Toxoplasma gondii Infection in the United States: Seroprevalence and Risk Factors
Bibliographic record
Abstract
Infection with Toxoplasma gondii can cause severe illness when the organism is contracted congenitally or when it is reactivated in immune-suppressed persons. To determine the prevalence of T. gondii infection in a representative sample of the US population, the authors tested sera from participants in the Third National Health and Nutrition Examination Survey (1988-1994) for immunoglobulin G antibodies to T. gondii. Of 27,145 persons aged > or =12 years, 17,658 (65%) had sera tested. The overall age-adjusted seroprevalence was 22.5% (95% confidence interval (CI): 21.1, 23.9); among women aged 15-44 years, seroprevalence was 15.0% (95% CI: 13.2, 17.0). Age-adjusted seroprevalence was higher in the Northeast (29.2%) than in the South (22.8%), Midwest (20.5%), or West (17.5%) (p < 0.05). In multivariate analysis, risk for T. gondii infection increased with age and was higher among persons who were foreign-born, persons with a lower educational level, those who lived in crowded conditions, and those who worked in soil-related occupations, although in subset analyses risk categories varied by race/ethnicity. Nearly one quarter of adults and adolescents in the United States have been infected with T. gondii. Most women of childbearing age in the United States are susceptible to acute infection and should be educated about ways to minimize exposure to T. gondii.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".