Laboratory-Based Surveillance of Neisseria meningitidis Isolates from Disease Cases in Latin American and Caribbean Countries, SIREVA II 2006–2010
Bibliographic record
Abstract
BACKGROUND: Published data on the epidemiology of meningococcal disease in Latin America and the Caribbean region is scarce and, when available, it is often published in Spanish and/or in non-peer-reviewed journals, making it difficult for the international scientific community to have access. METHODS: Laboratory data on 4,735 Neisseria meningitidis strains was collected and reported by the National Reference Laboratories in 19 Latin American countries and the Caribbean Epidemiology Centre (CAREC) between 2006 and 2010 as part of the work carried out by the SIREVA II network. Serogroup and MIC to penicillin, rifampin and chloramphenicol were determined. RESULTS: Isolates were mainly obtained from patients <5 years, but each year around 25% of isolates came from adult patients. Serogroup distribution was highly variable among countries. Serogroup C was the main cause of disease in Brazil; the majority of disease seen in the Southern cone was caused by serogroup B, but serogroup W135 strains have increased in recent years. In the Andean and Mexico, Central America and Caribbean regions, serogroups B and C were equally present, and serogroup Y was frequently isolated. Isolates were generally susceptible to chloramphenicol, penicillin and rifampin, but almost 60% of isolates characterized in Southern cone countries presented intermediate resistance to penicillin. Five rifampin-resistant isolates have been isolated in Uruguay and Brazil. CONCLUSIONS: Serogroup distribution is highly variable among countries, but some geographic structuring can be inferred from these data. Epidemiological and laboratory data are scarce among Andean and Mexico, Central America and Caribbean countries. Evaluation and implementation of corrective measures on disease surveillance and reporting systems and the implementation of molecular diagnostic techniques and molecular characterization on meningococcal isolates are advised.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".