Estimates of HIV prevalence in a highly endemic area of China: Dehong Prefecture, Yunnan Province.

Jia Y, Sun J, Fan L, Song D, Tian S, Yang Y, Jia M, Lu L, Sun X, Zhang S, Kulczycki A, Vermund SH
Int J Epidemiol. 2008 37 (6): 1287-96

PMID: 18922804 · PMCID: PMC2638873 · DOI:10.1093/ije/dyn196

BACKGROUND - Dehong Prefecture in Yunnan Province, China, borders Myanmar. Its proximity to the 'Golden Triangle', one of the world's largest illicit drug production and distribution centre, contributes to drug trafficking and ready availability of heroin. Dehong's 1.1 million people confront a serious HIV problem fuelled by injection drug use. The aim of this study is to improve the 2005 estimates of the true status of the HIV/AIDS epidemic in Dehong Prefecture.

METHODS - We estimated the HIV prevalence by synthesizing the results from several data sources (HIV/AIDS case reports, surveys, surveillance activities and epidemiological studies). We applied three different statistical procedures for estimations: (i) The Workbook method, adapted to meet the estimation needs in Dehong Prefecture; (ii) An estimate based on antenatal clinical data; and (iii) a dynamic model based on the local epidemic pattern.

RESULTS - We estimated that the population prevalence for HIV infections in Dehong Prefecture is 1.3% (likely range from low/high of three estimates: 0.9-1.7%) such that 13 500 people were living with HIV/AIDS in Dehong Prefecture (likely range: 8,200-18,300) in 2005. Infections remain concentrated among injection drug users, female sex workers and their clients with an uneven geographical distribution of estimated cases.

CONCLUSION - More reliable estimates of HIV prevalence can be made by synthesizing multiple data sources using several procedures. Current HIV prevention, care and treatment challenges are judged substantial in Dehong Prefecture, regardless of what modelling strategy is used.

MeSH Terms (18)

Adolescent Adult Child Child, Preschool China Data Collection Developing Countries Disease Outbreaks Female HIV-1 HIV Infections Humans Infant Infant, Newborn Male Middle Aged Models, Statistical Prevalence

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