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Aims: People under age 18 who inject drugs represent a population at risk of health and social harms. Age restrictions at harm reduction programmes often formally exclude this population, but the reason behind such restrictions is lacking in the literature. To help fill this gap, we examine the perspectives of people who use drugs and various other stakeholders regarding whether supervised injection facilities (SIFs) should have age restrictions. Methods: Interviews and focus groups were conducted with a total of 95 people who use drugs and 141 other stakeholders (including police, fire and emergency services personnel, other city employees and officials, healthcare providers, residents and business representatives) in two Canadian cities without SIFs. Findings: We highlight the following thematic areas: mixed opinions regarding specific age restrictions; safety as a priority; different experiences and understandings of youth, agency and drug use; and ideas regarding maturity, ''help'' and other approaches. We note throughout that a familiar vulnerability--agency dichotomy often surfaced in the discussions. Conclusions: This paper contributes new empirical insights regarding youth access to SIFs. We offer considerations that may inform discussions occurring in other jurisdictions debating SIF implementation and may help remove or clarify age-related policies for harm reduction programmes.

Background: The emergence of SARS-CoV-2 variants and COVID-19 vaccination have resulted in complex exposure histories. Rapid assessment of the effects of these exposures on neutralising antibodies against SARS-CoV-2 infection is crucial for informing vaccine strategy and epidemic management. We aimed to investigate heterogeneity in individual-level and population-level antibody kinetics to emerging variants by previous SARS-CoV-2 exposure history, to examine implications for real-time estimation, and to examine the effects of vaccine-campaign timing., Methods: Our Bayesian hierarchical model of antibody kinetics estimated neutralising-antibody trajectories against a panel of SARS-CoV-2 variants quantified with a live virus microneutralisation assay and informed by individual-level COVID-19 vaccination and SARS-CoV-2 infection histories. Antibody titre trajectories were modelled with a piecewise linear function that depended on the key biological quantities of an initial titre value, time the peak titre is reached, set-point time, and corresponding rates of increase and decrease for gradients between two timing parameters. All process parameters were estimated at both the individual level and the population level. We analysed data from participants in the University College London Hospitals-Francis Crick Institute Legacy study cohort (NCT04750356) who underwent surveillance for SARS-CoV-2 either through asymptomatic mandatory occupational health screening once per week between April 1, 2020, and May 31, 2022, or symptom-based testing between April 1, 2020, and Feb 1, 2023. People included in the Legacy study were either Crick employees or health-care workers at three London hospitals, older than 18 years, and gave written informed consent. Legacy excluded people who were unable or unwilling to give informed consent and those not employed by a qualifying institution. We segmented data to include vaccination events occurring up to 150 days before the emergence of three variants of concern: delta, BA.2, and XBB 1.5. We split the data for each wave into two categories: real-time and retrospective. The real-time dataset contained neutralising-antibody titres collected up to the date of emergence in each wave; the retrospective dataset contained all samples until the next SARS-CoV-2 exposure of each individual, whether vaccination or infection., Findings: We included data from 335 participants in the delta wave analysis, 223 (67%) of whom were female and 112 (33%) of whom were male (median age 40 years, IQR 22-58); data from 385 participants in the BA.2 wave analysis, 271 (70%) of whom were female and 114 (30%) of whom were male (41 years, 22-60); and data from 248 participants in the XBB 1.5 wave analysis, 191 (77%) of whom were female, 56 (23%) of whom were male, and one (<1%) of whom preferred not to say (40 years, 21-59). Overall, we included 968 exposures (vaccinations) across 1895 serum samples in the model. For the delta wave, we estimated peak titre values as 490·0 IC 50 (95% credible interval 224·3-1515·9) for people with no previous infection and as 702·4 IC 50 (300·8-2322·7) for people with a previous infection before omicron; the delta wave did not include people with a previous omicron infection. For the BA.2 wave, we estimated peak titre values as 858·1 IC 50 (689·8-1363·2) for people with no previous infection, 1020·7 IC 50 (725·9-1722·6) for people with a previous infection before omicron, and 1422·0 IC 50 (679·2-3027·3) for people with a previous omicron infection. For the XBB 1.5 wave, we estimated peak titre values as 703·2 IC 50 (415·0-3197·8) for people with no previous infection, 1215·9 IC 50 (511·6-7338·7) for people with a previous infection before omicron, and 1556·3 IC 50 (757·2-7907·9) for people with a previous omicron infection., Interpretation: Our study shows the feasibility of real-time estimation of antibody kinetics before SARS-CoV-2 variant emergence. This estimation is valuable for understanding how specific combinations of SARS-CoV-2 exposures influence antibody kinetics and for examining how COVID-19 vaccination-campaign timing could affect population-level immunity to emerging variants., Funding: Wellcome Trust, National Institute for Health Research University College London Hospitals Biomedical Research Centre, UK Research and Innovation, UK Medical Research Council, Francis Crick Institute, and Genotype-to-Phenotype National Virology Consortium., Competing Interests: Declaration of interests CSw receives grants from Bristol Myers Squibb, Ono Pharmaceuticals, Boehringer Ingelheim, Roche-Ventana, Pfizer, and Archer Dx; receives personal fees from Genentech, the Sarah Canon Research Institute, Medicxi, Bicycle Therapeutics, GRAIL, Amgen, AstraZeneca, Bristol Myers Squibb, Illumina, GlaxoSmithKline, MSD, and Roche-Ventana; holds stock options in Apogen Biotech, Epic Biosciences, GRAIL, and Achilles Therapeutics; is a member of a scientific advisory board for Bicycle Therapeutics, GRAIL, Relay Therapeutics, SAGA Diagnostics, and Achilles Therapeutics; is a co-founder of Achilles Therapeutics; receives consulting fees from Genentech, Medicxi, MetaboMed, Novartis, the China Innovation Centre of Roche, and the Sarah Cannon Research Institute; and receives honoraria from Amgen, AstraZeneca, Bristol Myers Squibb, Illumina, and Incyte. DLVB receives grants, paid to their institution, from AstraZeneca. EJC is an unpaid member of the Infection, Prevention and Control Committee of the UK Kidney Association. RB and DLVB are members of the Genotype-to-Phenotype 2 Consortium. AJK received the Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (grant number 206250/Z/17/Z). AJK and DH were supported by the National Institutes of Health (1R01AI141534–01A1). All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)