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Social and Structural Factors associated with HIV Risk among Female Sex Workers (FSW ) and Men who have Sex with Men (MSM) in Swaziland, 2011. Stefan Baral, MD MPH, JHSPH. Overview. Background HIV Epidemiology among MSM and FSW Objectives Methods Results Quantitative Qualitative - PowerPoint PPT Presentation
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SOCIAL AND STRUCTURAL FACTORS ASSOCIATED WITH HIV RISK AMONG FEMALE SEX WORKERS (FSW) AND MEN WHO HAVE SEX WITH MEN (MSM) IN SWAZILAND, 2011
Stefan Baral, MD MPH, JHSPH
Overview Background
HIV Epidemiology among MSM and FSW Objectives Methods Results
Quantitative Qualitative
Conclusions
HIV Epidemiology UNAIDS Classifies Epidemics as:
Low level Less than 5% Prevalence in any high risk group
Concentrated Greater than 5% in any high risk group, but less
than 1% antenatal clinics Generalized
Greater than 1% in antenatal clinics
Global HIV Prevalence
UNAIDS. Global Update on the HIV Pandemic. 2010
IDU, SW
IDU, MSM, SW,
HCHC
Legend• IDU Injection Drug Use• SW Sex Work• HC High Risk
Heterosexual Transmission
Legend
2002200320042005200620072008
Senegal [77]
21.5%(463)
21.8%(501)
Ghana [11]
25.0%(N/A)
Nigeria [79]
13.4%(1,125) Sudan [86]
9.3%(713)
7.3%(406)
Kenya [78]
24.6%(285)
Tanzania [80]
12.3%(509)
Malawi [81,82]
21.4%(201)
Soweto [83]
28.9%(249)
Botswana [82]
19.7%(117)
30.9%(68)
Capetown (Township) [84]Capetown
[85]
10.6%(538)
Namibia [82]
12.4%(218)
Egypt [90]
6.2%(267)
HIV Prevalence among MSM in Africa
Source: van Griensven, Baral, et al. The Global Epidemic of HIV Infection among Men who have Sex with Men. Curr Opinion on HIV/AIDS, 2009
Systematic Review of HIV among FSW
Data Quality Disease burden among MARPS in Africa
Data is predominantly Prevalence Data from Convenience Samples Tells us where epidemic was and not where it is going May not be generalizable to general population of MARPS
Samples are among young people--likely very conservative estimates of disease burden
Compared against age standardized data (15-49) in general population
HIV Incidence has been characterized in cohort studies in Kenya ~ 10% Incidence among MSM and FSW
Prevalence of Same-Sex Practices/Sex work are unknown in most of Africa Potential Risk Misclassification?
Ecological Model for HIV Risk in MSM
Stage of Epidemic
Individual
CommunityPublic Policy
Network
Level of Risks
Source: Baral and Beyrer, 2006
Quantitative Study Goal To collaborate with MOH to develop a
comprehensive set of data that can be used by municipal and national government in Swaziland to design evidence-based HIV prevention programs for Most at Risk Populations.
