model and ARIMAX model, most of the measured values fall within the 95% confidence interval of the predicted value. Conclusion: in actual work, ARIMA model and ARIMAX model can be used to predict the density of Oncomelania snails, but it needs to be based on the difference. The environmental characteristics of the model are established.
The third part is about the influencing factors of snail distribution in different scales in Hubei province.
Objective: To investigate the influence factors of the distribution of Oncomelania snails in Hubei Province, and to discuss the complex nonlinear relationship between the distribution and factors of Oncomelania snails under small scale. Methods: in a large scale (county level), the data of Oncomelania snails in 2000, 2005 and 2009 in the 30 counties and other counties of Hannan, Hubei province were collected and collected through a retrospective survey method. The density of living snail was taken as the dependent variable. At the same time, the climatic factors of the year and the last year of 30 counties and cities were collected. The relationship between the climatic factors and the density of living snail was studied by the linear mixed model. On the small scale (snail scale), the data of Oncomelania snails in 5 counties, such as Jiayu County, were collected and collected in 2010 by field investigation, and the density of living snail and each snails were extracted. The positive Oncomelania Oncomelania Oncomelania Oncomelania is only a number of two indexes. The 3S technology is used to obtain the environment of the snails, the terrain information, and the hydrological data of the annual snails are collected. The complex nonlinear relationship between the distribution of Oncomelania snails and the related factors under the small scale is discussed with the generalized additive model. The results are that the average temperature on the whole is positive to the density of the living snails under the larger scale. The density of living snails increased with the increase of temperature (P=0.0150). Rainfall has different effects on the density of living snail in different types of areas. Rainfall has a positive effect on the density of living snail in the embankment and beach areas (two P0.0001), while rainfall in the hilly subtype has no effect on the density of living snail (P=0.6259). There is a negative phase influence (P=0.0303). There is a complex nonlinear relationship between the upper water days, the elevation, the surface temperature and the density of the living snail (P0.0001, P=0.0462, P=0.0031). The number of upper water days is 90 days, the height is 29 meters, the surface temperature is 26 degrees of the snail density. There is a negative phase effect (P0.0001). There is a complex nonlinear relationship between the number of water days, the slope, the surface temperature and the density of the living snail (P0.0001, P=0.0026, P0.0001). There is a complex nonlinear relationship between the distribution of Oncomelania snails and the distribution of Oncomelania.
The fourth part is the strategy of schistosomiasis control in Lake and marshland areas of Hubei province.
Objective: To evaluate the effect of schistosomiasis control strategy based on infectious source control in the lake marshland area of Hubei Province, and to put forward specific measures in accordance with the actual situation in Hubei province. Method: a cluster random control design was adopted to control the source of infection from 2008 to 2011 in 12 villages in Gongan County, Hubei province. In the control group, the control group carried out routine intervention measures: human and animal synchronous chemotherapy and fire snail measures. In addition to conventional intervention measures, the intervention group added new intervention measures: enclosure closure of the continent and the establishment of safe pasture, improving the construction of village blood and defence rooms and strengthening health education, improving health facilities and sanitary conditions for residents. Five outcome indexes: population, cattle, Oncomelania snails, cow dung and sentry schistosomiasis infection rate. The difference between the two groups was evaluated by the generalized estimation equation. Results: from 2008 to 2011, the infection rate of population, cattle, oncomelania, cow dung and sentry schistosomiasis from 3.41% to 0., respectively, in the intervention group. 81%, from 3.3% to 0, from 11/6219 (0.177%) to 0, from 3.9% to 0, from 31.7% to 1.7% (all P0.01). The generalized estimation equation analysis showed that the risk of schistosomiasis infection in the control group was higher than that of the intervention group (OR=1.250, P=0.001), and during the whole study, the risk of schistosomiasis infection rate was studied in two groups. There is a downward trend (P0.001). Conclusion: the comprehensive prevention and control strategy of schistosomiasis control in Hubei province is better by controlling the source of infectious diseases in the lake marshland epidemic area of Hubei province. The measures to combine the fence closure and the establishment of safe pasture conform to the actual situation in Hubei province and can be popularized in the actual schistosomiasis control work.
【学位授予单位】：武汉大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：R532.21

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