海南省瘧疾疫情時(shí)空分析及影響因素研究
發(fā)布時(shí)間：2019-07-04 12:25
【摘要】：研究目的 通過對(duì)1990年-2010年海南省瘧疾疫情時(shí)空分析及影響因素的研究，為該省及類似地區(qū)瘧疾防控提供科學(xué)依據(jù)。通過嘗試時(shí)間空間分析技術(shù)與統(tǒng)計(jì)分析方法在瘧疾研究領(lǐng)域的綜合應(yīng)用，為類似研究提供方法學(xué)參考。 研究方法 收集整理1990-2010年海南省瘧疾疫情監(jiān)測數(shù)據(jù)，將全國1:100萬電子地圖加工處理為1:100萬海南省市縣邊界圖。提取海南省各縣市的氣溫、降水量、濕度等氣象與環(huán)境數(shù)據(jù)，人口、GDP、衛(wèi)生、人民生活指標(biāo)等數(shù)據(jù)，建立海南省市縣綜合信息數(shù)據(jù)庫。應(yīng)用時(shí)空掃描統(tǒng)計(jì)量、時(shí)間序列分析方法、主成分分析以及多元線性回歸分析方法對(duì)資料進(jìn)行分析。所采用的軟件包括Excel2003、SatScan9.0、SPSS13.0、Mapinfo7.0等統(tǒng)計(jì)軟件。 研究結(jié)果 1.1990年-2010年海南省瘧疾呈整體下降的趨勢，總體來說，海南省瘧疾發(fā)病最高峰為7、8月份，2月份為全年發(fā)病最低峰。海南省西南部地區(qū)是瘧疾疾病的高發(fā)區(qū)。人群分布，30-50歲男性為高發(fā)人群，農(nóng)民、工人及民工占總報(bào)告人數(shù)的85.11%。 2.運(yùn)用時(shí)空重排掃描統(tǒng)計(jì)量對(duì)2005-2010年瘧疾發(fā)病數(shù)據(jù)進(jìn)行分析發(fā)現(xiàn)，2005-2010年海南省可能存在7個(gè)瘧疾聚集區(qū)域（P0.05）。對(duì)2010年瘧疾發(fā)病數(shù)據(jù)進(jìn)行時(shí)空掃描發(fā)現(xiàn)有3個(gè)聚集區(qū)域（P0.05）。運(yùn)用2005年1月-2009年12月建立的ARIMA模型對(duì)海南省2010年1月份的疾病發(fā)病率進(jìn)行預(yù)測，預(yù)測值為0.15/10萬，95%的可信區(qū)間為[-1.04,1.33]，實(shí)際檢測發(fā)病率為0.17/10萬，瘧疾月發(fā)病率實(shí)際值落入了預(yù)測值的95%可信區(qū)間內(nèi)，預(yù)測相對(duì)誤差為11.8%。將2010年1月份瘧疾實(shí)際發(fā)病率納入時(shí)間序列模型，重新擬合，，并對(duì)2010年2-12月份瘧疾發(fā)病率進(jìn)行預(yù)測，實(shí)際瘧疾發(fā)病率比理論瘧疾發(fā)病率平均下降了85.75%。 3.將15個(gè)溫度指標(biāo)和13個(gè)降水量指標(biāo)進(jìn)行主成分分析得其主成分，并以2010年市縣瘧疾發(fā)病率為因變量，男性人口、農(nóng)業(yè)人口、少數(shù)名族人口、GDP、第一產(chǎn)業(yè)、第二產(chǎn)業(yè)、第三產(chǎn)業(yè)、人均GDP、衛(wèi)生機(jī)構(gòu)總數(shù)、執(zhí)業(yè)醫(yī)師人數(shù)、農(nóng)村居民家庭人均純收入、城市居民家庭人均純收入、溫度主成分、降雨量主成分、濕度等為解釋變量構(gòu)建結(jié)局變量為連續(xù)型變量的多元線性回歸模型。其中，瘧疾發(fā)病的危險(xiǎn)因素的包括“城市居民家庭人均純收入”、“降水量主成分2”、“濕度”這三個(gè)因素，瘧疾發(fā)病的保護(hù)因素包括“男性人口”、“農(nóng)業(yè)人口”、“人均GDP”、“醫(yī)療機(jī)構(gòu)個(gè)數(shù)”、“執(zhí)業(yè)醫(yī)師個(gè)數(shù)”、“農(nóng)村居民家庭人均純收入”這6個(gè)因素。 研究結(jié)論 本課題重點(diǎn)探討了1990-2010年海南省瘧疾流行病學(xué)特征和時(shí)空聚集性，還重點(diǎn)研究了海南省不同市縣瘧疾疫情存在差異的主要影響因素。在海南，瘧疾的流行有一定的周期性、地域性，并在某些特定人群中有較高的發(fā)病率。時(shí)間序列模型可以很好的擬合瘧疾發(fā)病率在時(shí)間序列上的變化趨勢。在防治措施、人口免疫狀態(tài)及人口流動(dòng)沒有發(fā)生大幅度變化的時(shí)候可以用來預(yù)測瘧疾的發(fā)病率變化。海南省2010年起開始實(shí)施的消除瘧疾計(jì)劃作用明顯，時(shí)間序列模型從側(cè)面也證明了這一點(diǎn)。另外，降水量和濕度將影響海南省瘧疾在各市縣的發(fā)病，而經(jīng)濟(jì)、衛(wèi)生和人民生活水平也是影響瘧疾發(fā)病的重要因素。這一研究結(jié)果將有助于當(dāng)?shù)剡M(jìn)一步在多方面對(duì)瘧疾疫情進(jìn)行防控。創(chuàng)新點(diǎn) 本課題在整個(gè)研究過程中，將多個(gè)領(lǐng)域的信息與知識(shí)進(jìn)行了整合。將瘧疾疫情數(shù)據(jù)進(jìn)行時(shí)間、空間上的整合，打破了時(shí)間與空間的限制，不僅僅研究了有網(wǎng)絡(luò)直報(bào)系統(tǒng)以來的數(shù)據(jù)，而且還研究了從1990年來的瘧疾發(fā)病數(shù)據(jù)。在空間上，打破了縣市的界限，對(duì)海南省全省疫情進(jìn)行空間掃描，為瘧疾疾病的預(yù)警提供新思路。將人口學(xué)、經(jīng)濟(jì)學(xué)及衛(wèi)生學(xué)知識(shí)相融合，使得瘧疾疫情及影響因素的分析更加的立體，更加的貼合實(shí)際。將自然因素與社會(huì)因素相結(jié)合的分析方法在國內(nèi)外的瘧疾研究領(lǐng)域較為罕見。
[Abstract]:Purpose of the study To provide scientific basis for malaria prevention and control in the province and similar areas through the study of the time-space analysis and the influencing factors of the malaria epidemic in Hainan Province from 1990 to 2010. According to the comprehensive application of the method of time-space analysis and statistical analysis in the field of malaria research, it provides methodological reference for similar research. An examination. The research method collects the monitoring data of the malaria epidemic in Hainan Province from 1990 to 2010, and the national 1:1 million electronic map processing and processing is 1:1 million Hainan. The boundary map of the city and county. The data such as air temperature, precipitation, humidity and other meteorological and environmental data, population, GDP, health