首页|面向疾病的空间聚集性与影响因素分析方法

面向疾病的空间聚集性与影响因素分析方法

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疾病的发生与自然环境、社会环境和人群特点密切相关,其发生与流行通常具有一定的空间分布特征.目前在疾病空间聚集特征与影响因素的已有研究中缺少两者关联关系的探讨,以及空间尺度多集中于省、市和县域,因此,本研究提出一种面向疾病空间聚集性与影响因素分析的方法.以武汉市的历史肺结核数据为例,进行基于乡镇尺度的肺结核发病率数据及影响因素数据的处理与整合,基于空间自相关方法分析 2011 年、2013 年和2015年肺结核空间聚集情况;并运用地理探测器探测肺结核发病率空间分布的影响因素及交互作用,探究肺结核空间聚集的成因.结果表明:肺结核热点聚集乡镇主要分布在新洲区、江夏区和蔡甸区,冷点聚集乡镇主要分布在洪山区;植被指数、人口密度、人均 GDP 及五类兴趣点密度(医疗保健类、生活服务类、餐饮类、住宅类和农林牧渔类)为肺结核发病率空间分布的主要影响因素,其交互作用对肺结核发病率影响显著增强.研究成果可为武汉市肺结核防治提供科学参考.
Analysis method for disease-oriented spatial clustering and influencing factors
With the rapid development of computer science,geographic information system(GIS),and spatial analysis algorithms,it provides a solid technical foundation for mining multi-dimensional and massive disease data.This technology is widely used in early warning,cluster analysis,and disease mapping of epidemics.The occurrence of diseases is closely related to the characteristics of the population,the natural environment,and the social environment,and their occurrence and epidemic often have certain spatial distribution characteristics.Tuberculosis is one of the important public health problems in China,and studying its spatial clustering and influencing factors is of great significance to guide tuberculosis prevention and control.Although there are abundant research results on the spatiotemporal characteristics and influencing factors of tuberculosis at home and abroad,there are still some shortcomings.At present,there is a lack of research on the characteristics and influencing factors of tuberculosis clustering,and there is a lack of methods to analyze the characteristics and causes of spatial clustering of diseases,making it difficult to effectively explain the causes of spatial clustering.At the same time,most current studies on the spatial clustering characteristics and influencing factors of tuberculosis focus on provincial,municipal,and county scales,with few studies conducted on larger spatial scales.To solve these problems,this paper proposes a method for analyzing disease spatial clustering and influencing factors.Firstly,based on historical tuberculosis data from the Wuhan area,data processing and integration of the incidence data and influencing factors of tuberculosis in the township units of Wuhan City were realized.Subsequently,the spatial autocorrelation method was used to analyze the spatial clustering of tuberculosis in Wuhan in 2011,2013,and 2015.The influencing factors and interactions of the spatial distribution of tuberculosis incidence were detected by geographic detectors,aiming to reveal the causes of the spatial clustering of tuberculosis.Our results show that:①In 2011,2013,and 2015,there are obvious spatial clustering characteristics of tuberculosis in Wuhan,with"hot spots"towns mainly distributed in Xinzhou,Jiangxia,and Caidian Districts,and"cold spots"towns mainly distributed in Hongshan District.②Normalized Difference Vegetation Index,population density,per capita GDP,and density of point of interest(health care,life services,catering,housing,agriculture,forestry,animal husbandry,and fishery)are the main influencing factors for the incidence of tuberculosis.Moreover,the interaction between these factors significantly enhances the incidence of tuberculosis.③ At the township scale of Wuhan,the high-risk areas corresponding to each influencing factor can better explain the reasons for the spatial clustering of tuberculosis,providing a scientific reference for the prevention and control of tuberculosis in Wuhan.

tuberculosisspatial clusteringspatial autocorrelationgeographic detectorspoint of interest

胡涛、王丽娜、李响、张正斌、俞鑫楷

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信息工程大学 地理空间信息学院,郑州 450052

郑州轻工业大学 计算机科学与技术学院,郑州 450001

武汉市结核病防治所结核病控制办公室,武汉 430030

肺结核 空间聚集性 空间自相关 地理探测器 兴趣点

国家自然科学基金

42201490

2024

地理信息世界
中国地理信息产业协会 黑龙江测绘地理信息局

地理信息世界

CSTPCD
影响因子:0.826
ISSN:1672-1586
年,卷(期):2024.31(1)
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