Association between Drug Co-use Networks and HIV Infection:A Latent Profile Analysis in Chinese Mainland  

作　　者：Bo Zhang Xiangyu Yan Yongjie Li He Zhu Zuhong Lu Zhongwei Jia 

机构地区：[1]School of Public Health,Peking University,Beijing 100191,China [2]China Center for Health Development Studies,Peking University,Beijing 100191,China [3]State Key Laboratory for Bioelectronics,School of Biological Science and Medical Engineering Southeast University,Nanjing 210009,China [4]Center for Intelligent Public Health,Institute for Artificial Intelligence,Peking University,Beijing 100191,China [5]Center for Drug Abuse Control and Prevention,National Institute of Health Data Science,Peking University,Beijing 100191,China

出　　处：《Fundamental Research》2021年第5期552-558,共7页自然科学基础研究（英文版）

基　　金：supported by the National Natural Science Foundation of China[Grant No.91546203,91846302 and 72104008];the Chinese Ministry of Public Security[Grant No.0716-1541GA590508];the Ministry of Science and Technology of the People’s Republic of China[Grant No.2020YFC0849200];the Beijing Advanced Discipline Construction Project[Grant No.BMU2021GJJXK002]。

摘　　要：Persons who use drugs are a high-risk subpopulation for HIV infection because more than one drug user often take drugs together,which increases the risk of HIV transmission.For the PWUDs who had tested for HIV,we extracted data on demographic characteristics,drug types,injection drug use behavior,encrypted IDs of co-users,and drug use location from the National Dynamic Management and Control Database for Persons Who Use Drugs between January 2008 and July 2016.We mapped and classified Co-UDs’networks and estimated the risk of HIV infection.Drug co-use networks were formulated on the basis of connections between PWUDs at the same time and location.Latent profile analysis(LPA)and logistic regression models were used to cluster the classes and to estimate the HIV infection risk among them,respectively.A total of 470967 PWUDs were included,among whom 69529 Co-UDs formed 7001 networks,which were categorized into three classes:Class A(n=211,3.0%)had large networks,with more members(median 10.0(IQR:8.0-14.5)),and comprised depressant and stimulant users located in central and eastern China;Class B(n=3770,53.8%)was dominated by depressant users(median 3.0(IQR:3.0-4.0))across the country;Class C(n=3020,43.1%)was dominated by stimulant users(median 3.0(IQR:3.0-4.0))located in central and eastern China.The HIV infection rates were 9.71%,3.33%,and 0.33%in Classes A,B,and C,respectively.Compared with Class A,Classes B and C were associated with decreased odds of HIV infection.Our findings suggest that more attention should be paid to larger networks,with a relatively high HIV infection risk,to enhance prevention and intervention strategies.

关 键 词：Network Persons who use drugs HIV Depressant STIMULANT China 

分 类 号：R512.91[医药卫生—内科学]