SEX WORK AND HIV INCIDENCE IN
SOUTH AFRICA: WHAT DO WE
KNOW?

          Mr Tshepo Molapo
        Sex workers symposium
         22-24 September 2012
       Birchwood, Johannesburg
WHAT WILL BE PRESENTED?
   Introduction

   Background

   New HIV infections and sex work in South Africa

   How does incidence TRANSLATE when it come
    to HIV prevalence among sex workers in South
    Africa

   Implications for programmes
INTRODUCTION
 Globally, sex workers (SW), have been shown to be at
  disproportionate risk for HIV infection.
 Sex workers (Female) are a population who are at
  heightened risk of HIV infection secondary to biological,
  behavioural, and structural risk factors.
 Multiple and concurrent partners, casual encounters

 Because they are often marginalized by society and
  greatly affected by discrimination and stigma, these
  groups have become some of the most at-risk
  populations for HIV infection.
 SWs form part of “key populations”.
BACKGROUND
   High levels of prejudice and moral loading has been
    shown to create barriers to accessing prevention,
    treatment, care and support – increasing vulnerability
    to HIV.

   Insufficient consensus around HIV incidence and
    prevalence in this key population have led to
    uncertainty around the perception of risk of HIV
    acquisition
WHAT ARE THE ESTIMATES WHEN IT COMES
TO HIV INCIDENCE AND SEX WORK IN SOUTH
AFRICA?
    As part of the Know you epidemic/Know your
     response (KYE/KYR), SACEMA was tasked with
     running a model for South Africa in 2009.
THE MODES OF TRANSMISSION
(MOT) MODEL
The MoT model is static, and provides a short-term projection
  based on current HIV prevalence levels and behaviours. The
  adult population is segmented into six closed
  subpopulations, namely
 Injecting drug users (IDU’s) and their partners
 Sex workers (SW’s), the clients of SW’s and the
  clients’ partners
 Men who have sex with men (MSM) and their females
  partners
 Individuals engaging in casual heterosexual sex (CHS) and
  their partners
 Individuals engaging in low-risk heterosexual sex
 Individuals at no risk
MODEL INPUTS (SOURCES)
Estimates from national South African surveys were used where possible. The three main
    surveys that provided data for model inputs are:
   The National HIV and Syphilis Prevalence Survey: by the National Department of
    Health and involves the surveillance of women attending antenatal clinics.
   The Demographic and Health Survey (DHS): conducted in 1998 and 2003.
   The National HIV Prevalence, Incidence, Behaviour and Communication Survey:
    by the Human Sciences Research Council (HSRC); the Medical Research Council (MRC);
    the Centre for AIDS Development, Research and Evaluation (CADRE) and the South
    African National Institute for Communicable Diseases (NICD).
   Estimates from smaller studies in South Africa and studies in other regions, as
    found in published literature, were also used as model inputs. Such estimates were
    particularly useful for describing the characteristics of the smaller, high-risk groups such
    as SW’s or MSM.
MODEL OUTPUT: NEW HIV
    INFECTIONS ESTIMATED DATA

 19.8% of all new HIV infections in South Africa are
  related sex work (SACEMA)
 Percent of new HIV infections, group only (5.5 %)

 Percent of new infections, group and their
  partners/clients (19.8 %)
HOW DOES THIS TRANSLATE IN TERMS
    OF DISEASE BURDEN – HIV
    PREVALENCE AS A START
 Meta-analyses of aggregate country data comparing
  HIV prevalence among female sex workers and women
  of reproductive age in low-income and middle-income
  countries, 2007–11. (Lancet Infect Dis 2012;12: 538–
  49)
 Method: Systematic review of 434 articles and
  surveillance reports representing 99 878 female sex
  workers in 50 middle income countries.
STUDY FINDINGS


HIV        95% CI      HIV          % HIV
prevalence             prevalence   infections
among                  among        among
female sex             female       female
workers                population   sex
                                    workers
59·6%      56.2–63.1   25.32%       5.7%
IMPLICATIONS FOR PROGRAMMES
   Results indicate the urgency of establishing a national
    programme for sex workers that includes HIV prevention
    interventions

   Further studies of South Africa’s high risk populations,
    including sex workers and their clients, to obtain estimates
    of the sizes of these groups and HIV incidence and
    prevalence among them.

   “In South Africa, the HIV epidemic is truly generalized
    with HIV transmitted mainly heterosexually, and high
    levels of infection by no means restricted to the high-risk
    groups”.
ACKNOWLEDGEMENTS
   The SACEMA team
•   Reshma Kassanjee and Alex Welte
•   Tyrone Lapidos

•   Eleanor Gouws (UNAIDS)

   Dr John Mkandawire (WRHI)
Ke a leboga

Sex work and HIV incidence in South Africa: what do we know?

