The role of gender in antimicrobial resistance: Findings from a scoping review
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is a growing global health threat requiring a strong focus on equity. This scoping review aimed to document the evidence to outline recommendations for gender-responsive AMR policies, programmes, and interventions aligned with the World Health Organization’s People-centered approach to addressing AMR in the human health sector. We collected academic and grey literature published in English between 2000 and 2025 resulting in 141 records included for data extraction. Data was mapped onto a Gender and AMR Matrix and thematically analysed. Our findings suggest that restrictive gender norms create gender inequities in AMR vulnerability, exposure and outcomes because of the gendered distribution of labour and roles, access to resources, and inequitable decision-making and power structures. Harmful gender norms and values not only influence access to quality healthcare but are also foundational to other gender domains such as the distribution of labour and roles, and decision-making power that ultimately impact the risk of infection and access to treatment and diagnosis. These findings underscore the complex interplay between gender dynamics and AMR outcomes and highlight the need for AMR policies that recognise gender inequities and address related systemic barriers to equitable access to the prevention, diagnosis and treatment of drug-resistant infections.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".