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Record W3003682467 · doi:10.1101/2020.01.27.20018994

Trends in hepatitis C virus seroprevalence and associated risk factors among men who have sex with men in Montréal: results from three cross-sectional studies (2005, 2009, 2018)

2020· preprint· en· W3003682467 on OpenAlexafffundabout
Charlotte Lanièce Delaunay, Joseph Cox, Marina B. Klein, Gilles Lambert, Daniel Grace, Nathan J. Lachowsky, Mathieu Maheu‐Giroux

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsPublic Health OntarioCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversity of TorontoInstitut National de Santé Publique du QuébecUniversity of VictoriaMcGill UniversityMcGill University Health Centre
FundersInstitut National de Santé Publique du Québec
KeywordsSeroprevalenceMen who have sex with menDemographyMedicineConfidence intervalPopulationPsychological interventionPoisson regressionEnvironmental healthVirologyHuman immunodeficiency virus (HIV)ImmunologySyphilisInternal medicineSerology

Abstract

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Abstract Introduction To eliminate the hepatitis C virus (HCV) by 2030, Canada must adopt a micro-elimination approach targeting priority populations, including gay, bisexual, and other men who have sex with men (MSM). HCV prevalence and risk factors among MSM populations are context-dependent, and accurately describing these indicators at the local level is essential if we want to design appropriate, targeted prevention and treatment interventions. We aimed first to estimate and investigate temporal trends in HCV seroprevalence between 2005-2018 among Montréal MSM, and then to identify the socio-economic, behavioural, and biological factors associated with HCV exposure among this population. Methods We used data from three bio-behavioural cross-sectional surveys conducted among Montréal MSM in 2005 (n=1,795), 2009 (n=1,258), and 2018 (n=1,086). To ensure comparability of seroprevalence estimates across time, we standardized the 2005 and 2009 time-location samples to the 2018 respondent-driven sample. Time trends overall and stratified by HIV status, history of injection drug use (IDU), and age were examined. Modified Poisson regression analyses with generalized estimating equations were used to identify factors associated with HCV seropositivity pooling all surveys. We used multiple imputation by chained equations for all missing values. Results Standardized HCV seroprevalence among all MSM remained stable from 7% (95% confidence interval (CI): 3-10%) in 2005, to 8% (95%CI: 1-9%) in 2009, and 8% (95%CI: 4-11%) in 2018. This apparent stability hides diverging temporal trends in seroprevalence between age groups, with a decrease among MSM <30 years old, and an increase among MSM aged ≥45 years. History of IDU was the strongest predictor for HCV seropositivity (adjusted prevalence ratio: 8.0; 95%CI: 5.5-11.5), and no association was found between HCV seroprevalence and the sexual risk factors studied (condomless anal sex with men of serodiscordant/unknown HIV status, number of sexual partners, and group sex), nor with biological markers of syphilis. Conclusions HCV seroprevalence remained stable among Montréal MSM between 2005-2018. Unlike other settings where HCV infection was strongly associated with sexual risk factors among MSM subgroups, IDU was the preeminent risk factor for HCV seropositivity. Understanding the intersection of IDU contexts, practices, and populations is essential to prevent HCV transmission among MSM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.336
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2020
Admission routes3
Has abstractyes

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