  • 1.
    SEX WORK ANDHIV INCIDENCE IN SOUTH AFRICA: WHAT DO WE KNOW? Mr Tshepo Molapo Sex workers symposium 22-24 September 2012 Birchwood, Johannesburg
  • 2.
    WHAT WILL BEPRESENTED?  Introduction  Background  New HIV infections and sex work in South Africa  How does incidence TRANSLATE when it come to HIV prevalence among sex workers in South Africa  Implications for programmes
  • 3.
    INTRODUCTION  Globally, sexworkers (SW), have been shown to be at disproportionate risk for HIV infection.  Sex workers (Female) are a population who are at heightened risk of HIV infection secondary to biological, behavioural, and structural risk factors.  Multiple and concurrent partners, casual encounters  Because they are often marginalized by society and greatly affected by discrimination and stigma, these groups have become some of the most at-risk populations for HIV infection.  SWs form part of “key populations”.
  • 4.
    BACKGROUND  High levels of prejudice and moral loading has been shown to create barriers to accessing prevention, treatment, care and support – increasing vulnerability to HIV.  Insufficient consensus around HIV incidence and prevalence in this key population have led to uncertainty around the perception of risk of HIV acquisition
  • 5.
    WHAT ARE THEESTIMATES WHEN IT COMES TO HIV INCIDENCE AND SEX WORK IN SOUTH AFRICA?  As part of the Know you epidemic/Know your response (KYE/KYR), SACEMA was tasked with running a model for South Africa in 2009.
  • 6.
    THE MODES OFTRANSMISSION (MOT) MODEL The MoT model is static, and provides a short-term projection based on current HIV prevalence levels and behaviours. The adult population is segmented into six closed subpopulations, namely  Injecting drug users (IDU’s) and their partners  Sex workers (SW’s), the clients of SW’s and the clients’ partners  Men who have sex with men (MSM) and their females partners  Individuals engaging in casual heterosexual sex (CHS) and their partners  Individuals engaging in low-risk heterosexual sex  Individuals at no risk
  • 7.
    MODEL INPUTS (SOURCES) Estimatesfrom national South African surveys were used where possible. The three main surveys that provided data for model inputs are:  The National HIV and Syphilis Prevalence Survey: by the National Department of Health and involves the surveillance of women attending antenatal clinics.  The Demographic and Health Survey (DHS): conducted in 1998 and 2003.  The National HIV Prevalence, Incidence, Behaviour and Communication Survey: by the Human Sciences Research Council (HSRC); the Medical Research Council (MRC); the Centre for AIDS Development, Research and Evaluation (CADRE) and the South African National Institute for Communicable Diseases (NICD).  Estimates from smaller studies in South Africa and studies in other regions, as found in published literature, were also used as model inputs. Such estimates were particularly useful for describing the characteristics of the smaller, high-risk groups such as SW’s or MSM.
  • 8.
    MODEL OUTPUT: NEWHIV INFECTIONS ESTIMATED DATA  19.8% of all new HIV infections in South Africa are related sex work (SACEMA)  Percent of new HIV infections, group only (5.5 %)  Percent of new infections, group and their partners/clients (19.8 %)
  • 9.
    HOW DOES THISTRANSLATE IN TERMS OF DISEASE BURDEN – HIV PREVALENCE AS A START  Meta-analyses of aggregate country data comparing HIV prevalence among female sex workers and women of reproductive age in low-income and middle-income countries, 2007–11. (Lancet Infect Dis 2012;12: 538– 49)  Method: Systematic review of 434 articles and surveillance reports representing 99 878 female sex workers in 50 middle income countries.
  • 10.
    STUDY FINDINGS HIV 95% CI HIV % HIV prevalence prevalence infections among among among female sex female female workers population sex workers 59·6% 56.2–63.1 25.32% 5.7%
  • 11.
    IMPLICATIONS FOR PROGRAMMES  Results indicate the urgency of establishing a national programme for sex workers that includes HIV prevention interventions  Further studies of South Africa’s high risk populations, including sex workers and their clients, to obtain estimates of the sizes of these groups and HIV incidence and prevalence among them.  “In South Africa, the HIV epidemic is truly generalized with HIV transmitted mainly heterosexually, and high levels of infection by no means restricted to the high-risk groups”.
  • 12.
    ACKNOWLEDGEMENTS  The SACEMA team • Reshma Kassanjee and Alex Welte • Tyrone Lapidos • Eleanor Gouws (UNAIDS)  Dr John Mkandawire (WRHI)
  • 13.