Estimated cytomegalovirus seroprevalence in the general population of the United States and Canada
Bibliographic record
Abstract
Seroprevalence data for cytomegalovirus (CMV), a widespread virus causing lifelong infection, vary widely, and contemporary data from the United States (US) and Canada are limited. Utilizing a modeling approach based on a literature review (conducted August, 2022) of data published since 2005, we determine age-, sex-, and country-specific CMV seroprevalence in the general US and Canadian populations. Sex-specific data were extracted by age categories, and a random-effects meta-regression model was used to fit the reported data (incorporating splines for the US). Seven studies reported US CMV seroprevalence (both sexes, aged 1‒89 years); all used National Health and Nutrition Examination Survey data. Due to limited population-based studies, Canadian estimates were modeled using other limited country data. In both countries, modeled seroprevalence estimates increased with age and were higher in females versus males (US: 49.0% vs. 41.6% at 18‒19 years; 61.5% vs. 50.0% at 38‒39 years; Canada: 23.7% vs. 13.7% at 18‒19 years; 32.6% vs. 22.6% at 38‒39 years). Notably, by young adulthood, one-half of US and one-quarter of Canadian females have acquired CMV. The observed differences in CMV seroprevalence in the US and Canada may partially reflect variations in general population characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".