本文選題：釘螺孳生地類型 + 釘螺分布　； 參考：《武漢大學(xué)》2013年博士論文

【摘要】：在中國(guó),血吸蟲病是一個(gè)重要的公共衛(wèi)生問題。但近年來我國(guó)血.吸蟲病的控制情況并不樂觀,部分地區(qū)疫情有了回升的趨勢(shì)。因此,對(duì)于釘螺的控制以及綜合防控策略的相關(guān)研究是現(xiàn)階段研究的重點(diǎn)。本文采用混合線性模型、時(shí)間序列分析模型、廣義相加模型和廣義估計(jì)方程,系統(tǒng)地分析了湖北省不同類型(洲灘亞型、洲垸亞型和丘陵亞型)的釘螺分布特點(diǎn),時(shí)間變化規(guī)律,建立了不同類型的活螺密度預(yù)測(cè)模型。探討了不同尺度上釘螺分布的影響因素,以及釘螺分布與因素之間的復(fù)雜關(guān)系。最后,評(píng)估了在公安縣實(shí)施的一項(xiàng)以傳染源控制為主的血吸蟲病防控策略的效果。本文的主要內(nèi)容分為四個(gè)部分。 第一部分湖北省釘螺分布特點(diǎn)的初步分析 目的：了解湖北省不同類型釘螺孳生地釘螺分布的差別和時(shí)間變化趨勢(shì)。方法：通過回顧性調(diào)查方法,收集整理了湖北省的漢南區(qū)等30個(gè)縣市1980年至2009年每隔5年(最后一個(gè)時(shí)間段是間隔4年)的釘螺數(shù)據(jù),提取釘螺面積和活螺密度兩個(gè)指標(biāo)。根據(jù)當(dāng)?shù)蒯斅萱苌闹饕h(huán)境,將研究地區(qū)分為洲灘亞型、洲垸亞型和丘陵亞型三種類型,應(yīng)用混合線性模型分析不同類型釘螺分布(釘螺面積和活螺密度)的差別和和時(shí)間變化趨勢(shì)。結(jié)果：洲垸亞型和洲灘亞型地區(qū)釘螺面積高于丘陵亞型(P=0.0179和P0.0001),并且整體上釘螺面積隨調(diào)查年份有下降的趨勢(shì)(P=0.0139)。洲垸業(yè)型地區(qū)活螺密度高于丘陵亞型(P=0.0098),并且洲垸亞型活螺密度隨時(shí)問有下降的趨勢(shì)(P=0.0005)。結(jié)論：湖北省不同類型釘螺分布有差別,并且隨時(shí)間變化趨勢(shì)不一樣。 第二部分湖北省釘螺分布的時(shí)間特點(diǎn)及預(yù)測(cè)模型研究 目的：分析湖北省三種環(huán)境類型釘螺分布的時(shí)間特點(diǎn),并建立不同環(huán)境類型的活螺密度預(yù)測(cè)模型。方法：根據(jù)釘螺孳生的主要環(huán)境類型,通過回顧性凋查方法,收集整理了湖北省3個(gè)縣市(代表三種類型)1980年至2009年(連續(xù)年份)釘螺監(jiān)測(cè)資料,提取螺點(diǎn)尺度上的活螺密度。應(yīng)用時(shí)間序列分析方法(ARIMA模型),建立不同類型的活螺密度預(yù)測(cè)模型。同時(shí),收集了3個(gè)縣市1980年至2009年的氣候數(shù)據(jù),在ARIMA模型中加入氣候因子,建立帶輸入變量的預(yù)測(cè)模型(ARIMAX模型)。結(jié)果：洲垸亞型、洲灘亞型和和丘陵亞型活螺密度的ARIMA模型依次為：(1-B)(1-0.867B6)d1=ε1,(1-B)(1+1.014B+0.776B2)d1=ε1,(1-B)d1=(1-0.475B)ε1。洲垸亞型和丘陵亞型活螺密度的ARIMAX模型依次為：d1=16.363+(-0.501-0.380B)tem1+(1+0.535B)v1其中,d1,tem1,sun1分別為t時(shí)的活螺密度,每日平均溫度和日照時(shí)數(shù)；ε1和vt為白噪聲序列,B為延遲算子。ARIMA模型和ARIMAX模型均有較好的效果,絕大多數(shù)實(shí)測(cè)值均落在預(yù)測(cè)值的95%可信區(qū)間內(nèi)。結(jié)論：實(shí)際工作中,ARIMA模型和ARIMAX模型可以用來預(yù)測(cè)釘螺密度,但是需要根據(jù)不同的環(huán)境特點(diǎn)建立模型。 第三部分湖北省不同尺度下釘螺分布的影響因素研究 目的：探討不同尺度下湖北省釘螺分布的影響因素,重點(diǎn)探討小尺度下釘螺分布與因素間的復(fù)雜非線性關(guān)系。方法：在較大尺度下(縣級(jí)尺度),通過回顧性調(diào)查方法,收集整理了湖北省的漢南區(qū)等30個(gè)縣市2000年,2005年和2009年釘螺數(shù)據(jù),提取活螺密度作為因變量。