Impact of interventions on mpox transmission during the 2022 outbreak in Canada: a mathematical modeling study of three different cities
Bibliographic record
Abstract
OBJECTIVES: The global mpox (clade II) outbreak of 2022 primarily affected gay, bisexual, and other men who have sex with men (GBM) and was met with swift community and public health responses. We aimed to estimate the relative impact of changes in sexual behaviors, contact tracing/isolation, and first-dose vaccination on transmission in Canadian cities. METHODS: We estimated changes in sexual behaviors during the outbreak using 2022 data from the Engage Cohort Study, which recruited self-identified GBM in Montréal, Toronto, and Vancouver (n = 1,445). We developed a transmission dynamic model to estimate the fraction of new infections averted due to the three interventions in each city. RESULTS: The empirical estimates of sexual behavior changes were imprecise: a 20% reduction (RR = 0.80; 95% credible interval [95% CrI]: 0.47-1.36) in the number of sexual partners in the past 6 months among those reporting ≤7 partners and a 33% (RR = 0.67; 95% CrI: 0.31-1.43) reduction among those with >7 partners. The three interventions combined averted 46%-58% of cases. Reductions in sexual partners and contact tracing/isolation prevented approximately 12% and 14% of cases, respectively. Vaccination's effect varied across cities due to the programs' timing and coverage, with 21%-39% mpox infections prevented. CONCLUSIONS: Reduction in sexual activity, contact tracing/isolation, and vaccination all contributed to accelerating epidemic control. Early vaccination had the largest impact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".