The Central Importance of Vaccines to Mitigate the Threat of Antibiotic-Resistant Bacterial Pathogens
Bibliographic record
Abstract
Antibiotics have dramatically reduced the burden of infectious diseases since their discovery, but the accelerating rise in antimicrobial resistance (AMR) now threatens these gains. AMR was responsible for nearly 5 million deaths in 2023 and continues to undermine the efficacy of existing treatments, particularly in low- and middle-income countries. While efforts to address AMR have focused heavily on antibiotic stewardship and new drug development, vaccines represent a powerful yet underutilized tool for prevention. By reducing the incidence of bacterial infections, vaccines lower antibiotic consumption, interrupt transmission of resistant strains, and minimize the selective pressures that drive resistance. Unlike antibiotics, vaccines offer long-lasting protection, rarely induce resistance, and confer indirect protection through herd immunity. This review examines the global burden and drivers of AMR, highlights the unique advantages of vaccines over antibiotics in mitigating AMR, and surveys the current development pipeline of vaccines targeting key multidrug-resistant bacterial pathogens.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".