Seroprevalence of Bactericidal, Specific IgG Antibodies and Incidence of Meningitis Due to Group A Neisseria meningitidis by Age in Burkina Faso 2008
Bibliographic record
Abstract
BACKGROUND: We investigated serological correlates of protection against Neisseria meningitidis serogroup A (NmA) in Burkina Faso before the introduction of NmA conjugate vaccine. METHODOLOGY/PRINCIPAL FINDINGS: We collected blood from a representative sample (N = 1022) of Bobo-Dioulasso residents. Sera were evaluated for serum bactericidal antibody (SBA) activity against NmA strains of immunotype L11 (F8238) and L10 (3125) and NmA-specific IgG. Seroprevalence was compared to the age-specific NmA meningitis incidence in Bobo-Dioulasso during March 2007-February 2008. Meningococcal carriage was evaluated in a subset (N = 538). Geometric mean titres (GMT)/concentrations (GMC) of SBA and NmA-specific IgG increased with age, peaking around age 20 years. Overall, 70% of our sample had NmA-specific IgG ≥2 ug/mL. Meningitis incidence was highest in those aged <6 months and 5-19 years. No NmA carriers were found. Compared to the reference strain SBA, GMTs were higher against a locally isolated strain and around 40-fold lower against Dutch strain 3125. CONCLUSIONS/SIGNIFICANCE: This study provides estimates of natural immunity to NmA, according to a variety of antibody measures, which will be helpful in ascertaining antibody persistence after MenAfriVac™ introduction. Age-specific seroprevalence of reference strain SBA titres most likely reflects exposure to meningococci and consecutive reactive immunity. We could not define any serological correlate of protection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".