Background Gay, bisexual, and other men who have sex with men (gbMSM) experience disproportionate risks of HIV acquisition and transmission. In 2017, Montréal 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 and sexual behaviours on HIV transmission dynamics among gbMSM in Montréal between 1975 and 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, HIV’s natural history, and treatment and prevention strategies were considered. The model simulations were analyzed to estimate the fraction of HIV acquisitions and transmissions attributable to specific groups, with a focus on age, sexual partnering level, and gaps in the HIV care-continuum. Results The model-estimated HIV incidence peaked in 1985 (2.3 per 100 person years (PY); 90% CrI: 1.4–2.9 per 100 PY) and decreased to 0.1 per 100 PY (90% CrI: 0.04–0.3 per 100 PY) in 2019. Between 2000–2017, the majority of HIV acquisitions and 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 90–93% of transmissions and 67–73% of acquisitions annually. The primary stage of HIV played an increasing role over time, contributing to 11–22% of annual transmissions over 2000–2019. In 2019, approximately 70% of transmission events occurred from men who had discontinued, or never initiated antiretroviral therapy. Conclusions The evolving HIV landscape has contributed to the declining HIV incidence among gbMSM in Montréal. The shifting dynamics identified in this study highlight the need for continued population-level surveillance to identify gaps in the HIV care continuum and core groups on which to prioritize elimination efforts.

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

Disease modeling is increasingly being used to evaluate the effect of health intervention strategies, particularly for infectious diseases. However, the utility and application of such models are hampered by the inconsistent use of infectious disease modeling terms between and within disciplines. We sought to standardize the lexicon of infectious disease modeling terms and develop a glossary of terms commonly used in describing models’ assumptions, parameters, variables, and outcomes. We combined a comprehensive literature review of relevant terms with an online forum discussion in a virtual community of practice, mod4PH (Modeling for Public Health). Using a convergent discussion process and consensus amongst the members of mod4PH, a glossary of terms was developed as an online resource. We anticipate that the glossary will improve inter- and intradisciplinary communication and will result in a greater uptake and understanding of disease modeling outcomes in heath policy decision-making. We highlight the role of the mod4PH community of practice and the methodologies used in this endeavor to link theory, policy, and practice in the public health domain.

Background: Reducing HIV transmission using pre-exposure prophylaxis (PrEP) requires focussing on individuals at high acquisition risk, such as men who have sex with men with a history of nonoccupational post-exposure prophylaxis (nPEP). This study aims to characterize longitudinal trends in PrEP uptake and its determinants among nPEP users in Montréal. Methods: Eligible attendees at Clinique médicale l'Actuel were recruited prospectively starting in October 2000 (nPEP) and January 2013 (PrEP). Linking these cohorts, we characterized the nPEP-to-PrEP cascade, examined the determinants of PrEP uptake after nPEP consultation using a Cox proportional-hazard model, and assessed whether PrEP persistence differed by nPEP history using Kaplan–Meier curves. Results: As of August 2019, 31% of 2682 nPEP cohort participants had 2 or more nPEP consultations. Subsequent PrEP consultations occurred among 36% of nPEP users, of which 17% sought nPEP again afterward. Among 2718 PrEP cohort participants, 46% reported previous nPEP use. Among nPEP users, those aged 25–49 years [hazard ratio (HR) = 1.3, 95% confidence interval (CI): 1.1 to 1.7], with more nPEP episodes (HR = 1.4, 95% CI: 1.3 to 1.5), who reported chemsex (HR = 1.3, 95% CI: 1.1 to 1.7), with a sexually transmitted infection history (HR = 1.5; 95% CI: 1.3 to 1.7), and who returned for their first nPEP follow-up visit (HR = 3.4, 95% CI: 2.7 to 4.2) had higher rates of PrEP linkage. There was no difference in PrEP persistence between nPEP-to-PrEP and PrEP only participants. Conclusion: Over one-third of nPEP users were subsequently prescribed PrEP. However, the large proportion of men who repeatedly use nPEP calls for more efficient PrEP-linkage services and, among those who use PrEP, improved persistence should be encouraged.

Human papillomavirus (HPV), a sexually transmitted infection, is the necessary cause of cervical cancer, the third most common cancer affecting women worldwide. Prevention and control strategies include vaccination, screening, and treatment. While HPV prevention and control efforts are important worldwide, they are especially important in low-income areas with a high infection rate or high rate of cervical cancer. This study uses mathematical modeling to explore various vaccination and treatment strategies to control for HPV and cervical cancer while using Nepal as a case study. Two sets of deterministic models were created with the goal of understanding the impact of various prevention and control strategies. The first set of models examines the relative importance of screening and vaccination in an unscreened population, while the second set examines various screening scenarios. Partial rank correlation coefficients confirm the importance of screening and treatment in the reduction of HPV infections and cancer cases even when vaccination uptake is high. Results also indicate that less expensive screening technologies can achieve the same overall goal as more expensive screening technologies.