【摘要】：第一部分廣西1996～2012年艾滋病流行特征研究 目的 分析廣西1996～2012年艾滋病的流行特征，探討廣西艾滋病流行強度的地區(qū)差異。為廣西艾滋病針對性防控策略和措施的制定提供科學依據(jù)。 方法 收集廣西1996～2012年廣西艾滋病防治信息管理系統(tǒng)中首次報告的確證HIV抗體陽性的感染者（包括HIV感染者和AIDS病人），，用各種統(tǒng)計圖表對廣西艾滋病流行特征進行描述性分析；并將感染者以縣（市、區(qū)）為基本統(tǒng)計單位，通過GIS軟件的自然斷點分級法劃分累積感染率（CPI）、累積患病率(CP)、累積死亡率(CMR)、累積病死率(CFR)4項流行指標（下稱4項流行指標）高、中、低流行區(qū)，對比分析各縣（市、區(qū)）4項流行指標的特征。 結(jié)果 1.廣西艾滋病流行特征 （1）傳染源累積數(shù)量大。1996～2012年累計報告廣西籍HIV感染者和AIDS病人83241例，其中HIV感染者47094例，所占比例為56.58%、；36147例感染者在首次確證感染時即為AIDS病人,占43.42%。（2）感染趨勢先慢后快。2003年之前，感染者數(shù)量增長緩慢，2003年以后，數(shù)量呈快速增長，但2012年有下降趨勢。（3）感染人群特征明顯。以男性為主，占72.34%；年齡集中在15-49歲，占68.94%；以漢族（61.11%）、已婚（57.05%）、初中及以下文化程度（79.11%）、職業(yè)為農(nóng)民（含民工）和工人（60.39%）為主。（4）異性性傳播為主要感染途徑。66.31%的HIV感染者通過異性性傳播途徑感染；（5）非婚異性性行為是主要高危行為。感染者中存在非婚異性性行為（至少1個非婚異性性伴）的比例占42.56%，其中80.59%有2個及以上非婚異性性伴。（6）臨床就診為發(fā)現(xiàn)HIV感染者的主要途徑。感染者主要以臨床就診檢查發(fā)現(xiàn)為主，占65.68%。 2.廣西艾滋病流行區(qū)的劃分及特點 以GIS軟件的自然斷點分級法將CPI、CP、CMR、CFR分成三組，對應(yīng)為高、中、低流行區(qū)。CPI高、中、低流行區(qū)所包括的縣（市、區(qū)）分別為15、45、49個，相應(yīng)區(qū)間分別為2.99‰～6.91‰、1.21‰～2.98‰、0.18‰～1.20‰。CP高、中、低流行區(qū)所包括的縣（市、區(qū)）分別為13、41、65個，相應(yīng)區(qū)間分別為1.54‰～4.24‰、0.55‰～1.53‰、0.06‰～0.54‰。CMR高、中、低流行區(qū)所轄縣（市、區(qū)）分別為4、20、85個，相應(yīng)區(qū)間為0.58‰～1.26‰、0.17‰～0.57‰、0.00‰～0.16‰。CFR高、中、低流行區(qū)所包括的縣（市、區(qū)）分別為18、45、46個，相應(yīng)區(qū)間分別為27.25%～50.00%、13.28%～27.24%、0.00%～13.27%。 CPI和CP高、中、低流行區(qū)分布一致性較高，以CPI為參照，CP高、中、低流行區(qū)與CPI高、中、低流行區(qū)的符合率分別為86.67%、84.44%、93.88%,總體符合率達到88.99%。CPI、CP均高的縣（市、區(qū)）艾滋病流行較早，主要分布在邊境城市、柳州市城區(qū)及周圍。CPI、CP均居中的縣（市、區(qū)）主要分為兩大聚集叢：以柳州片區(qū)的高流行縣為中心向周圍輻射的聚集叢和以邊境城市的高流行縣為起始，向內(nèi)部蔓延的聚集叢。CPI、CP均低的縣（市、區(qū)）則主要分布高、中流行區(qū)的外圍。直觀地圖可發(fā)現(xiàn)，CPI、CP高、中流行區(qū)主要為自東北向西南以約45°角傾斜走向的廣西經(jīng)濟相對發(fā)達，交通較為便利的中部地帶。CMR高、中流行區(qū)所包括的縣（市、區(qū)）與CPI、CP一致。