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中国广西青年艾滋病病毒/艾滋病的分布及相关因素:贝叶斯时空分析。

The Distribution and Associated Factors of HIV/AIDS Among Youths in Guangxi, China, From 2014 to 2021: Bayesian Spatiotemporal Analysis.

机构信息

Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Guilin, 541100, China, 86 07733680605.

Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, 18 Jinzhou Road, Nanning, China.

出版信息

JMIR Public Health Surveill. 2024 Sep 27;10:e53361. doi: 10.2196/53361.


DOI:10.2196/53361
PMID:39331816
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11452016/
Abstract

BACKGROUND: In recent years, the number of HIV/AIDS cases among youth has increased year by year around the world. A spatial and temporal analysis of these AIDS cases is necessary for the development of youth AIDS prevention and control policies. OBJECTIVE: This study aimed to analyze the spatial and temporal distribution and associated factors of HIV/AIDS among youth in Guangxi as an example. METHODS: The reported HIV/AIDS cases of youths aged 15-24 years in Guangxi from January 2014 to December 2021 were extracted from the Chinese Comprehensive Response Information Management System of HIV/AIDS. Data on population, economy, and health resources were obtained from the Guangxi Statistical Yearbook. The ArcGIS (version 10.8; ESRI Inc) software was used to describe the spatial distribution of AIDS incidence among youths in Guangxi. A Bayesian spatiotemporal model was used to analyze the distribution and associated factors of HIV/AIDS, such as gross domestic product per capita, population density, number of health technicians, and road mileage per unit area. RESULTS: From 2014 to 2021, a total of 4638 cases of HIV/AIDS infection among youths were reported in Guangxi. The reported incidence of HIV/AIDS cases among youths in Guangxi increased from 9.13/100,000 in 2014 to 11.15/100,000 in 2019 and then plummeted to a low of 8.37/100,000 in 2020, followed by a small increase to 9.66/100,000 in 2021. The districts (counties) with relatively high HIV/AIDS prevalence among youths were Xixiangtang, Xingning, Qingxiu, Chengzhong, and Diecai. The reported incidence of HIV/AIDS among youths was negatively significantly associated with road mileage per unit area (km) at a posterior mean of -0.510 (95% CI -0.818 to 0.209). It was positively associated with population density (100 persons) at a posterior mean of 0.025 (95% CI 0.012-0.038), with the number of health technicians (100 persons) having a posterior mean of 0.007 (95% CI 0.004-0.009). CONCLUSIONS: In Guangxi, current HIV and AIDS prevention and control among young people should focus on areas with a high risk of disease. It is suggested to strengthen the allocation of AIDS health resources and balance urban development and AIDS prevention. In addition, AIDS awareness, detection, and intervention among Guangxi youths need to be strengthened.

摘要

背景:近年来,全球范围内青年人群中的艾滋病毒/艾滋病病例数量逐年增加。对这些艾滋病病例进行时空分析,对于制定青年艾滋病预防和控制政策至关重要。

目的:本研究旨在以广西为例,分析青年艾滋病的时空分布及相关因素。

方法:从中国艾滋病综合防治信息管理系统中提取 2014 年 1 月至 2021 年 12 月广西 15-24 岁青年艾滋病报告病例。从《广西统计年鉴》中获取人口、经济和卫生资源数据。使用 ArcGIS(版本 10.8;ESRI Inc)软件描述广西青年艾滋病发病率的空间分布。采用贝叶斯时空模型分析国内生产总值人均、人口密度、卫生技术人员数量和单位面积道路里程等因素与艾滋病的分布及相关因素。