Specific Aims Calculate a probability estimate of HIV and
Syphilis prevalence among sex workers and men who have sex with men in Swaziland
Describe behavioral factors associated with HIV/STI infection, including individual sexual practices, the composition of sexual networks, concurrent partnerships, substance use, and access to clinical health care and prevention services
Examine the role of social and structural factors on HIV-related behaviors and risk for HIV infection among sex workers and MSM including social inclusion, stigma and discrimination
Methods Target Populations
328 Men who have had anal sex with another man in the last 12 months
325 women who report sex work as primary form of income
Accrual Methodology Respondent-driven sampling
Behavioral Survey Validated and Piloted in each population
Biological Testing HIV and Syphilis Swaziland National Guidelines with Pre and Post-test
counseling
Respondent-Driven Sampling Peer-referral system using coupon
management system that allows for adjustment for network sizes and homophily (the concept that people recruit people that are similar to themselves)
Allows for estimation of unbiased estimates from a non-probability sample
FSW DemographicsNo. %
Age<21 64 19.721-24 82 25.225-29 91 2830+ 88 27.1Total 325 100
EducationPrimary or less 106 32.6Some Secondary 175 53.8Completed Secondary or more 44 13.5Total 325 100
Marital statusMarried 3 0.9Cohabiting 10 3.1Divorced/Sep 23 7.2Single/Never married 285 88.8Total 321 100
Number of childrenNone 80 24.61 100 30.82+ 145 44.6Total 325 100
Has other income sourceNo 216 66.7Yes 108 33.3Total 324 100
Numbers of PartnersNumber of new clients (past 30 days)*0-1 44 13.52-4 142 43.75-10 108 33.2>10 31 9.5Total 325 100
Number of regular clients (past 30 days)*0-1 27 8.32-4 93 28.65-10 131 40.3>10 74 22.8Total 325 100
Number of non-commercial partners (past 30 days)None 37 11.41 172 52.92+ 116 35.7Total 325 100
Disclosed occupation to Family member 98 30.2Health care worker 84 25.9
Condom UseAlways used condoms with new clients in past monthNo 77 25.8Yes 222 74.2Total 299 100
Always used condoms with regular clients in past monthNo 160 51.8Yes 149 48.2Total 309 100
Always used condoms with non-commercial partners in past monthNo 189 66.5Yes 95 33.5Total 284 100
Always used condoms with all reported partners in past monthNo 247 76.5Yes 76 23.5Total 323 100
Condom break/slip with any partner in past monthNo 143 44.7Yes 177 55.3Total 320 100
Structural Risks for HIVCharacteristic No.
Percentage
Have ever been raped 123 39.2Instances of rape since age 18 0 6 4.6 1-2 77 58.3 3-4 17 12.9 5-6 9 6.8 6 or more 23 17.4Responsible for rape
Uniformed Officer (police, military, security) 4 3.9 Family Member 21 20.6 Regular partner (not client) 14 13.7 One-time client 33 32.4 Regular Client 7 6.9As a result of selling sex:
Felt afraid to seek healthcare 143 44.0 Experienced legal discrimination 152 46.8 Been refused police protection 160 49.4 Been blackmailed 113 34.8 Verbal and physical harassment 198 60.9 Have been tortured 173 53.2 Have been beaten up 125 38.7 Have been beaten up by Uniformed Officers (police, miltary, security) 45 20.8 Family Member 21 9.7 Regular Partner 16 7.4 One time client 11 5.1 Regular client, partner 9 4.2 Manager/pimp 6 2.8
HIV Prevalence among FSW compared to Reproductive Age Women, Swaziland 2011
Source: Central Statistical Office & Macro International, 2008, p. 222
16-20 21-24 25-29 30-400
10
20
30
40
50
60
70
80
90
FSW HIV PrevalenceFemale HIV Prevalence
Age Groups
HIV
Pre
vale
nce
(%)
Significant Univariate Associations with HIV among FSW Higher Age Lower Education Marriage Ever Pregnant
MSM Demographics Characteristic Crude prevalence (N)
Age 15-19 20-24 25-29 30-34 35 -39 40-44
22.0 (71)48.0 (155)20.4 (66)5.6 (18)2.5 (8)1.5 (5)
Age Below 25 25 or older
70.0 (226)30.0 (97)
Marital status Single Married
96.9 (310)3.1 (10)
Education Some secondary school Completed secondary school Vocational training College/university
32.1 (101)43.5 (137)4.1 (13)20.3 (64)
Sexual orientation Gay/homosexual Bisexual Heterosexual
63.3 (205)35.2 (114)1.5 (5)
Sexual Practices Characteristic Crude prevalence
(N)Always Wear Condoms with Regular Partners YesNo
