Regional Distribution of Antibodies to Herpes Simplex Virus Type 1 (HSV-1) and HSV-2 in Men and Women in Ontario, Canada
Bibliographic record
Abstract
This study estimated the regional and age- and gender-specific seroprevalences of herpes simplex virus type 1 (HSV-1) and HSV-2 in Ontario, Canada. Stored serum specimens from subjects aged 15 to 44 years, including men (n = 979), women not under prenatal care (n = 638), and women under prenatal care (n = 701) submitted for routine viral serology were randomly selected according to regional population size from public health laboratories. HSV-1 and HSV-2 testing was done with the MRL enzyme immunoassay (EIA) (Focus Technologies), and HSV-2 was also tested by the Gull/Meridian EIA. Specimens discordant for HSV-2 antibodies between the two EIAs were resolved by a recombinant immunoblot assay (Focus Technologies). The overall age- and gender-standardized seroprevalences of HSV-1 and HSV-2 were 51.1% (95% confidence interval [CI], 50.1 to 52.1) and 9.1% (95% CI, 8.6 to 9.7), respectively. The seroprevalence of HSV-1 antibodies increased from 26.9 to 54.7% in men between 15 to 16 and 40 to 44 years of age, from 32.0 to 88.7% in women not under prenatal care, and from 55.2 to 69.2% in women under prenatal care. The seroprevalence of HSV-2 increased from 3.8 to 21.3% in men between 15 to 16 and 40 to 44 years of age, from 0 to 18.9% in women not under prenatal care, and from 3.4 to 23.1% in women under prenatal care. HSV-2 results were discordant for 3.3% (76 of 2,318) of specimens. Both types of HSV antibodies appeared to be acquired earlier among women under prenatal care than among men and women not under prenatal care. Antibodies were more prevalent among people in northern Ontario (72.9% of subjects [range, 68.4 to 77.4%] for HSV-1 and 13.7% of subjects [95% CI, 10.2 to 17.2%] for HSV-2) than elsewhere.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".