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京津唐地区HFMD时空变异分析与影响因子探测
引用本文:张湘雪,王丽,尹礼唱,徐成东,李霞,刘杨.京津唐地区HFMD时空变异分析与影响因子探测[J].地球信息科学,2019,21(3):398-406.
作者姓名:张湘雪  王丽  尹礼唱  徐成东  李霞  刘杨
作者单位:1. 长安大学地球科学与资源学院,西安 7100542. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 1001013. 河南大学环境与规划学院,开封 4750044. 贵州科学院,贵阳5500015. 国家食品安全风险评估中心,北京100022
基金项目:资源与环境信息系统国家重点实验室自主创新项目(O88RA205YA、O88RA200YA);公益性科研专项(GYHY20140616)
摘    要:手足口病(HFMD)是一种多发于儿童的常见传染病。近年来,中国HFMD发病人数逐年上升,疾病疫情也日益受到社会广泛关注。虽已有不少相关研究,但对于探测其时空异质性及量化潜在影响因子解释力的研究仍然较少。本文采用地理探测器及贝叶斯时空层次模型,对2009-2013年京津唐地区HFMD发病率的时空异质性进行分析,并量化各影响因子及其两两交互作用对HFMD发病率的解释力。结果表明:① HFMD的相对风险存在时间异质性,其发病风险在春夏季(5-7月)达到峰值,而冬季(12-次年2月)发病风险最低;② HFMD的相对风险存在空间异质性,在经济发达的地区HFMD发病率较高;③ 影响HFMD发病率时间异质性的主要气象因子为平均温度、累积降水、相对湿度,解释力分别为0.38,0.27,0.13,且交互作用都大于独自影响的作用,如平均温度和相对湿度、平均温度和降水,平均温度和风速两两交互的解释力分别为0.43, 0.40, 0.42。通过研究京津唐地区HFMD发病率的时空异质性以及影响因子的量化状况,为本地区HFMD的预防和控制提供理论依据。

关 键 词:手足口病  地理探测器  时空异质性  解释力  气象因子  
收稿时间:2018-10-14

Spatiotemporal Variation Analysis and Risk Determinants of Hand,Foot and Mouth Disease in Beijing-Tianjin-Tangshan,China
Xiangxue ZHANG,Li WANG,Lichang YIN,Chengdong XU,Xia LI,Yang LIU.Spatiotemporal Variation Analysis and Risk Determinants of Hand,Foot and Mouth Disease in Beijing-Tianjin-Tangshan,China[J].Geo-information Science,2019,21(3):398-406.
Authors:Xiangxue ZHANG  Li WANG  Lichang YIN  Chengdong XU  Xia LI  Yang LIU
Institution:1. The School of Earth Science and Resources, Chang'an University, Xi’an 710054, China;2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China3. The College of Environment and Planning of Henan University, Kaifeng 475004, China4. Guizhou Academy of Sciences,Guiyang 550001, China5. China National Center for Food Safety Risk Assessment, Beijing 100022, China
Abstract:Hand, foot and mouth disease (HFMD) is a common infectious childhood disease. In recent years, the number of cases of HFMD in China has increased rapidly, and has received increasing attention. Although there are many related studies, only a few studies focus on the spatiotemporal heterogeneity of HFMD incidence and quantify the association between meteorological factors, socioeconomic variables, and HFMD incidence. Geodetector and Bayesian space-time hierarchical models were applied to analyze the spatiotemporal heterogen-eity of the HFMD incidence from 2009 to 2013 within the Beijing-Tianjin-Tangshan region. These were used to quantify the determinant power of meteorological factors, socioeconomic variables, and the interactions between two of these factors. The Geodetector method has the axiom that if an explanatory variable (x) determined an explained variable (y), the explained variable would exhibit a spatial distribution similar to that of the explanatory variable. This method has been widely used to measure the determinant power of potential explanatory variables. The Bayesian space-time hierarchical model has the potential to show the spatiotemporal variation of a geographic phenomenon. The results showed that: (1) the highest incidence of HFMD occurred in late spring and summer (May to July), and the lowest incidence occurred in winter (December to February). (2) Spatial heterogeneity existed. In particular high risks areas were mainly concentrated in areas of high economic development. The population density and proportion of the tertiary industry determinants, play a lead role in contributing to the spatial heterogeneity of HFMD incidence (q values of 0.35 and 0.28, respectively, as calculated by GeoDetector). (3) The main meteorological factors affecting the temporal heterogeneity of HFMD incidence were average temperature, cumulative precipitation, and relative humidity (with a determinant powers calculated by GeoDetector of 0.38, 0.27 and 0.13, respectively). Additionally, the interactions were greater than the independent effects between socioeconomic variables or meteorological factors. For example, the interaction of average temperature and relative humidity, average temperature and precipitation, average temperature and wind speed were 0.43, 0.40 and 0.42, respectively. The interaction of population density and proportion of the tertiary industry was 0.55. This result presented the strongest correlation with HFMD incidence. Temperature and relative humidity were also dominant factors influencing the spatiotemporal transmission of HFMD, along with areas of high economic development with high population density. This study provides a theoretical basis for the prevention and control of HFMD by detecting the spatiotemporal heterogeneity of the HFMD incidence and quantifying the impact factors within the study region.
Keywords:Hand  foot  and mouth disease  GeoDetector  spatiotemporal heterogeneity  determinant power  meteorological factors  
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