同時(shí)收集了30個(gè)縣市當(dāng)年和上年度的氣候因子,利用線性混合模型探討氣候因子與活螺密度的關(guān)系。在小尺度下(螺點(diǎn)尺度),通過現(xiàn)場(chǎng)調(diào)查收集整理了嘉魚縣等5個(gè)縣市2010年的釘螺資料,提取活螺密度和每個(gè)螺點(diǎn)陽性釘螺只數(shù)兩個(gè)指標(biāo)。利用3S技術(shù)獲取螺點(diǎn)的環(huán)境、地形信息,并且收集了螺點(diǎn)上年度的水文資料,應(yīng)用廣義相加模型探討小尺度下釘螺分布與相關(guān)因子的復(fù)雜非線性關(guān)系。結(jié)果：較大尺度下,整體上平均溫度對(duì)活螺密度是正向影響,活螺密度隨溫度的上升而上升(P=0.0150)。降雨量對(duì)不同類型地區(qū)的活螺密度影響不一樣,在洲垸業(yè)型和洲灘業(yè)型地區(qū)降雨量對(duì)活螺密度有正向影響(兩個(gè)P0.0001),而丘陵亞型地區(qū)降雨量對(duì)活螺密度無影響(P=0.6259)。小尺度下,坡度對(duì)活螺密度有負(fù)相影響(P=0.0303),螺點(diǎn)的上一年上水天數(shù)、高程、地表溫度與活螺密度間存在復(fù)雜的非線性關(guān)系(分別為P0.0001,P=0.0462,P=0.0031)。上年上水天數(shù)為90天,高程為29米,地表溫度為26度的螺點(diǎn)活螺密度最高。陽性釘螺數(shù)方面,高程對(duì)陽性釘螺數(shù)有負(fù)相影響(P0.0001),上一年上水天數(shù)、坡度、地表溫度與活螺密度間存在復(fù)雜的非線性關(guān)系(分別為P0.0001,P=0.0026,P0.0001)。結(jié)論：在較大尺度下,氣候?qū)Σ煌h(huán)境類型的活螺密度有影響,但并不完全一致。在小尺度下,水文、環(huán)境和地形因子與釘螺分布之間有復(fù)雜的非線性關(guān)系。 第四部分湖北省湖沼型地區(qū)血吸蟲病防控策略的研究 目的：評(píng)估以傳染源控制為主的血吸蟲病綜合防控策略在湖北省湖沼型地區(qū)的實(shí)施效果,并提出符合湖北省實(shí)際情況的具體措施。方法：采用整群隨機(jī)對(duì)照設(shè)計(jì),從2008年至2011年在湖北省公安縣的12個(gè)村莊實(shí)施了一項(xiàng)以控制傳染源為主的綜合防控策略。對(duì)照組實(shí)施常規(guī)干預(yù)措施：人畜同步化療和火螺措施。干預(yù)組除了常規(guī)干預(yù)措施外,增加了新的干預(yù)措施：圍欄封洲禁牧和建立安全牧場(chǎng),完善村血防室的建設(shè)和加強(qiáng)健康教育,改善居民衛(wèi)生設(shè)施和衛(wèi)生條件。測(cè)量了五個(gè)結(jié)局指標(biāo)：人群、牛、釘螺、牛糞以及哨鼠血吸蟲感染率。采用廣義估計(jì)方程評(píng)估主要結(jié)局指標(biāo)(人群血吸蟲感染率)在兩組間的差異。結(jié)果：從2008年至2011年在干預(yù)組中,人群、牛、釘螺、牛糞以及哨鼠血吸蟲感染率分別從3.41%下降到0.81%,從3.3%下降到0,從11/6219(0.177%)下降到0,從3.9%下降到0,從31.7%下降到1.7%(所有P0.01)。廣義估計(jì)方程分析結(jié)果顯示,對(duì)照組研究對(duì)象血吸蟲病感染率的風(fēng)險(xiǎn)高于干預(yù)組(OR=1.250,P=0.001),并且在整個(gè)研究期間,兩組研究對(duì)象血吸蟲病感染率風(fēng)險(xiǎn)有下降的趨勢(shì)(P0.001)。結(jié)論：以控制傳染源為主(重點(diǎn)控制耕牛)的血吸蟲病綜合防控策略在湖北省的湖沼型流行區(qū)的效果比較好。圍欄封洲禁牧和建立安全牧場(chǎng)相結(jié)合的措施符合湖北省的實(shí)際情況,在實(shí)際血防工作中可以推廣。
[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.
【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：R532.21

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