50.6 (157)49.4 (266)
Had both male and female sexual partners in the last 12 monthsYesNo
37.4 (122)62.6 (204)
Had a concurrent regular partnership with two or more regular partners in the last 12 months No Yes male and female Yes, two or more male partners Yes, two or more female partners
45.5 (148)20.9 (68)31.1 (101)2.1 (7)
Exchange sex in the last 12 months 26.1 (85)Number of male partners in the last 12 months 1 2-5 6 or more
32.9 (107)58.5 (190)8.6 (28)
Condom Use Characteristic Crude prevalence (N)
STI testing in the last 12 months 13.0 (41)HIV testing in the last 12 months No Yes, once Yes, more than once
45.7 (149)30.4 (99)23.9 (78)
Access to condoms No access Difficult or little access Some access Very easy access
0.9 (3)17.9 (58)11.4 (37)69.8 (226)
Access to lube No access Difficult or little access Some access Very easy access
26.7 (83)30.2 (94)15.4 (48)27.6 (86)
Received HIV prevention for MSM last 12 months
27.1 (88)
Structural Risks for HIV Characteristic Crude
prevalence (N)
Afraid to seek health care due to sexuality 55.3 (177)
Felt rejected by friends due to sexuality 54.4 (176)
Faced legal discrimination due to sexuality 31.2 (100)
Ever been raped 6.0 (19)
Ever been to prison 12.9 (42)
Ever beaten up due to sexuality 9.0 (29)
HIV Prevalence among MSM compared to Reproductive Age Men, Swaziland 2011
16-20 21-24 25-29 30-400
10
20
30
40
50
60
MSM HIV PrevalenceMale HIV Prevalence
Age Groups
HIV
Pre
vale
nce
(%)
Source: Central Statistical Office & Macro International, 2008, p. 222
Significant Univariate Associations with HIV among MSM Age Syphilis Been in Prison Excessive Alcohol Use
Positive Prevention 30 years into the HIV epidemic, new infections still
outpace people initiating treatment Historically, most HIV prevention interventions
targeted uninfected individuals Globally, little access to HIV testing Fear of blaming the victim and adding to stigma
Recently, dramatic scale-up of HIV testing and treatment services worldwide More PLHIV now know their status With treatment, PLHIV living longer, healthier lives
Positive prevention helps people living with HIV lead a complete and healthy life and reduce the risk of transmission of the virus to others.
WHO guidelines In 2007, WHO issued
guidelines for positive prevention interventions in resource-limited settings
However, little evidence from studies focused on PLHIV, and little focus on MARPS
Study goal To examine the prevention needs of Most
at Risk Populations (MARPS) including Sex Workers (SW) and Men who have Sex with Men (MSM) in Swaziland to better tailor PHDP programs for these populations.
Study Methods Qualitative study design One-on-one, in-depth interviews with key
stakeholders (n=16) and HIV-positive SW (n=21) and MSM (n=20) Most MSM and SW interviewed twice each
for more depth Focus groups with SW (n=3) and MSM
(n=3)
Data analysis Weekly interviewer debriefing meetings All interviews audio recorded, transcribed, and
translated into English Full day data analysis workshop held Oct. 13, 2011
at the Mountain Inn Attended by representatives from MSM and SW groups,
MOH and NERCHA staff, interviewers and members of the research team, clinicians, and others
Read transcripts, developed list of key themes, and discussed implications
Further coding of transcripts and analysis by 4 study team members
Stigma, discrimination, and violence
Both groups experienced dual stigma related to both HIV+ and SW/MSM identities Led to lack of disclosure of both identities
SW reported violence from clients and police Some clients became violence when asked to use condoms Others would refuse to pay after sex and become violent Police round-ups, demand for sex, violence
MSM reported discrimination and violence from a wide range of individuals Partners, families, general public, police raids
Both groups felt they had no recourse to bring such incidents to the authorities
Risk cycle of hunger, sex work, and HIV for SW
SW described a risk cycle of hunger & poverty driving sex work driving HIV infection.
HIV in turn drives an increased need for ‘healthy foods’
Sex work leads to alienation from social networks which offer material and emotional support against hunger & poverty.
