Projecting dynamic trends for HIV/AIDS in a highly endemic area of China: estimation models for Liangshan Prefecture, Sichuan Province.
This study describes the current situation and projects dynamic trends for HIV prevalence in a highly endemic area of China, Liangshan Prefecture, Sichuan Province. Epidemiological, behavioral, and population census data from multiple sources were analyzed to extract input for an Asian Epidemic Model (AEM). Fitting curves to historical trends in HIV prevalence were used as a baseline, and future intervention scenarios were explored using the AEM. For 2007, modeled data suggested approximately 0.5% adult HIV prevalence in Liangshan, with an estimated 17,450 people living with HIV/AIDS and 3,400 new infections. With current high risk behaviors, the model predicts that adult prevalence will rise to 1.5% by 2020. Increased condom use and clean needle exchange among injection drug users (IDUs) have slowed the epidemic. The source of new HIV infections will change from a preponderance of IDU-related infections in 2007 (65.9%) to a mixed epidemic in 2020 (general population heterosexuals 45.2%, IDU 38.6%, homosexual transmission between men 12.7%, female sex workers and their clients 3.5%). We anticipate rising prevalence, stable incidence, and higher representation of sexual transmission over time. Prevention investments should target specific interventions toward sub-groups at highest risk, given that both IDUs and men who have sex with men will likely represent a majority of cases and serve as a bridge population.
Liu
Li
L
Department of Epidemiology, West China School of Public Health, Sichuan University, Chengdu, Sichuan 610041, P.R. China. liulir@163.com
Luan
Rongsheng
R
Yang
Wen
W
Zhang
Linglin
L
Zhang
Jianhua
J
Nan
Lei
L
Huang
Jun
J
Hu
Ying
Y
Mao
Guangyu
G
Feng
Liao
L
Gong
Yuhan
Y
Vermund
Sten H
SH
Jia
Yujiang
Y
D000328:Adult; D002681:China / Q000453:epidemiology; D019353:Endemic Diseases / Q000517:prevention & control*; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D008297:Male; D015233:Models, Statistical; D015995:Prevalence; D012307:Risk Factors