然而CFR高流行區(qū)所轄的縣（市、區(qū)）中，77.78%CPI、CP、CMR均低。 結(jié)論 1.廣西艾滋病傳染源累積基數(shù)較大，1996～2012年艾滋病的流行特點呈現(xiàn)先慢后快趨勢，但在2012年開始下降。廣西艾滋病存在43.42%的HIV陽性感染者在首次確證感染時即為AIDS病人，感染途徑主要為異性接觸傳播，主要高危行為是非婚異性性行為等特征。因此，針對性的防控策略和措施，如推廣簡便、快捷的HIV檢測方法，加強對文化程度較低人群的艾滋病相關(guān)健康教育，進一步推廣性行為、特別是非婚性行為中安全套的使用等措施對預防廣西艾滋病通過性途徑的進一步蔓延具有重大的意義。 2.利用GIS自然斷點分級法劃分的高、中、低流行區(qū)具有較高的符合率，為直觀廣西不同縣（市、區(qū)）艾滋病流行狀況提供了便利，但需要重點考慮社會、行為等因素的影響。 3.針對不同縣（市、區(qū)）4項流行指標的等級差異，廣西艾滋病防控重點可以考慮CPI與CP的高、中流行區(qū)域，而CPI與CP的低流行區(qū)域（即CFR高流行區(qū)）的干預重點是降低HIV/AIDS的病死率。 第二部分廣西艾滋病流行地區(qū)數(shù)理判別模型研究 目的 以CPI、CP、CMR（簡稱為3項流行指標，下同）為主體指標進行分層分析，分析不同流行地區(qū)的艾滋病流行模式和趨勢，并探討影響廣西艾滋病3項流行指標的經(jīng)濟社會學因素，建立影響CPI的地區(qū)經(jīng)濟社會發(fā)展相關(guān)因素的多重線性回歸模型以及3項流行指標高、中、低流行地區(qū)類別的數(shù)理判別模型，為科學制定艾滋病防控策略提供依據(jù)。 方法 收集影響高、中、低流行區(qū)的經(jīng)濟社會學發(fā)展指標資料，利用Spearman簡單相關(guān)分析它們與CPI、CP、CMR的關(guān)聯(lián)性；用單因素方差分析方法比較不同流行區(qū)經(jīng)濟社會發(fā)展指標的差異性；用逐步回歸分析方法建立影響CPI的多重線性回歸模型；用Fisher逐步判別法建立廣西艾滋病不同流行地區(qū)類別的數(shù)理判別模型，并進行效果評價。 結(jié)果 1.經(jīng)濟社會學發(fā)展因素與CPI、CP、CMR的關(guān)聯(lián)性：8項經(jīng)濟社會學相關(guān)指標（人口密度X1、非農(nóng)業(yè)人口占總?cè)丝诒戎豖2、人口自然增長率X3、人均地區(qū)生產(chǎn)總值X4、城鎮(zhèn)居民人均可支配收入X5、農(nóng)村居民人均純收入X6、受教育人口九年義務(wù)教育完成率X7、AIDS病人累積治療率X8與3項流行指標進行Spearman簡單相關(guān)分析發(fā)現(xiàn)，X1、 X2、X4、X5、X6、X7與CPI、CP相關(guān)（P0.10）；X2、X4、X6、X7與CMR相關(guān)（P0.10）。 2.影響CPI、CP、CMR的經(jīng)濟社會學發(fā)展因素：（1）影響CPI的地區(qū)經(jīng)濟社會學因素為X2、X4、X5、X6、X7，多因素模型影響因素為X7，判別模型影響因素為X4、X7；影響CP的地區(qū)經(jīng)濟社會學因素為X2、X4、X6、X7，判別模型影響因素為X4、X7，多因素模型影響因素為X7；影響CMR的地區(qū)經(jīng)濟社會學因素為X2、X4、X7，多因素模型影響因素為X4，判別模型影響因素為X4。X4是3項流行指標地區(qū)類別判別模型的共同影響因素，均呈正相關(guān)關(guān)系；而X7是CPI和CP的地區(qū)類別判別模型的共同影響因素，同樣呈正相關(guān)關(guān)系。 3. CPI、CP、CMR不同流行地區(qū)數(shù)理判別模型的構(gòu)建：結(jié)合單因素分析有統(tǒng)計學意義的經(jīng)濟社會學發(fā)展因素以及專業(yè)知識，將與艾滋病流行密切相關(guān)的因素納入Fisher逐步判別模型分析。