结果:2014 年至 2021 年,广西共报告青年艾滋病病毒感染者 4638 例。广西青年艾滋病报告发病率从 2014 年的 9.13/10 万上升到 2019 年的 11.15/10 万,然后在 2020 年急剧下降至 8.37/10 万,随后在 2021 年略有上升至 9.66/10 万。艾滋病流行率较高的县(区)为西乡塘区、兴宁市、青秀区、城中区和叠彩区。青年艾滋病报告发病率与单位面积道路里程(km)呈显著负相关,后验均值为-0.510(95%置信区间-0.818 至 0.209)。青年艾滋病报告发病率与人口密度(100 人)呈正相关,后验均值为 0.025(95%置信区间 0.012-0.038),与卫生技术人员数量(100 人)呈正相关,后验均值为 0.007(95%置信区间 0.004-0.009)。

结论:在广西,目前青年艾滋病防控工作应重点关注高危地区。建议加强艾滋病卫生资源配置,平衡城乡发展与艾滋病防控。此外,还需加强广西青年艾滋病意识、检测和干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/24c97df1c6e5/publichealth-v10-e53361-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/04e749bc15eb/publichealth-v10-e53361-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/1caab2b909ee/publichealth-v10-e53361-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/24c97df1c6e5/publichealth-v10-e53361-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/04e749bc15eb/publichealth-v10-e53361-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/1caab2b909ee/publichealth-v10-e53361-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f8/11452016/24c97df1c6e5/publichealth-v10-e53361-g003.jpg

相似文献

[1]
The Distribution and Associated Factors of HIV/AIDS Among Youths in Guangxi, China, From 2014 to 2021: Bayesian Spatiotemporal Analysis.

JMIR Public Health Surveill. 2024-9-27

[2]
The Distribution of HIV and AIDS Cases in Luzhou, China, From 2011 to 2020: Bayesian Spatiotemporal Analysis.

JMIR Public Health Surveill. 2022-6-14

[3]
Spatiotemporal Analysis of HIV/AIDS Incidence in China From 2009 to 2019 and Its Association With Socioeconomic Factors: Geospatial Study.

JMIR Public Health Surveill. 2024-6-7

[4]
Effectiveness of human immunodeficiency virus prevention strategies by mapping the geographic dispersion pattern of human immunodeficiency virus prevalence in Nanning, China.

BMC Public Health. 2024-3-16

[5]
Spatial Analysis of the Human Immunodeficiency Virus Epidemic among Men Who Have Sex with Men in China, 2006-2015.

Clin Infect Dis. 2017-4-1

[6]
HIV molecular transmission networks among students in Guangxi: unraveling the dynamics of student-driven HIV epidemic.

Emerg Microbes Infect. 2025-12

[7]
Epidemiological and spatiotemporal analyses of HIV/AIDS prevalence among older adults in Sichuan, China between 2008 and 2019: A population-based study.

Int J Infect Dis. 2021-4

[8]
The HIV/AIDS epidemic among young people in China between 2005 and 2012: results of a spatial temporal analysis.

HIV Med. 2017-3

[9]
[Spatial-temporal distribution of newly reported HIV/AIDS cases in Henan Province, 1995-2020].

Zhonghua Liu Xing Bing Xue Za Zhi. 2024-12-10

[10]
[Spatial-temporal analysis on the human immunodeficiency virus/acquired immunodeficiency syndrome among permanent residence and migrants in Shanghai, 2005-2015].

Zhonghua Yu Fang Yi Xue Za Zhi. 2018-12-6

本文引用的文献

[1]
Spatial disparities of HIV prevalence in South Africa. Do sociodemographic, behavioral, and biological factors explain this spatial variability?

Front Public Health. 2022

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The Distribution of HIV and AIDS Cases in Luzhou, China, From 2011 to 2020: Bayesian Spatiotemporal Analysis.

JMIR Public Health Surveill. 2022-6-14

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A Bayesian Spatio-Temporal Analysis of Malaria in the Greater Accra Region of Ghana from 2015 to 2019.

Int J Environ Res Public Health. 2021-6-4

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Qual Health Res. 2021-8

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BMC Public Health. 2021-1-21

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PLoS Negl Trop Dis. 2020-3-20

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