Linwei Wang1, Nasheed Moqueet1, Anna Simkin1, Jesse Knight1,2, Huiting Ma1, Nathan J Lachowsky3, Heather L Armstrong4,5, Darrell H S Tan1,6,7, Ann N Burchell1,8,9, Trevor A Hart9,10, David M Moore4,11, Barry D Adam12, Derek R Macfadden6, Stefan Baral13, Sharmistha Mishra1,2,6,7. 1. MAP-Centre for Urban Health Solutions, St. Michael's Hospital, Unity Health Toronto. 2. Institute of Medical Sciences, University of Toronto, Toronto, Ontario. 3. School of Public Health and Social Policy, University of Victoria, Victoria. 4. British Columbia Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada. 5. School of Psychology, University of Southampton, Southampton, UK. 6. Department of Medicine. 7. Institute of Health Policy, Management, and Evaluation. 8. Department of Family and Community Medicine. 9. Dalla Lana School of Public Health, University of Toronto. 10. Department of Psychology, Ryerson University, Toronto, Ontario. 11. Department of Medicine, Division of Infectious Disease, University of British Columbia, Vancouver, British Columbia. 12. Department of Sociology, Anthropology, and Criminology, University of Windsor, Windsor, Ontario, Canada. 13. Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA.
Abstract
OBJECTIVES: HIV pre-exposure prophylaxis (PrEP) may change serosorting patterns. We examined the influence of serosorting on the population-level HIV transmission impact of PrEP, and how impact could change if PrEP users stopped serosorting. DESIGN: We developed a compartmental HIV transmission model parameterized with bio-behavioural and HIV surveillance data among MSM in Canada. METHODS: We separately fit the model with serosorting and without serosorting [counterfactual; sero-proportionate mixing (random partner-selection proportional to availability by HIV status)], and reproduced stable HIV epidemics with HIV-prevalence 10.3-24.8%, undiagnosed fraction 4.9-15.8% and treatment coverage 82.5-88.4%. We simulated PrEP-intervention reaching stable pre-specified coverage by year-one and compared absolute difference in relative HIV-incidence reduction 10 years post-intervention (PrEP-impact) between models with serosorting vs. sero-proportionate mixing; and counterfactual scenarios when PrEP users immediately stopped vs. continued serosorting. We examined sensitivity of results to PrEP-effectiveness (44-99%; reflecting varying dosing or adherence levels) and coverage (10-50%). RESULTS: Models with serosorting predicted a larger PrEP-impact than models with sero-proportionate mixing under all PrEP-effectiveness and coverage assumptions [median (interquartile range): 8.1% (5.5-11.6%)]. PrEP users' stopping serosorting reduced PrEP-impact compared with when PrEP users continued serosorting: reductions in PrEP-impact were minimal [2.1% (1.4-3.4%)] under high PrEP-effectiveness (86-99%); however, could be considerable [10.9% (8.2-14.1%)] under low PrEP effectiveness (44%) and high coverage (30-50%). CONCLUSION: Models assuming sero-proportionate mixing may underestimate population-level HIV-incidence reductions due to PrEP. PrEP-mediated changes in serosorting could lead to programmatically important reductions in PrEP-impact under low PrEP-effectiveness. Our findings suggest the need to monitor sexual mixing patterns to inform PrEP implementation and evaluation.
OBJECTIVES: HIV pre-exposure prophylaxis (PrEP) may change serosorting patterns. We examined the influence of serosorting on the population-level HIV transmission impact of PrEP, and how impact could change if PrEP users stopped serosorting. DESIGN: We developed a compartmental HIV transmission model parameterized with bio-behavioural and HIV surveillance data among MSM in Canada. METHODS: We separately fit the model with serosorting and without serosorting [counterfactual; sero-proportionate mixing (random partner-selection proportional to availability by HIV status)], and reproduced stable HIV epidemics with HIV-prevalence 10.3-24.8%, undiagnosed fraction 4.9-15.8% and treatment coverage 82.5-88.4%. We simulated PrEP-intervention reaching stable pre-specified coverage by year-one and compared absolute difference in relative HIV-incidence reduction 10 years post-intervention (PrEP-impact) between models with serosorting vs. sero-proportionate mixing; and counterfactual scenarios when PrEP users immediately stopped vs. continued serosorting. We examined sensitivity of results to PrEP-effectiveness (44-99%; reflecting varying dosing or adherence levels) and coverage (10-50%). RESULTS: Models with serosorting predicted a larger PrEP-impact than models with sero-proportionate mixing under all PrEP-effectiveness and coverage assumptions [median (interquartile range): 8.1% (5.5-11.6%)]. PrEP users' stopping serosorting reduced PrEP-impact compared with when PrEP users continued serosorting: reductions in PrEP-impact were minimal [2.1% (1.4-3.4%)] under high PrEP-effectiveness (86-99%); however, could be considerable [10.9% (8.2-14.1%)] under low PrEP effectiveness (44%) and high coverage (30-50%). CONCLUSION: Models assuming sero-proportionate mixing may underestimate population-level HIV-incidence reductions due to PrEP. PrEP-mediated changes in serosorting could lead to programmatically important reductions in PrEP-impact under low PrEP-effectiveness. Our findings suggest the need to monitor sexual mixing patterns to inform PrEP implementation and evaluation.
Authors: Kevin M Maloney; David Benkeser; Patrick S Sullivan; Colleen Kelley; Travis Sanchez; Samuel M Jenness Journal: Epidemiology Date: 2022-07-27 Impact factor: 4.860