建立相應(yīng)的地區(qū)類別判別模型結(jié)果如下： 3.1CPI判別模型 CPI高流行區(qū)：YH=-19.36+2.39×10-4X4+0.62X7 CPI中流行區(qū)：YM=-19.97+4.68×10-4X4+0.69X7 CPI低流行區(qū)：YL=-15.72+4.27×10-4X4+0.61X7 3.2CP判別模型 CP高流行區(qū)：YH=-19.32+1.80×10-4X4+0.61X7 CP中流行區(qū)：YM=-20.31+4.43×10-4X4+0.69X7 CP低流行區(qū)：YL=-15.97+4.29×10-4X4+0.62X7 3.3CMR判別模型 CMR高流行區(qū)：YH=-3.78+3.78×10-4X4（由于自然斷點法劃分的CMR高流行區(qū)包括的研究單位較少，因此在建模過程中將高、中流行區(qū)合并為高流行區(qū)） CMR低流行區(qū)：YL=-2.54+2.92×10-4X4 4.判別模型效果評價：用回代法檢驗各判別函數(shù)的符合率：（1）CPI高、中、低流行地區(qū)的判別符合率分別為56.25%、58.18%、53.06%，總的判別符合率為51.38%。(2)CP高、中、低流行地區(qū)的判別符合率分別為53.84%、48.78%、52.4%，總體判別符合率為54.13%。(3)CMR高、低流行地區(qū)的判別符合率分別為48.00%、69.05%，總體判別符合率為64.22%。 結(jié)論 1.CPI、CP、CMR、CFR能夠全面反映廣西艾滋病的流行強度。 2.人均地區(qū)生產(chǎn)總值（X4）、受教育人口九年義務(wù)教育完成率（X7）是促進廣西艾滋病流行的重要經(jīng)濟社會學發(fā)展因素。 3.對廣西艾滋病流行區(qū)的劃分可考慮構(gòu)建數(shù)理判別模型，但其判別符合率的提高仍需要結(jié)合考慮多樣、復雜的行為、生物學等因素的影響。
[Abstract]:The first part is about the epidemiological characteristics of AIDS in Guangxi in the past 1996~2012 years.
objective
To analyze the epidemic characteristics of AIDS in Guangxi from 1996 to 2012, and to explore the regional differences of the epidemic intensity of AIDS in Guangxi.
Method
To collect the first reported HIV-positive infections (including HIV-infected persons and AIDS patients) in Guangxi AIDS prevention and control information management system from 1996 to 2012, and analyze the epidemic characteristics of AIDS in Guangxi with various statistical charts and charts. However, the breakpoint classification method was used to classify the four epidemic indicators (CPI, CP, CMR and CFR) into high, middle and low epidemic areas. The characteristics of the four epidemic indicators in each county (city, district) were compared and analyzed.