and people's living standards in various counties and counties of Hainan are extracted to establish a comprehensive city and county of Hainan Province. Information database. Application of space-time scanning statistics, time series analysis method, principal component analysis and multivariate linear regression analysis method The materials used include Excel2003, SatScan9.0, SPSS13.0, Mapinfo 7.0. equal statistical soft According to the results of the study, the total incidence of malaria in Hainan Province from 1990 to 2010 is the trend of overall decline. In general, the peak of malaria in Hainan Province is 7, August and February. The lowest peak in the whole year of the whole year. Is a high-risk area of malaria. Population,30-50-year-old male is a high-risk group, and farmers, workers and migrant workers account for the total report. The number of malaria cases was 85.11%.2. The analysis of the data of malaria in 2005-2010 was carried out by using the time-space rearrangement scanning statistic, and there may be 7 malaria cases in Hainan province from 2005 to 2010. The area of aggregation (P0.05). The time-and-space scan of the malaria incidence data in 2010 was found to be 3 The disease incidence of Hainan Province in January 2010 was predicted with the ARIMA model established in January-December,2009. The predicted value was 0.15/ 100,000, and the confidence interval of 95% was[-1.04, 1.33], and the actual detection was made. In the case of 0.17/ 100,000, the actual value of the monthly incidence of malaria falls within the 95% confidence interval of the predicted value, pre- The relative error is 11.8%. The actual incidence of malaria in January 2010 is included in the time series model, re-fitted, and the incidence of malaria in the period from February to December 2010 is predicted, and the actual incidence of malaria is higher than the theoretical malaria incidence The average decrease of 85.75%.3. The main components of 15 temperature indexes and 13 precipitation indexes are analyzed to obtain the main components, and the incidence of malaria in the city of the city in 2010 is the dependent variable, the male population, the agricultural population, the minority population, the GDP, the first industry, the second industry, Industrial, tertiary industry, per capita GDP, total number of health facilities, number of medical practitioners, net income per person in rural households, net income per person of urban resident, main component of temperature, main component of rainfall, humidity, etc., and the construction outcome variable of the interpretation variable is continuous The multivariate linear regression model of the continuous variable is the three factors including "per capita net income of urban residents", "Precipitation principal component 2" and "humidity", including "male population", "agricultural population", "per capita GDP", "Number of medical institutions", "Number of medical practitioners",
本文編號(hào)：2509910
