Interconnections between the food system and antimicrobial resistance: A systems-informed umbrella review from a One Health perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Human food systems are a major driver of antimicrobial resistance (AMR), with significant implications for human, animal, and ecosystem health. While recent research frames AMR as an emerging property of a complex system, this perspective has not been systematically applied to the existing evidence. This review aims to synthesise the evidence on AMR and the food system from a complex systems perspective, highlighting the interconnections between factors that contribute to AMR emergence and spread. Materials and methods: An umbrella review methodology was used to identify relevant studies. We searched Medline, SCOPUS, Agricola, and Dimensions using terms related to AMR and the food system. Systematic reviews at this intersection containing evidence of at least one relationship between two variables were included. Data were extracted and summarised according to umbrella review guidelines, and a causal loop diagram (CLD) was developed to map the interrelationships between food system factors and AMR. Results: Our synthesis incorporated evidence from 80 studies, highlighting how AMR emergence and spread within food systems is driven by a complex interplay of factors across human, animal, and environmental reservoirs (e.g., water, soil), with impacts for disease burden in humans, animals and crops and financial viability of farming. The tensions driving antimicrobial use (AMU) in livestock, a key driver of AMR, were underlined, with trade-offs between disease treatment, animal welfare, and economic outcomes. Feedback loops between humans, animals, and the environment were identified, with antimicrobials and AMR spreading between multiple reservoirs. Conclusions: This review underscores the need for a One Health approach to AMR mitigation, given the interconnections between human, animal, and ecosystem health. Findings highlight the trade-offs in AMU and the economic incentives that may conflict with global antimicrobial stewardship. Further research may empirically explore connections to upstream factors, such as consumer preferences and environmental determinants.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it