Result
1. epidemiological characteristics of AIDS in Guangxi
(1) The cumulative number of sources of infection is large. From 1996 to 2012, 83 241 cases of HIV-infected persons and AIDS patients in Guangxi were reported, of which 47 094 were infected with HIV, accounting for 56.58%; 36 147 were infected with AIDS at the time of first confirmation of infection, accounting for 43.42%. (2) The trend of infection was slow and fast. Before 2003, the number of infected persons increased slowly, and in 2003, the number of infected persons increased slowly. After that, the number showed a rapid growth, but there was a downward trend in 2012. (3) The characteristics of the infected population were obvious. (3) Male dominated, accounting for 72.34%; age concentrated in 15-49 years old, accounting for 68.94%; Han (61.11%), married (57.05%), junior high school and below education level (79.11%), occupation for farmers (including migrant workers) and workers (60.39%) mainly heterosexual transmission. (4) heterosexual transmission was the main route of infection. 66.31% of HIV-infected people were infected through heterosexual transmission; (5) heterosexual non-marital sex was the main high-risk behavior. 42.56% of HIV-infected people had heterosexual non-marital sex (at least one heterosexual partner), of which 80.59% had two or more heterosexual partners. (6) Clinic visits were the main way to find HIV-infected people. The patients were mainly found by clinical examination, accounting for 65.68%.
2. the classification and characteristics of Guangxi AIDS epidemic area
CPI, CP, CMR and CFR were divided into three groups according to the natural breakpoint grading method of GIS software, which corresponded to high, middle and low prevalence areas. The corresponding ranges were 1.54 8240to 4.24 82, 0.55 82to 1.53 82, 0.55 82to 1.53 82, 0.06 82to 0.54 82. CMR was high, 4, 20, 85 count (city, district) in the middle and low endemic areas were 4, 20, 85, the corresponding ranges were 0.58 82to 1.26 82, 0.17 82to 1.57 82, 0.17 82to 0.57 82, 0.00 82to 0.16 82 82. CFR was high, the middle and low endemic areas were 4, 20, 20 and 85 respectively, the corresponding ranges were 0.58 82 82to 1.26 8218,45,46, respectively 27.25% ~ 50%, 13.28% ~ 27.24%, 0% ~ 13.27%.
The coincidence rates of CPI and CP were 86.67%, 84.44%, 93.88% and 88.99% respectively. The counties (cities and districts) with higher CPI and CP had earlier AIDS epidemic, mainly distributed in border cities, Liuzhou city and its surrounding areas. The counties (cities, districts) in the middle are mainly divided into two clusters: the cluster with the high prevalence counties in the Liuzhou area as the center and the cluster with the high prevalence counties in the border cities as the beginning, and the cluster spreading inward. It is mainly from the northeast to southwest to about 45 degrees inclined to the relatively developed economy, traffic is more convenient in the central zone. CMR is high, the counties (cities, districts) included in the epidemic areas are consistent with CPI, CP. However, in the counties (cities, districts) under the jurisdiction of the high prevalence areas of CFR, 77.78% of the CPI, CP, CMR are low.
conclusion
1. The cumulative base of HIV infection sources in Guangxi is large. The epidemic characteristics of AIDS from 1996 to 2012 show a slow and fast trend, but it began to decline in 2012. 43.42% of HIV-positive people in Guangxi were infected with AIDS when they were first confirmed. The main route of infection is heterosexual contact transmission, and the main high-risk behavior is heterosexual non-marriage. Therefore, targeted prevention and control strategies and measures, such as the promotion of simple and fast HIV testing methods, to strengthen AIDS-related health education for the less educated population, to further promote sexual behavior, especially the use of condoms in non-marital sexual behavior, and other measures to prevent the further spread of AIDS through sexual channels in Guangxi. Of great significance.
2. The high, middle and low prevalence areas classified by the natural breakpoint classification method of GIS have higher coincidence rate, which provides convenience for visualizing the epidemic situation of AIDS in different counties (cities and districts) in Guangxi, but the influence of social and behavioral factors should be considered.
3. Aids prevention and control in Guangxi should focus on the high and middle prevalence areas of CPI and CP, while the low prevalence areas of CPI and CP (i.e. high prevalence areas of CFR) should focus on reducing the mortality of HIV/AIDS.
The second part is the mathematical discriminant model of the epidemic area in Guangxi.
objective
Taking CPI, CP, CMR (hereinafter referred to as three epidemic indicators) as the main indicators for stratified analysis, the epidemic patterns and trends of AIDS in different epidemic areas were analyzed, and the economic and sociological factors affecting the three epidemic indicators of AIDS in Guangxi were explored. The multiple linear regression model and 3. The mathematical discriminant model of the high, middle and low epidemic areas provides the basis for scientific formulation of AIDS prevention and control strategies.
