Increasing incidence of anogenital warts with an urban–rural divide among males in Manitoba, Canada, 1990–2011
Bibliographic record
Abstract
BACKGROUND: Anogenital warts (AGW) are caused by the most common sexually transmitted infection, human papillomavirus. The objective of this study was to examine AGW incidence from 1990 to 2011 by sex, age, income quintile, and residential area category (urban/rural). The study period included the initiation of school-based HPV vaccination for girls in the sixth grade, which began in 2008. The data presented in this paper may also be useful for establishing baseline rates of AGW incidence which may be used to evaluate the success of the school-based HPV immunization program. METHODS: Cases of anogenital warts were identified using Manitoba's administrative databases of Physician Claims and Hospital Discharge Abstracts. Annual age-standardized incidence in Manitoba from 1990 to 2011 was calculated. Incident AGW rates were compared by sex, age group, residential area category (urban/rural), and household income quintile using logistic regression. Joinpoint regression analyses were used to evaluate the time trends of AGW. RESULTS: Prior to 2000, AGW incidence was higher among females than males. However, from 2000 to 2011 the incidence was higher among males and increased steadily over time. AGW incidence tended to peak in younger age groups among females compared to males. Females and males living in urban areas had nearly twice the odds of AGW occurrence compared to those in rural areas. CONCLUSIONS: There is a need for education about AGW in male population. The upcoming initiation of HPV vaccination among boys may reduce the incidence and should be evaluated.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".