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P512 Quantifying sexual mixing by HIV status and pre-exposure prophylaxis (PrEP) use among men who have sex (MSM) with men
  1. Linwei Wang1,
  2. Nasheed Moqueet1,
  3. Gilles Lambert2,
  4. Daniel Grace3,
  5. Ricky Rodrigues4,
  6. Joseph Cox5,
  7. Nathan Lachowsky6,
  8. Syed Noor4,
  9. Heather Armstrong7,
  10. Darrell Tan1,
  11. Ann Burchell1,
  12. Huiting Ma1,
  13. Jesse Knight1,
  14. Stefan Baral8,
  15. Trevor Hart4,
  16. David Moore9,
  17. Sharmistha Mishra10
  1. 1Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Centre for Urban Health Solutions, Toronto, Canada
  2. 2National Institute of Public Health of Quebec, Montreal, Canada
  3. 3University of Toronto, Dalla Lana School of Public Health, Toronto, Canada
  4. 4Ryerson University, Toronto, Canada
  5. 5McGill University, Montreal, Canada
  6. 6University of Victoria, School of Public Health and Social Policy, Victoria, Canada
  7. 7University of British Columbia, Vancouver, Canada
  8. 8Johns Hopkins University, Baltimore, USA
  9. 9BC Centre for Excellence in HIV/AIDS, Vancouver, Canada
  10. 10St. Michael’s Hospital, Centre for Urban Health Solutions, Toronto, Canada


Background Existing measures of preferential partner selection do not account for attribute-concordance by chance. We quantified network-level sexual mixing by HIV status and PrEP use using a balancing partnership approach.

Methods Data were from Engage, a cross-sectional survey of MSM ≥16 year-old in three Canadian cities (2017–2018). MSM with ≥1 anal/oral sex partners in the past six months (P6M) reported their own and partners’ HIV status and PrEP use. After stratifying by respondents’ HIV status (positive/negative/unknown) and P6M PrEP use (yes/no), we compared observed seroconcordance to that expected by chance among P6M-partnerships with known-status. Within HIV negative-concordant recent partnerships, we compared observed concordance in PrEP use at last sex to chance. Concordance by chance is calculated under proportionate-mixing assumption, which means the distribution of partnerships by partners’ attributes equals that by respondents’ attributes as a result of partnership balancing. We used chi-squared tests for all comparisons.

Results Of the 22,102 P6M-partnerships reported by 1881 respondents (17.0%, 74.5% and 8.5% HIV-positive, negative and unknown, respectively), 60.2% comprised partners’ of known-status. 64.3% of HIV-positive respondents’ partnerships were HIV-positive (vs chance 24.6%, p<0.001). HIV-negative or status-unknown respondents had higher proportions of HIV-negative partners (87.0% and 87.5%, respectively, vs chance 75.4%, p<0.001). HIV-negative respondents on PrEP had a higher proportion of HIV-positive partners than those not on PrEP (20.6% vs 8.4%; p<0.001). HIV-negative respondents on PrEP had a higher proportion of HIV-negative partners on PrEP (55.8% vs 34.7%); those not on PrEP had a higher proportion of HIV-negative partners not on PrEP (78.6% vs 65.3%), than chance (p<0.001).

Conclusion Network-level serosorting and PrEP matching were evident after accounting for distribution of partnerships by chance. PrEP-mediated changes to mixing, such as less serosorting among MSM on PrEP, may indirectly influence the population-level HIV prevention impact of PrEP and should be included in the monitoring and evaluation of PrEP roll-out.

Disclosure No significant relationships.

  • gay bisexual and other men who have sex with men
  • ART
  • PrEP
  • serosorting

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