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

Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis
Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis
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 men who have sex with men 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-1 and compared absolute difference in relative HIV-incidence reduction ten-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 (inter-quartile-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%).
Conclusions: 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.
0269-9370
1113-1125
Wang, Linwei
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Moqueet, Nasheed
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Simkin, Anna
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Knight, Jesse
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Ma, Huiting
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Lachowsky, Nathan J.
87634bac-759c-4e7b-9f16-22fb37e87cf6
Armstrong, Heather
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Tan, Darrell
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Burchell, Ann
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Hart, Trevor
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Moore, David M.
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Adam, Barry
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MacFadden, Derek
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Baral, Stefan
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Mishra, Sharmistha
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Wang, Linwei
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Moqueet, Nasheed
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Simkin, Anna
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Knight, Jesse
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Ma, Huiting
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Lachowsky, Nathan J.
87634bac-759c-4e7b-9f16-22fb37e87cf6
Armstrong, Heather
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Tan, Darrell
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Burchell, Ann
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Hart, Trevor
49f351fd-ecb1-4fae-a272-93d1050e0aca
Moore, David M.
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Adam, Barry
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MacFadden, Derek
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Baral, Stefan
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Mishra, Sharmistha
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Wang, Linwei, Moqueet, Nasheed, Simkin, Anna, Knight, Jesse, Ma, Huiting, Lachowsky, Nathan J., Armstrong, Heather, Tan, Darrell, Burchell, Ann, Hart, Trevor, Moore, David M., Adam, Barry, MacFadden, Derek, Baral, Stefan and Mishra, Sharmistha (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:10.1097/QAD.0000000000002826).

Record type: Article

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 men who have sex with men 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-1 and compared absolute difference in relative HIV-incidence reduction ten-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 (inter-quartile-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%).
Conclusions: 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.

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Accepted/In Press date: 11 January 2021
e-pub ahead of print date: 29 January 2021
Published date: 1 June 2021
Additional Information: Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.

Identifiers

Local EPrints ID: 446563
URI: http://eprints.soton.ac.uk/id/eprint/446563
ISSN: 0269-9370
PURE UUID: 7d0bdddd-d7a6-4e04-aa05-adcbfee516f2
ORCID for Heather Armstrong: ORCID iD orcid.org/0000-0002-1071-8644

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Date deposited: 15 Feb 2021 17:31
Last modified: 17 Mar 2024 06:15

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Contributors

Author: Linwei Wang
Author: Nasheed Moqueet
Author: Anna Simkin
Author: Jesse Knight
Author: Huiting Ma
Author: Nathan J. Lachowsky
Author: Darrell Tan
Author: Ann Burchell
Author: Trevor Hart
Author: David M. Moore
Author: Barry Adam
Author: Derek MacFadden
Author: Stefan Baral
Author: Sharmistha Mishra

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