[Abstract]:Purpose of the study To provide scientific basis for malaria prevention and control in the province and similar areas through the study of the time-space analysis and the influencing factors of the malaria epidemic in Hainan Province from 1990 to 2010. According to the comprehensive application of the method of time-space analysis and statistical analysis in the field of malaria research, it provides methodological reference for similar research. An examination. The research method collects the monitoring data of the malaria epidemic in Hainan Province from 1990 to 2010, and the national 1:1 million electronic map processing and processing is 1:1 million Hainan. The boundary map of the city and county. The data such as air temperature, precipitation, humidity and other meteorological and environmental data, population, GDP, health and people's living standards in various counties and counties of Hainan are extracted to establish a comprehensive city and county of Hainan Province. Information database. Application of space-time scanning statistics, time series analysis method, principal component analysis and multivariate linear regression analysis method The materials used include Excel2003, SatScan9.0, SPSS13.0, Mapinfo 7.0. equal statistical soft According to the results of the study, the total incidence of malaria in Hainan Province from 1990 to 2010 is the trend of overall decline. In general, the peak of malaria in Hainan Province is 7, August and February. The lowest peak in the whole year of the whole year. Is a high-risk area of malaria. Population,30-50-year-old male is a high-risk group, and farmers, workers and migrant workers account for the total report. The number of malaria cases was 85.11%.2. The analysis of the data of malaria in 2005-2010 was carried out by using the time-space rearrangement scanning statistic, and there may be 7 malaria cases in Hainan province from 2005 to 2010. The area of aggregation (P0.05). The time-and-space scan of the malaria incidence data in 2010 was found to be 3 The disease incidence of Hainan Province in January 2010 was predicted with the ARIMA model established in January-December,2009. The predicted value was 0.15/ 100,000, and the confidence interval of 95% was[-1.04, 1.33], and the actual detection was made. In the case of 0.17/ 100,000, the actual value of the monthly incidence of malaria falls within the 95% confidence interval of the predicted value, pre- The relative error is 11.8%. The actual incidence of malaria in January 2010 is included in the time series model, re-fitted, and the incidence of malaria in the period from February to December 2010 is predicted, and the actual incidence of malaria is higher than the theoretical malaria incidence The average decrease of 85.75%.3. The main components of 15 temperature indexes and 13 precipitation indexes are analyzed to obtain the main components, and the incidence of malaria in the city of the city in 2010 is the dependent variable, the male population, the agricultural population, the minority population, the GDP, the first industry, the second industry, Industrial, tertiary industry, per capita GDP, total number of health facilities, number of medical practitioners, net income per person in rural households, net income per person of urban resident, main component of temperature, main component of rainfall, humidity, etc., and the construction outcome variable of the interpretation variable is continuous The multivariate linear regression model of the continuous variable is the three factors including "per capita net income of urban residents", "Precipitation principal component 2" and "humidity", including "male population", "agricultural population", "per capita GDP", "Number of medical institutions", "Number of medical practitioners",
"per capita net income of rural housa. s" 【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：R531.3
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