Consistent, Excess Viral Meningitis Incidence Rates in Young Males: A Multi-country, Multi-year, Meta-analysis of National Data. The Importance of Sex as a Biological Variable
Bibliographic record
Abstract
BACKGROUND: Sex can be an important biological variable in the immune response to infections and the response to vaccines. The magnitude and consistency in age-specific sex differences in the incidence of viral infections remain unclear. METHODS: We obtained data from national official agencies on cases of viral meningitis by sex and age group over a period of 6-16 years from five countries: Canada, Czech Republic, Germany, Israel, and Poland. Male to female incidence rate ratios (RR) were computed for each year, by country, and age group. For each age group, we used meta-analysis methodology to combine the incidence RRs. Meta-regression was conducted to the estimate the effects of age, country, and time period on the RR. FINDINGS: In the age groups < 1, 1-4, 5-9, 10-14, there were consistently higher incidence rates in males, over countries and time. The pooled incidence RRs (with 95% CI) were 1.38 (1.30-1.47), 1.94 (1.85-2.03), 1.98 (1.88-2.07), and 1.58 (1.47-1.71) respectively. In young and middle-age adults there were no differences with pooled incidence RRs of 1.00 (0.97-1.03), and 0.97 (0.94-1.00), respectively. Sensitivity analysis confirms that the results are stable and robust. Meta-regression showed that almost all the variations in the incidence RRs were contributed by age group. INTERPRETATION: The higher incidence rates from viral meningitis in males under the age of 15 are remarkably consistent across countries and time-periods. These findings emphasize the importance of sex as a biological variable in infectious diseases. This could provide keys to the mechanisms of infection and lead to more personalized treatment and vaccine doses and schedules. FUNDING: There was no funding source for this article.
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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 | 0.033 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.067 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".