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



Recruitment


16 years of age or older
Self-reported commercial sex work within the
previous 3 months
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 sociodemographic 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
Baseline Participant Characteristics
Variable
N (%)
Han ethnicity
594 (69.8%)
Registered residence
461 (54.2%)
Kaiyuan 212 (24.9%)
Other cities in Yunnan Province 461 (54.2%)
Outside Yunnan Province 178 (20.9%)
Less than 6 years of education
298 (35.0%)
Works out of low-risk entertainment venues
539 (63.3%)
Always used condoms with clients in the past week
732 (86.0%)
History of injection drug use
81 (9.5%)
History of non-injection drug use
56 (6.6%)
N. gonorrheae
58 (6.8%)
C. trachomatis
184 (21.6%)
Trichomonas vaginalis
62 (7.3%)
Herpes simplex virus type 2
532 (62.5%)
Syphilis
67 (7.9%)
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:


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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
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
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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


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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
1
Katherine Brown, BS
1
Xia Jin, MS
4
Junjie Xu, PhD

1 National
Guowei Ding, MS1
1
Chunpeng Zang, MS
1
Junjie Wang, MS
1
Ning Wang, MD, PhD

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