1747Are Screening Blitzes Contributing to the Observed Trends in Syphilis Outbreaks in Urban Men Who Have Sex with Men?
Bibliographic record
Abstract
Background. Syphilis has reemerged as a significant public health problem in many urban centers in North America, with outbreaks focused in men who sex with men (MSM). In many jurisdictions, these recent outbreaks have displayed a stereotyped behavior, with initial increases in diagnosed cases followed by a period of plateau or decrease, and a subsequent resurgence in rates. We hypothesized that intensive screen and treat campaigns ('blitzes') may be contributing to observed syphilis trends. Methods. We developed a dynamic compartmental mathematical model of syphilis transmission in a population of sexually active MSM. Parameters were derived from the biomedical literature and by model calibration. We assumed that base case annual screening coverage was 30%. We modeled a one-year transient increase in syphilis screening, with population coverage of screening during this blitz period ranging from 50-90%, followed by a return to base case screening levels. We evaluated the impact of screening blitzes on model-projected syphilis incidence and incidence of diagnosed early syphilis over a 10-year period following the transient screening increase. Results. Blitzes were projected to result in transient stabilization (blitz coverage of 50-60%) or decreases (blitz coverage of ≥70%) in diagnosed cases and syphilis incidence. These declines were followed by rebounds in disease occurrence. Diagnoses of early syphilis cases were projected to exceed base case levels by the end of the evaluation period, regardless of blitz intensity. At the end of the evaluation period, syphilis incidence was projected to reach higher levels (4-28% relative to base case) than in the absence of intervention (figure). The overall impact on disease burden was minimal, with no significant change in cumulative syphilis incidence in the post-intervention period. Conclusion. Sharp increases in syphilis screening as a result of screening blitzes may account for observed trends in syphilis diagnoses in MSM. Such interventions are not projected to reduce disease burden in the long-term, suggesting that efforts to achieve regular, sustained screening of at-risk individuals are likely to be more impactful for outbreak control. Disclosures. All authors: No reported disclosures.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".