Pertussis Across the Globe
Bibliographic record
Abstract
Pertussis has reemerged as a problem across the world. To better understand the nature of the resurgence, we reviewed recent epidemiologic data and we report disease trends from across the world. Published epidemiologic data from January 2000 to July 2013 were obtained via PubMed searches and open-access websites. Data on vaccine coverage and reported pertussis cases from 2000 through 2012 from the 6 World Health Organization regions were also reviewed. Findings are confounded not only by the lack of systematic and comparable observations in many areas of the world but also by the cyclic nature of pertussis with peaks occurring every 3-5 years. It appears that pertussis incidence has increased in school-age children in North America and western Europe, where acellular pertussis vaccines are used, but an increase has also occurred in some countries that use whole-cell vaccines. Worldwide, pertussis remains a serious health concern, especially for infants, who bear the greatest disease burden. Factors that may contribute to the resurgence include lack of booster immunizations, low vaccine coverage, improved diagnostic methods, and genetic changes in the organism. To better understand the epidemiology of pertussis and optimize disease control, it is important to improve surveillance worldwide, irrespective of pertussis vaccine types and schedules used in each country.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".