Bibliographic record
Abstract
INTRODUCTION: Globally, the three main pathogens causing serious infections are Haemophilus influenzae type b, Streptococcus pneumoniae and Neisseria meningitidis. Over the last 5 years, new vaccines protecting against these bacteria have been developed and introduced in various countries. AREAS COVERED: This review describes the recently licensed glycoconjugates being used to protect against these encapsulated bacteria. Immunogenicity and safety data that led to licensure or licensure expansion of these glycoconjugates are discussed in addition to the resultant impact on the disease burden. EXPERT OPINION: The maintenance of robust immunisation programmes with high uptake rates is important in maintaining low rates of disease. Epidemiological surveillance systems are essential in monitoring any changes in infectious disease trends and in identifying emerging infections such as from non-typeable H. influenzae, pneumococcal serotype replacement disease and changes in the epidemiology of meningococcal serogroups. This is important to guide future vaccine development. Accessibility of these glycoconjugate vaccines in resource poor regions, which bear the highest disease burden from these pathogens, remains challenging largely due to high vaccine pricing. Recent aids from public and private funding, tiered vaccine pricing and the transfer of vaccine technology have helped in introducing these vaccines where they are most needed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; both teacher heads agree on what is shown here.
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".