Characteristics of the sexual networks of gay, bisexual, and other men who have sex with men and impact of past interventions on mpox transmission during the 2022 outbreak in Montréal, Toronto, and Vancouver (Canada)
Notice bibliographique
Résumé
Background: The 2022-2023 global mpox outbreak affected more than 90,000 people in 110 historically non-endemic countries, including Canada. Almost all reported Canadian cases were among gay, bisexual, and other men who have sex with men (GBM) and 70% of the cases occurred in the country’s three largest cities: Montréal, Toronto, and Vancouver. It remains unknown how characteristics of GBM sexual networks and public health interventions shaped mpox’s transmission dynamics in the three cities.Objectives: My thesis aims to understand mpox outbreaks and inform preparedness and response to re-emerging threats through data-driven statistical and mathematical modeling. Specifically, I addressed two main research questions: 1) How did GBM’s sexual networks affect mpox’s transmission potential in Montréal, Toronto, and Vancouver? 2) What is the relative contribution of changes in sexual partner numbers, contact tracing/isolation, and first-dose vaccination to the epidemic downturn of the 2022-2023 mpox outbreak?Methods: For 1), I leveraged the Engage Cohort Study (2017-present), which recruited self-identified GBM in Montréal, Toronto, or Vancouver via respondent-driven sampling (RDS). Using this data, I compared GBM’s self-reported number of sexual partners in the past 6 months (P6M) across cities and by time periods (i.e., pre-COVID-19 pandemic, pandemic, and after lifting travel restrictions). I modeled the distributions of sexual partners using Bayesian negative binomial regressions, adjusting for key correlates, survey weights, and loss to follow-up. I then developed a deterministic mathematical model to estimate mpox’s city-specific basic reproduction number (R0). For 2), I examined if GBM’s number of sexual partners changed during the peak of the mpox outbreak in Canada (May–August 2022) compared to the rest of 2022 using a negative binomial regression model. I expanded the deterministic mathematical model to estimate the averted fraction of new infections (AF) in the first 150 days of the outbreak through the three interventions separately, as compared to the counterfactual scenario of an unmitigated epidemics.Results: A total of 2,449 GBM participated in Engage (Montréal: 1,179; Toronto: 517; Vancouver: 753). The pre-COVID-19 pandemic distribution of sexual partner numbers (P6M) was similar across cities: participants’ mean number of partners was 10.4 (95% credible interval [CrI]: 9.4-11.5) in Montréal, 13.1 (11.3-15.1) in Toronto, and 10.7 (9.5-12.1) in Vancouver. Partner numbers decreased greatly during the COVID-19 pandemic in all cities: 4.7 (4.0-5.5) in Montréal, 4.3 (3.3-5.8) in Toronto, and 5.5 (4.3-7.3) in Vancouver. Post-travel-restrictions, sexual partner numbers increased but remained well below pre-pandemic levels: 5.5 (4.7-6.4) in Montréal, 7.2 (5.7-9.1) in Toronto, and 6.7 (5.3-8.4) in Vancouver. The estimated R0 for mpox varied from 2.4 to 2.7 between cities. During the peak of the mpox outbreak, GBM might have had fewer sexual partners compared to the rest of 2022, but the estimates were imprecise. A larger decline was observed among GBM with >7 sexual partners (P6M) before 2022 (rate ratio [RR]: 0.67, 95%CrI: 0.31-1.43), as compared to 0.80 (0.47-1.36) among those with ≤ 7 sexual partner, but credible intervals were overlapping and very wide. Cases prevented by changes in sexual partner numbers and contact tracing/isolation were around 12% and 14% in the cities, respectively. Vaccination averted most cases in all cities, contributing to 21% (16%-33%), 22% (16%-41%), and 39% (35%-48%) of infections prevented in Montréal, Toronto, and Vancouver, respectively.Conclusions: The 2022-23 mpox outbreak in Canada occurred while sexual activity had not yet recovered to pre-pandemic levels and ongoing surveillance is warranted. In case of mpox resurgence, ensuring contact tracing/isolation, as well as increasing vaccination coverage among individuals with high numbers of sexual partners, should be prioritized
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».