Past dynamics of HIV transmission among men who have sex with men in Montreal, Canada: a mathematical modelling study

medRxiv(2021)

Cited 5|Views4
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Abstract
Background: Gay, bisexual, and other men who have sex with men (gbMSM) experience disproportionate risks of HIV acquisition/transmission. In 2017, Montreal became the first Canadian Fast-Track city, setting the 2030 goal of zero new HIV infections. To inform local elimination efforts, we estimate the evolving role of prevention/risk behaviours and HIV transmission dynamics among gbMSM in Montreal between 1975-2019. Methods: Data from local bio-behavioural surveys were analyzed to develop, parameterize, and calibrate an agent-based model of sexual HIV transmission. Partnership dynamics, the HIV natural history, and treatment and prevention strategies were considered. The model simulations were analyzed to estimate the fraction of HIV acquisitions/transmissions attributable to specific age-groups and unmet prevention needs. Results: The model-estimated HIV incidence peaked in 1985 (2.2%; 90%CrI: 1.3-2.8%) and decreased to 0.1% (90%CrI: 0.04-0.3%) in 2019. Between 1990-2017, the majority of HIV acquisitions/transmissions occurred among men aged 25-44 years, and men aged 35-44 thereafter. The unmet prevention needs of men with >10 annual anal sex partners contributed 92-94% of transmissions and 63-73% of acquisitions annually. The primary stage of HIV played an increasing role over time, contributing to 12%-27% of annual transmissions over 1990-2019. In 2019, approximately 75% of transmission events occurred from men who had discontinued, or never initiated ART. Conclusions: The evolving HIV landscape has contributed to the recent low HIV incidence among MSM in Montreal. The shifting dynamics identified in this study highlight the need for continued population-level surveillance to identify unmet prevention needs and core groups on which to prioritize elimination efforts.
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Key words
HIV/AIDS,Gay bisexual and other men who have sex with men (gbMSM),Mathematical modeling,Agent-based model,Approximate Bayesian Computation Sequential Monte Carlo,Treatment and care cascade
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