1. Responding to the HIV epidemic in Africa: how important is HIV prevention programming among most-at-risk populations? Africa-India HIV Learning Exchange, Washington D.C., July 2012 Stephen Moses MD, MPH University of Manitoba and Karnataka Health Promotion Trust (KHPT) Stephen Moses MD, MPH University of Manitoba and Karnataka Health Promotion Trust (KHPT)

2. Why is This Presentation Necessary? Plummer et al: The importance of core groups in the epidemiology and control of HIV-1 infection. AIDS 1991. Côté et al: Transactional sex is the driving force in the dynamics of HIV in Accra, Ghana. AIDS 2004. Alary et al: The central role of clients of female sex workers in the dynamics of heterosexual transmission in sub-Saharan Africa. AIDS 2004.

3. Meta-analysis of HIV prevalence among FSWs and All Adult women* CountryHIV Prevalence (FSWs) HIV Prevalence (All adult women) Odds Ratio India 13.7%0.29%54.3 Kenya 45.1%7.7%9.8 Nigeria 33.7%4.5%10.7 Malawi 70.7%13.3%15.7 South Africa 59.6%25.3%2.5 Uganda 37.2%8.5%6.4 Zimbabwe 61.2%21.4%5.8 Lower prevalence countries (< 1%) 5.1%0.17%24.5 Higher prevalence countries (> 1%) 30.7%5.5%11.6 *From Baral et al., Lancet Infect Dis, 2012

4. Percentage of Women Reporting Commercial Sex in Past 12 Months* From Caraël et al., AIDS 1995

5. Modes of Transmission (MOT) Analyses: Distribution of HIV Incident Infections by Sub-group* Uganda, 2008 Kenya, 2008 Nigeria, 2009 Low-risk heterosexual42.9%12.3%42.3% IDU0.28%3.8%9.0% Female sex workers0.91%6.6%3.4% Clients of FSWs7.8%7.5%4.8% Partners of clients1.8%1.6%3.4% MSM0.6%15.2%10.3% Multiple partners (MP)23.7%20.3%9.1% Partners of MP21.8%28.3%14.8% *From Mishra et al., PLoS One, 2012.

6. Key Issues Confounding Understanding of HIV Transmission Dynamics Under-estimation of the size estimates of the populations of female sex workers and especially of clients (also MSM and IDUs). Calculations of the distribution of prevalent and incident HIV infections in the short-term can be very misleading in terms of HIV transmission dynamics and upstream causes of infection.

7. National Urban FSW Estimates, Kenya 2011 Total: 138,420 (5% of adult urban females) DHS 2009: Men reporting paying for sex: 2.1% (N=218,000)

8. Squaring the FSW-Client Circle in Kenya Number of urban FSWs: ~138,000 Number of males who reported paying for sex from FSWs in past year (from 2009 DHS): ~218,000 Average of only 1.5 clients per FSW per year? Would mean that each client, on average, has sex with an FSW 316 times per year (6 days per week). Clearly, the client estimation is significantly low, probably by 7-10 fold.

9. Percent of Male Population Visiting Female Sex Workers From DHS DataFrom Other Survey Data Benin0.7%12-22% Burkina Faso0.2%14.5-28.8% Côte d’Ivoire3.1%-- Ghana1.6%9.2-52% Nigeria2.9%--

10. Polling Booth Surveys Group anonymous interviews 10-20 individuals Respondents isolated from each other by private booths Simple set of yes/no questions read aloud Voting cards with question number put in colour- coded boxes for ‘yes’ and ‘no’ answers Responses collected together from each type of box Group response rates calculated – aggregate data only

11. Conduct of PBS: Urban, Married Men

12. Comparison of FTFI and PBS, Cotonou, Benin FTFIPBS Married men, paid for sex with FSW in past year 12.1%23.6% Unmarried men, paid for sex with FSW in past year 12.6%16.8% Married women, were paid for sex with a man in past year 0.8%12.5% Unmarried women, were paid for sex with a man in past year 2.8%13.5%

13. Transmission Dynamics Issues In countries with largely concentrated epidemics, and to an extent in generalized epidemics, “low- risk” cases of HIV infection are mostly due to past experience of risky behaviour or having a high-risk partner. Modelling incident HIV cases over only one year will thus underestimate the contribution of high- risk individuals and their partners to the total number of HIV cases.* *Mishra et al., PLoS One, 2012

14. Estimating the Population Attributable Fraction (PAF) for HIV Infection in Adult Men of Being a Client of an FSW (Cotonou) No. of client contacts per FSW per year782 No. of FSWs in Cotonou1,915 Average number of visits to FSW per client per year32 No. of clients of FSWs in Cotonou46,798 No. of adult males in Cotonou155,307 % of adult male population who are clients of FSWs30.1% HIV prevalence in clients of FSWs9.1% HIV prevalence in non-FSW clients0.8% RR for sex with an FSW and HIV infection in men11.4% PAF for HIV in adult men of being an FSW client76%

15. Relative Risk, Etiological Fraction and Population Attributable Fraction of HIV among Men, Related to Sexual Contact with Female Sex Workers RREFPAF Accra, Ghana11.892%84% Cotonou, Benin11.491%76% Rufisque and Tambacounda, Sénégal 26.596%81%

16. Benin: Commercial Sex Work Dominates HIV Transmission, but not HIV/AIDS Funding 76% of HIV infections among men in Benin have been shown to be attributable to sex work

17. Budget Breakdown of the Ghana National Strategic Framework, 2006-10 Budget (US$)Proportion (%) Prevention175,155,79032.3 Priority populations77,548,89114.3 Youth12,505,2792.3 FSWs and clients4,399,8400.8 Workplace53,619,4099.9 Others7,024,3631.3 Service delivery (VCT, PMTCT, etc.)83,786,56615.7 Prevention in health care13,850,3322.6 Care and treatment164,091,288730.3 Mitigation119,749,24622.1 Policy, advocacy, admin. & research82,619,33815.3 TOTAL541,615,661100.0

18. Renewed Work on Sources of New HIV Infections* *From John Stover, ICASA 2008

19. Renewed Work on Sources of New HIV Infections, Cross River State, Nigeria* *From H. Prudden, A. Foss, C. Watts, et al., 2012 MARPs: 26%MARPs: 55%

20. Conclusions In most African countries, high proportions of the adult female population are sex workers, and high proportions of adult men purchase sex. HIV prevalence is much higher in these populations than in the general population. FSW-client and client-other women contacts, including transactional sex, account for the majority of HIV transmission in most African settings, and more than would be suggested by current “Know your epidemic” methods. HIV prevention programming among most-at-risk populations is critical in responding to the HIV epidemic in African countries with both concentrated and generalized epidemics.

21. Acknowledgements Michel Alary, Université Laval Jamie Blanchard, University of Manitoba B.M. Ramesh & Shajy Isac, KHPT & University of Manitoba Willis Odek, University of Manitoba Holly Prudden, Anna Foss & Charlotte Watts, LSHTM David Wilson, World Bank