2010―2020年成都市50岁及以上HIV/AIDS空间聚集性

施雅莹; 陈思琪; 何勤英; 段振华; 奚静; 朱彦锋

doi:10.16462/j.cnki.zhjbkz.2022.12.004

2010―2020年成都市50岁及以上HIV/AIDS空间聚集性

doi: 10.16462/j.cnki.zhjbkz.2022.12.004

1.
610041 成都，成都市疾病预防控制中心性病艾滋病防制科
2.
610500 成都，成都医学院公共卫生学院

基金项目:

四川养老与年健康协同创新中心 YLZBS2002

详细信息

通讯作者:
朱彦锋，E-mail: cmc_zhuyanfeng@163.com

中图分类号: B512.91
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出版历程
- 收稿日期: 2022-03-23
- 修回日期: 2022-06-17
- 网络出版日期: 2022-12-30
- 刊出日期: 2022-12-10

Spatial clustering of HIV/AIDS cases aged 50 years and above in Chengdu from 2010 to 2020

1.
Department of STD/AIDS Control and Prevention, Chengdu Center for Disease Control and Prevention, Chengdu 610041, China
2.
School of Public Health, Chengdu Medical College, Chengdu 610500, China

Funds:

Collaborative Innovation Center of Sichuan for Elderly Care and Health YLZBS2002

More Information

Corresponding author: ZHU Yan-feng, E-mail: cmc_zhuyanfeng@163.com

摘要

摘要: 目的分析2010―2020年成都市50岁及以上HIV感染者和AIDS病人(简称HIV/AIDS)的空间聚集性特征和趋势，为50岁及以上艾滋病的区域化防控及资源调整提供参考依据。方法从“中国疾病预防控制信息系统”筛选出2010―2020年成都市新报告的50岁以上HIV/AIDS并进行描述性分析，运用ArcGIS 10.6软件开展时空自相关分析及空间聚集性分析。结果成都市50岁及以上新报告的HIV/AIDS近11年年均增长率为28.95%，病例普遍以小学文化程度为主，占50.07%；已婚有配偶，占63.00%；职业为农民为主，占61.98%；异性传播，占95.72%。HIV/AIDS人数在区域范围内呈现聚集性分布，病例高－高型聚集区随时间推移：北部地区由西部两个区县逐渐向东扩散至四个区县，并向南扩散到周边两个区县；南部地区三个区县扩散至周边四个区县。结论 2010―2020年成都市50岁及以上人群HIV/AIDS数持续增加，空间分布上呈现出明显的不均衡性，疫情较严重的区域集中在成都市中部偏北，随时间推移中部地区和东部地区的热点区域逐渐增多，并且呈现扩散趋势。
- 艾滋病 /
- 50岁及以上 /
- 空间自相关 /
- 地理信息系统
Abstract: Objective To explore the spatial clustering characteristics and trends of AIDS among HIV/AIDS cases aged 50 years and above in Chengdu from 2010 to 2021. And to provide a reference basis for regionalised prevention and control of AIDS. Methods HIV/AIDS cases aged 50 years or above in Chengdu between 2010 and 2020 were selected from China information system for disease control and prevention, and descriptive analysis was carried out. Moreover, spatial and temporal autocorrelation and spatial aggregation analyses were conducted using ArcGIS 10.6 software. Results The average annual growth rate was 28.95% over the last 11 years among HIV/AIDS cases aged 50 years and above in Chengdu. Of 50.07% AIDS aged 50 years and above have only received primary education, 63.00% were unmarried. 61.98% of cases were farmers. Heterosexual transmission accounts for 95.72% of cases. HIV/AIDS cases were in a pattern of aggregative distribution. Areas of high-high case were clustering over time. In northern region, high-high aggregation areas gradually spreads from two districts in the west eastwards to four districts and southwards to two adjacent districts. However in southern region high-high aggregation areas spreads from three districts to four adjacent districts. Conclusions The spatial distribution of HIV/AIDS cases among aged 50 years and above in Chengdu is not random, and there is spatial clustering. The high-value clustering area gradually develops from central northern regions of Chengdu to central and eastern regions.
- AIDS /
- Aged 50 years and above /
- Spatial autocorrelation /
- GIS system

HTML全文

图 1 2010―2020年成都市50岁及以上新报告AIDS病例聚类和异常值分析

注：本图基于国家地理信息公共服务平台下载的成都市2018年矢量化乡镇/街道级地理电子地图制作，底图无修改。

Figure 1. Anselin Local Moran's I of newly reported HIV/AIDS cases aged 50 years and above in Chengdu, 2010-2020

下载: 全尺寸图片幻灯片

图 2 2010―2020年成都市50岁及以上新报告AIDS病例热点分析

注：本图基于国家地理信息公共服务平台下载的成都市2018年矢量化乡镇/街道级地理电子地图制作，底图无修改。

Figure 2. Getis-Ord Gi of newly reported HIV/AIDS cases aged 50 years and above in Chengdu, 2010-2020

下载: 全尺寸图片幻灯片

表 1 2010―2020年全局自相关系数和G统计量分析结果

Table 1. Results of the analysis of Global Moran's I and Getis-Ord General for 2010-2020

年份(年)	自相关系数			G统计量
年份(年)	Moran’s I值	Z值	P值	General G值	期望指数值	Z值	P值
2010	0.696	6.278	＜0.001	0.023	0.008	3.250	0.001
2011	0.525	5.771	＜0.001	0.025	0.007	4.765	＜0.001
2012	0.424	6.283	＜0.001	0.024	0.010	4.900	＜0.001
2013	0.228	4.090	＜0.001	0.020	0.013	3.368	＜0.001
2014	0.322	6.163	＜0.001	0.023	0.012	6.226	＜0.001
2015	0.163	3.730	＜0.001	0.019	0.011	6.240	＜0.001
2016	0.174	4.144	＜0.001	0.022	0.013	8.635	＜0.001
2017	0.246	6.013	＜0.001	0.023	0.013	9.583	＜0.001
2018	0.227	6.180	＜0.001	0.022	0.014	9.324	＜0.001
2019	0.251	7.034	＜0.001	0.023	0.014	10.700	＜0.001
2020	0.185	3.822	＜0.001	0.019	0.011	6.240	＜0.001

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