Method
The data of economic and social development indicators in high, middle and low prevalence areas were collected, and the correlation between them and CPI, CP and CMR was analyzed by Spearman simple correlation method. Fisher stepwise discriminant method was used to establish mathematic discriminant models for different types of AIDS epidemic areas in Guangxi.
Result
1. Correlation between economic sociology development factors and CPI, CP, CMR: 8 economic sociology related indicators (population density X1, non-agricultural population proportion X2, natural population growth rate X3, per capita GDP X4, per capita disposable income X5 of urban residents, per capita net income X6 of rural residents, nine-year compulsory education completion rate of educated population) Spearman correlation analysis showed that X1, X2, X4, X5, X6, X7 were correlated with CPI and CP (P 0.10), X2, X4, X6, X7 were correlated with CMR (P 0.10).
2. Economic and sociological development factors affecting CPI, CP and CMR: (1) The regional economic and sociological factors affecting CPI are X2, X4, X5, X6, X7, the multi-factor model influencing factor is X7, the discriminant model influencing factor is X4, X7; the regional economic and sociological factors influencing CP are X2, X4, X6, X7, the discriminant model influencing factor is X4, X7, and the multi-factor model influencing factor is X7. X2, X4, X7 were the regional socioeconomic factors influencing CMR, X4 was the multifactor model influencing factor, and X4.X4 was the common influencing factor of the three epidemic index regional classification discriminant models. X7 was the common influencing factor of CPI and CP regional classification discriminant models, and also had a positive correlation.
3. Establishment of mathematical discriminant models for different epidemic areas of CPI, CP and CMR: Combining with single factor analysis of statistically significant economic and social development factors and professional knowledge, the factors closely related to AIDS epidemic will be incorporated into Fisher stepwise discriminant model analysis.
3.1CPI discriminant model
CPI high endemic area: YH=-19.36+2.39 * 10-4X4+0.62X7
CPI epidemic area: YM=-19.97+4.68 * 10-4X4+0.69X7
CPI low epidemic area: YL=-15.72+4.27 * 10-4X4+0.61X7
3.2CP discriminant model
CP high endemic area: YH=-19.32+1.80 * 10-4X4+0.61X7
CP epidemic area: YM=-20.31+4.43 * 10-4X4+0.69X7
CP low epidemic area: YL=-15.97+4.29 * 10-4X4+0.62X7
3.3CMR discriminant model
High prevalence area of CMR: YH = - 3.78 + 3.78 *10-4X4 (because there are fewer research units in the high prevalence area of CMR divided by natural breakpoint method, the high and medium prevalence areas are merged into high prevalence areas in the modeling process)
CMR low epidemic area: YL=-2.54+2.92 * 10-4X4
4. Effect evaluation of discriminant model: The coincidence rate of each discriminant function was tested by substitution method: (1) The coincidence rate of discriminant function was 56.25%, 58.18%, 53.06% in high, medium and low prevalence areas respectively, and the total coincidence rate was 51.38%. (2) The coincidence rate of discriminant in high, middle and low prevalence areas was 53.84%, 48.78%, 52.4%, and the overall coincidence rate was 54.13%. (3) CMR. The discriminative coincidence rates in high and low endemic areas were 48% and 69.05% respectively, and the overall discriminant accordance rate was 64.22%.
conclusion
1.CPI, CP, CMR and CFR can fully reflect the epidemic intensity of AIDS in Guangxi.
2. The per capita GDP (X4) and the nine-year compulsory education completion rate (X7) of the educated population are important economic and sociological factors to promote the AIDS epidemic in Guangxi.
3. Establishing mathematical discriminant model can be considered in the division of AIDS epidemic areas in Guangxi, but the improvement of the discriminant coincidence rate still needs to be combined with the influence of diverse, complex behavior, biology and other factors.
【學位授予單位】：廣西醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：R512.91

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