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HIV incidence and associated risk factors among female sex workers in a high HIV prevalence area of China. Kathleen H. Reilly, MPH 6th IAS Conference on HIV Pathogenesis, Treatment and Prevention Rome, Italy July 19, 2011. Background.
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HIV incidence and associated risk factors among female sex workers in a high HIV prevalence area of China Kathleen H. Reilly, MPH 6th IAS Conference on HIV Pathogenesis, Treatment and Prevention Rome, Italy July 19, 2011
Background • Sexual transmission is replacing injection drug use as the main method of HIV transmission in China • Female sex workers (FSWs) are at high risk for HIV infection • FSWs pose a risk of bridging the HIV epidemic to the general population through sex with clients and regular sexual partners
Yunnan Province Kaiyuan County Population 292,000 Honghe Prefecture
Methods • Participant Eligibility • 16 years of age or older • Self-reported commercial sex work within the previous 3 months • Recruitment • Local CDC outreach workers recruited potential study subjects at sex work venues directly and through venue-owner outreach • Ethics Approval • This study was approved by the National Center for AIDS/STDs Control and Prevention, China CDC IRB
Methods – Data Collection • Cross-sectional surveys were conducted biannually from March 2006 to November 2009 • Questionnaires were administrated through face-to-face interviews by trained Kaiyuan CDC staff • Participants were asked about their socio-demographic characteristics, basic medical history, sexual behavior, and illegal drug use history • Blood and vaginal swab samples were collected by trained physicians and tested for HIV and sexually transmitted infections (STIs)
Methods – Statistical Analyses • Those HIV-positive at baseline were excluded from analysis • Chi-squared tests were used to compare demographic and behavioral characteristics of participants who returned for follow-up and subjects who did not return • HIV incidence density was calculated for subjects who were HIV-negative at baseline and completed at least two surveys
Methods – Statistical Analyses • HIV infection was estimated to occur midway between the last HIV negative test result and the first HIV positive test result • HIV incidence density was calculated by dividing the number of events of HIV seroconversion by the number of person years of follow up • Follow-up time for each FSW was calculated as the time between her first negative HIV test and the most recent negative HIV test or incident HIV infection if she seroconverted
Methods – Statistical Analyses • Poisson 95% confidence intervals (CI) were calculated for overall incidence density • Univariate and multivariate Cox proportional hazards regression models with time dependent variables were used to determine the factors associated with HIV seroconversion • Factors significant in univariate analysis were included in a stepwise Cox proportional hazards multiple regression model with entry criteria of p<0.2 and exit criteria of p>0.05
Results • From 2006 to 2009, a total of 2282 FSWs participated in at least one survey • 2051 (89.9%) participants were HIV negative at baseline • 851 (41.5%) initially HIV-negative FSWs returned for at least one follow-up visit
Results • Over 3.5 years, 851 FSWs were followed an average of 1.57 (±1.14) years • 19 incident cases of HIV infection were diagnosed, with an incidence of 1.42 per 100 person years (PY) (95% CI, 0.86-2.21)
Results • Of 19 participants who seroconverted: • 5 were IDUs • 5 were non-injection drug users • 9 were non-drug users • It is estimated that at least 73.7% (14 non-drug users and non-injection drug users of 19 new HIV cases) of subjects were infected through sexual transmission.
Independent Risk Factors for HIV Infection • Non-injection drug use (adjusted hazard ratio [AHR] 5.8, (95% CI 2.0-16.8)) • Inconsistent condom use with clients in the previous week (AHR 3.0, (95% CI 1.0-8.9)) • At least 7 clients in the previous week (AHR 5.1, 95% CI 1.9-13.4)
Limitations • Information was gathered through self-report and may be subject to social desirability and/or recall bias • Nearly 60% of eligible FSWs were lost to follow-up • Participants in the cohort had a higher prevalence of illicit drug use, HSV-2 infection, and current syphilis infection • Participants had less clients in the previous week • It is difficult to determine whether HIV incidence was overestimated or underestimated based on these differences • The results of this study may not be generalizable to other areas of China
Conclusion • Sexual transmission seems to play a strong role in the growth of the HIV epidemic among Kaiyuan FSWs • Non-injection drug use was the most salient predictor for incident HIV infection • these results underscore the need for HIV interventions among drug users that incorporate sexual risk reduction
Funding Sources • The Comprehensive International Program of Research on AIDS (CIPRA), the National Institute of Allergy and Infectious Diseases, US National Institutes of Health (U19 AI51915-05) • Science and Technology major projects of China (2008ZX10001-003) • The National Institute of Allergy and Infectious Diseases, US National Institutes of Health (RFA-A1-06-041) • Fogarty International Center, National Institutes of Health Office of the Director, Office of AIDS Research, National Cancer Institute, National Eye Institute, National Heart, Blood, and Lung Institute, National Institute of Dental & Craniofacial Research, National Institute On Drug Abuse, National Institute of Mental Health, National Institute of Allergy and Infectious Diseases Health, Office of Women’s Health Research, National Institute of Child Health and Human Development, through the International Clinical Research Fellows Program at Vanderbilt (R24 TW007988)
Conflicts of Interest • The authors declare that there are no conflicts of interest
Acknowledgements • Haibo Wang, PhD, MPH1,3 • Katherine Brown, BS1 • Xia Jin, MS1 • JunjieXu, PhD4 • Guowei Ding, MS1 • ChunpengZang, MS1 • Junjie Wang, MS1 • Ning Wang, MD, PhD1 1 National Center for AIDS/STD Prevention and Control, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206, China 2 Tulane University Health Sciences Center, School of Public Health and Tropical Medicine, New Orleans, LA, USA 3 Chinese Center for Disease Control and Prevention, 27 Nanwei Rd, Beijing 100050, China 4Key Laboratory of Immunology of AIDS, Ministry of Health, First Affiliated Hospital, China Medical University, 155 Nanjingbei Rd, Shenyang 110001, China
Acknowledgements • Westat, Inc. (Rockville, Maryland, USA) • Kaiyuan and Yunnan CDCs
Thank You! 谢谢!