Antimicrobial resistance burden in India and Germany in 2022: A systematic analysis along with One Health perspective
Bibliographic record
Abstract
Globally increasing antibiotic resistance has been linked to the extensive use of antibiotics in medical, veterinary, and agricultural Practices. This study aims to investigate the correlations of antimicrobial-resistant of various pathogens in three compartments: humans, animals and the environment in India and Germany. A systematic search was carried out in Medline via PubMed, Google Scholar, and science direct, including studies published in 2022. Out of 532 papers, 24 were considered for meta-analysis. Our findings reveals that in India, β-lactam is highly resistant in animals. Quinolone, on the other hand, was highly resistant in humans. In the environmental sectors, aminoglycosides and β-lactams is resistant. While in Germany, β-lactam resistance is high across all three sectors. However, E. coli was the most frequent and resistant pathogen in both countries, with significant resistance to β-lactams and cephalosporins across all compartments. These results underscore the critical need for monitoring antibiotic resistance patterns and developing targeted antibiotic regimens. A One Health-based intervention strategy is essential to mitigate the spread of AMR and improve health outcomes globally.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".