Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis

dc.contributor.authorWang, Linwei
dc.contributor.authorMoqueet, Nasheed
dc.contributor.authorSimkin, Anna
dc.contributor.authorKnight, Jesse
dc.contributor.authorMa, Huiting
dc.contributor.authorLachowsky, Nathan J.
dc.contributor.authorArmstrong, Heather L.
dc.contributor.authorTan, Darrell H.S.
dc.contributor.authorBurchell, Ann N.
dc.contributor.authorHart, Trevor A.
dc.contributor.authorMoore, David M.
dc.contributor.authorAdam, Barry D.
dc.contributor.authorMacfadden, Derek R.
dc.contributor.authorBaral, Stefan
dc.contributor.authorMishra, Sharmistha
dc.date.accessioned2022-03-08T18:53:58Z
dc.date.available2022-03-08T18:53:58Z
dc.date.copyright2021en_US
dc.date.issued2021
dc.descriptionSome of the model parameters in the current modelling article drew on estimates published in Wang et al. 2019 (https://doi.org/10.1093/aje/kwz231). We acknowledge the Engage study and its funders (Canadian Institutes of Health Research (CIHR) Team Grant [TE2-138299]; CIHR Canadian HIV Trials Network [CTN 300]; Canadian Foundation for AIDS Research [Engage]; Canadian Blood Services [MSM2017LP-OD]; Ontario HIV Treatment Network (OHTN) [1051]; Ryerson University [no related grant number]; and Public Health Agency of Canada [4500370314]), which supported the independently published results in Wang et al. 2019 (https://doi.org/10.1093/aje/kwz231). We would like to thank Kristy Yiu for supporting submission and project coordination, and Steven Tingley for helpful discussions surrounding model structure.en_US
dc.description.abstractObjectives: 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 postintervention (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.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipS.M. and D.H.S.T. are supported by a CIHR and the Ontario HIV Treatment Network (OHTN) New Investigator Award. T.A.H. is supported by an OHTN Applied HIV Research Chair Award. D.M.M. and N.J.L. are supported by Scholar Awards from the Michael Smith Foundation for Health Research (#5209, #16863).N.M. was supported by the CIHR-funded Canadian HIV Trials Network Postdoctoral Fellowship. This study was funded by the Canadian Institutes of Health Research (CIHR) foundation grant [grant number FN-13455].en_US
dc.identifier.citationWang, L., Moqueet, N., Simkin, A., Knight, J., Ma, H., Lachowsky, N. J., Armstrong, H. L., Tan, D. H. S., Burchell, A. N., Hart, T. A., Moore, D. M., Adam. B. D., Macfadden, D. R., Baral, S., & Mishra, S. (2021). “Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis.” AIDS, 35(7), 1113-1125. DOI: https://doi.org/10.1097/QAD.0000000000002826en_US
dc.identifier.urihttps://doi.org/10.1097/QAD.0000000000002826
dc.identifier.urihttp://hdl.handle.net/1828/13787
dc.language.isoenen_US
dc.publisherAIDSen_US
dc.subjectHIVen_US
dc.subjectMSMen_US
dc.subjectpre-exposure prophylaxisen_US
dc.subjectserosortingen_US
dc.subjectsexual mixing patternsen_US
dc.titleMathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxisen_US
dc.typeArticleen_US

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