Seroprevalence of Rubella among Women of Reproductive Age in Iran: A Prisma-Based Systematic Review and Meta-Analysis.
Bibliographic record
Abstract
OBJECTIVE: Rubella is a highly contagious viral disease with a significant teratogenic effect. Various results have been published about the seroprevalence of rubella in Iran. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-systematic review and meta-analysis were conducted to assess the immunity against rubella in Iranian women. METHODS: Eleven English and Persian electronic databases including PubMed, ScienceDirect, Scopus, Web of Science, Google Scholar, Embase, Scientific Information Database, Iran doc, Iran Medex, Magiran, and Medlib were searched using the keywords: Epidemiology, Prevalence, Rubella, Women, Childbearing age, Reproductive age, and Iran. A mathematician (NS) reviewed all steps for accuracy. RESULTS: Out of 1,520 articles, 25 well-conducted studies with a total amount of 10,145 women were reviewed. The pooled prevalence rate of anti-rubella IgG was 84% (95% CI: 83%-86%). The highest prevalence rate of IgG was in Zahedan, Rasht, and Arak (each 100%), while the lowest prevalence was in Jahrom (54%). Subgroup analysis showed that from 1989 through 2012, the IgG prevalence rate increased from 78% (95% CI: 73-83%) to 99% (95% CI: 98 100%). CONCLUSIONS: Although the vaccination program seems working in Iran, some peripheral regions may be a target to improve health care policies.
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 | 0.023 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.037 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".