Hunger &
poverty
Sex work
HIV infectio
n
Increased need
for healthy foods
Reduced social support
Challenges keeping MSM/SW PLHIV physically healthy
Perceived stigma from health care settings leading to lack of care-seeking
Perceived stigma from families/partners leading to lack of disclosure of HIV status Challenges with ART adherence, hiding
medications, lack of social support for treatment Poverty and hunger
For SW, risk cycle of hunger, sex work, and HIV MSM also reported transactional sex, challenges
adhering to ART, and challenges getting to clinic due to poverty and hunger
Challenges keeping MSM/SW PLHIV mentally healthy
Primary challenge of living with dual stigma
Depression and self-stigma or shame Some MSM said feelings of self-stigma
led MSM to drink alcohol to “forget”, which often led to sexual risk behavior
Challenges preventing further HIV transmission
Questions around HIV prevention during clinical services often assume heterosexuality/one partner Due to fear of stigma, SW/MSM often just answer the
question asked (e.g., ‘I don’t have a steady partner’), rather than discuss their true risk behaviors – missed opportunity for prevention
SW offered more money for sex without condoms Clandestine nature of MSM relationships may lead to
more and more casual partnerships MSM described many of their partners as bisexual or having
female partners/wives (possibly to hide MSM behavior or to fulfill cultural expectations)
MSM relationships are kept secret and therefore families do not play a role in relationship counseling and peacekeeping
Successes preventing further HIV transmission Sex workers appreciated the tailored HIV
educational sessions provided for them MSM suggested ‘training of trainers’ model
Train trusted MSM community members who could then share messages with others
Both SW and MSM suggested continued/further distribution of condoms and particularly lubricant to prevent condom breakage
Consider MSM/SW “expert clients” for those living with HIV
Challenges increasing agency of MSM/SW PLHIV
Dual stigma and hidden identities MSM/SW have difficulty trusting
outsiders until they get to know particular individuals over time
MSM/SW are often unwilling to disclose their status publically to represent these groups in HIV-related activities
Successes increasing agency of MSM/SW PLHIV Ongoing activities by MOH, PSI, SNAP,
SWAPOL, and others – including this research – suggests if approached in the right way, MSM and SW are interested in participating in HIV prevention, care and treatment decisions for their communities
Service delivery models Some respondents suggested developing
special clinics or services for HIV+ MSM or SW Others said targeted services would reinforce
stigma Several participants said health care workers
should be trained on issues related to MARPS “I would train health care workers. Even their
procedures manuals should have information on how to handle MARPS … Also let’s make educational materials that also speak of MARPS.” – KI
Successful existing models of SW-friendly services
Respondents emphasized the success of specific SW-friendly services (e.g. FLAS, others)
Several said the “support group” code word model used for SW-friendly services in Piggs Peak, Lobamba, and a few other clinics worked well. “For instance, Piggs Peak and Lobamba, they come and say,
‘I’ve come to see so and so … and the health care worker will know it’s from the support group so it means she is a sex worker. Same with Lobamba, they meet and she can say, ‘I’m from the support group,’ oh, then she will know she is a sex worker without announcing.” – KI
“We could use some of those centres as learning sites, you know. We could share the lessons learnt from those people.” – KI
“They are human beings, they are Swazi.”
Key informants consistently said that regardless of personal belief, they had an ethical responsibility to provide services to everyone, equally “As a health sector, my belief is non-discriminatory
services to all the members of the population, and issues of legality and everything rest with the Ministry of Justice.” – KI
“Even though I don’t approve of what they are doing … as a public health officer, I have to make sure that they have access to health services. I don’t have to judge them. I don’t have to give my views on what they are doing. But my duty is to make sure that they have access to services… whatever their sexual orientation is, they are human beings, they are Swazi.” – KI
Conclusions FSW and MSM represent distinct high risk populations in
Swaziland These populations are underserved with only sporadic targeted
program Even in the context of countries with hyperendemic HIV prevalence
rates, there is still concentration of HIV risk and prevalence Moving Forward
Combination HIV Prevention Programs Biomedical
Increasing HTC and Active Linkage to ART for eligible Evaluate future strategies as they are developed
Chemoprophylaxis Behavioral
Increasing Condom and Condom Compatible Lubricant Use Structural
Community Systems Strengthening Health Sector Interventions Gender normalization strategies Safe work spaces
Next steps for Studies Finalize findings and recommendations with MOH Write final report Swaziland dissemination to MOH, MARPS
technical working group, stakeholders, media Global dissemination through peer-reviewed
articles and presentations for the International AIDS Conference, July 2012
Compare with same qualitative research in the Dominican Republic (concentrated HIV epidemic)