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中国深圳和重庆的艾滋病流行情况。

HIV epidemics in Shenzhen and Chongqing, China.

作者信息

Yang Shu, Chiu Alice P Y, Lin Qianying, Zeng Ziqian, Li Yafei, Zhang Yao, Yang Zhengrong, Yang Lin, He Daihai

机构信息

Chengdu Medical College, Chengdu, Sichuan, China.

Department of Applied Mathematics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (SAR) China.

出版信息

PLoS One. 2018 Feb 15;13(2):e0192849. doi: 10.1371/journal.pone.0192849. eCollection 2018.

DOI:10.1371/journal.pone.0192849
PMID:29447229
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5813969/
Abstract

OBJECTIVE

Men who have sex with men (MSM) and heterosexuals are the populations with the fastest growing HIV infection rates in China. We characterize the epidemic growth and age patterns between these two routes from 2004 to 2015 in Chongqing and Shenzhen, China.

DESIGN AND METHODS

Data were downloaded from the National HIV/ AIDS Comprehensive Response Information Management System. For the new HIV diagnoses of heterosexuals and MSM in both cities, we estimated the growth rates by fitting different sub-exponential models. Heat maps are used to show their age patterns. We used histograms to compare these patterns by birth cohort.

RESULTS

The MSM epidemics grew significantly in both cities. Chongqing experienced quadratic growth in HIV reported cases with an estimated growth rate of 0.086 per week and a "deceleration rate" of 0.673. HIV reported cases of MSM in Shenzhen grew even more drastically with a growth rate of 0.033 per week and "deceleration rate" of 0.794. The new infections are mainly affecting the ages of 18 to 30 in Chongqing and ages of 20 to 35 in Shenzhen. They peaked in early 1990's and mid-1990's birth cohorts in Chongqing and Shenzhen respectively. The HIV epidemic among heterosexuals grew rapidly in both cities. The growth rates were estimated as 0.02 and 0.028 in Chongqing and Shenzhen respectively whereas the "deceleration rates" were 0.878 and 0.790 in these two places. It affected mostly aged 18 to 75 in males and 18 to 65 in females in Chongqing and aged 18 to 45 in males and 18 to 50 in females in Shenzhen in 2015. In Chongqing, the heterosexual female epidemics display two peaks in HIV diagnoses in the birth cohorts of early 1950's and early 1980's, with heterosexual male epidemics peaked in early 1940's and early 1960's. The heterosexual male and female epidemics display higher rates in the birth cohort 1940-1960, than the birth cohort 1960-1990. It peaked in birth cohorts of 1950's and 1980's in Shenzhen.

CONCLUSIONS

We revealed striking differences in epidemic growth and age patterns of the HIV epidemics in these two cities. Our results may be used to inform age-targeted public health policies to curb their epidemic growth.

摘要

目的

男男性行为者(MSM)和异性恋者是中国艾滋病病毒(HIV)感染率增长最快的人群。我们对2004年至2015年中国重庆和深圳这两条传播途径之间的疫情增长和年龄模式进行了特征描述。

设计与方法

数据从国家艾滋病综合防治信息管理系统下载。对于两市异性恋者和男男性行为者的新HIV诊断病例,我们通过拟合不同的次指数模型来估计增长率。使用热图展示其年龄模式。我们用直方图按出生队列比较这些模式。

结果

两市男男性行为者疫情均显著增长。重庆报告的HIV病例呈二次增长,估计每周增长率为0.086,“减速率”为0.673。深圳男男性行为者报告的HIV病例增长更为迅猛,每周增长率为0.033,“减速率”为0.794。重庆新感染主要影响18至30岁人群,深圳主要影响20至35岁人群。分别在重庆1990年代初出生队列和深圳1990年代中期出生队列达到峰值。两市异性恋者中的HIV疫情均快速增长。重庆和深圳的增长率分别估计为0.02和0.028,而两地的“减速率”分别为0.878和0.790。2015年在重庆主要影响18至75岁男性和18至65岁女性,在深圳主要影响18至45岁男性和18至50岁女性。在重庆,异性恋女性疫情在20世纪50年代初和80年代初出生队列的HIV诊断中有两个峰值,异性恋男性疫情在20世纪40年代初和60年代初达到峰值。异性恋男性和女性疫情在1940 - 1960年出生队列中的发生率高于1960 - 1990年出生队列。在深圳,疫情在20世纪50年代和80年代出生队列达到峰值。

结论

我们揭示了这两个城市HIV疫情在流行增长和年龄模式上的显著差异。我们的结果可用于为有针对性的年龄公共卫生政策提供信息,以遏制其疫情增长。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/422709731cc8/pone.0192849.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/695bd2ed3a9e/pone.0192849.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/82b377fdabfb/pone.0192849.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/71cd66717f24/pone.0192849.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/422709731cc8/pone.0192849.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/695bd2ed3a9e/pone.0192849.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/82b377fdabfb/pone.0192849.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/71cd66717f24/pone.0192849.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baf1/5813969/422709731cc8/pone.0192849.g006.jpg

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