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P716 HIV prevalence in at-risk adolescent girls and young women in kenya across locations associated with sex work
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  1. Marissa Becker1,
  2. Helgar Musyoki2,
  3. Sharmistha Mishra3,
  4. Parinita Bhattacharjee4,
  5. Eve Cheuk1,
  6. Stella Leung1,
  7. Robert Lorway1,
  8. Shajy Isac5,
  9. Peter Gichangi6,
  10. Francois Cholette7,
  11. Paul Sandstrom8,
  12. James Blanchard1,
  13. Michael Pickles1
  1. 1University of Manitoba, Centre for Global Public Health, Department of Community Health Sciences, Winnipeg, Canada
  2. 2National AIDS and STI Control programme (NASCOP), Key Populations, Nairobi, Kenya
  3. 3St. Michael’s Hospital, Li Ka Shing Knowledge Institute, Toronto, Canada
  4. 4University of Manitoba, Centre for Global Public Health, Nairobi, Kenya
  5. 5India Health Action Trust, Delhi, India
  6. 6International Centre for Reproductive Health-Kenya, Mombasa, Kenya
  7. 7National HIV and Retrovirology Laboratories, Winnipeg, Canada
  8. 8National HIV and Retrovirology Laboratory, JC Wilt Infectious Diseases Research Centre, Winnipeg, Canada

Abstract

Background HIV prevalence is influenced by biological, behavioural and structural factors. We sought to understand HIV prevalence among at-risk adolescent girls and young women (AGYW) in Kenya and the relative importance of location and subgroup.

Methods We conducted a cross-sectional survey among AGYW aged 14–24 years in Mombasa, Kenya in 2015/16. Using probabilistic sampling we recruited participants from hotspots where female sex workers (FSWs) solicit clients, divided into venue-based (bars/brothels/hotels/brew dens) and non-venue-based (streets/public places) hotspots. We measured HIV prevalence using dried blood spot serology testing and examined predictors of risk including subgroup: engagement in formal sex work; transactional sex (TS) (exchange of sex for goods/money without pre-negotiation of price); and casual sex (CS) (did not self-identify as FSW or engaging in TS). We compared determinants of risk in venue-based and non-venue-based participants after adjusting for age.

Results Overall HIV prevalence was 5.6%, with highest prevalence among FSWs (10.1%), compared to those engaged in TS (3.6%) or CS (3.6%) (p < 0.001). Daily/almost daily alcohol use was associated with higher prevalence in both venue- (AOR 2.8 (1.3–6.1)) and non-venue-based (AOR 5.3 (1.3–21.1)) hotspots. Venue-based participants were also more likely to test positive if they had ever been pregnant [AOR 1.9 (1.0–3.5)], had their first sexual experience aged <15 years [AOR2.2 (1.2–4.1)] or had ever experienced sexual [AOR 3.2 (1.8–5.7)] or physical violence [AOR 2.4 (1.3–4.3)]. Compared to CS and TS, HIV prevalence was higher among FSWs in venue-based hotspots [AOR3.4 (1.8–6.3)], but not non-venues [AOR 1.1 (0.3–3.8)].

Conclusion We identified a high prevalence of HIV among AGYW congregating in hotspots for FSW, with heterogeneity across subgroups. Determinants of HIV varied by location suggesting that one’s environment is an important contributor to risk, and HIV programmes should take this into consideration for designing delivery of interventions.

Disclosure No significant relationships.

  • Kenya
  • sex workers
  • youth

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