Abstract
Antimicrobial resistance (AMR) is a growing global health concern that spans human, animal, and environmental health, making it a quintessential One Health issue. Global AMR surveillance systems such as the World Health Organisation’s (WHO) Global Antimicrobial Resistance and Use Surveillance System (GLASS) have created important opportunities for countries to collect and
report AMR data systematically across sectors and settings. These systems also include the capacity to capture variables such as sex, age, and infection origin (community-acquired or healthcare-associated). This can facilitate the use of equity indicators and provide a foundation for more inclusive and responsive AMR analysis. This commentary highlights the value of building on these existing systems by expanding the routine collection and analysis of both basic and advanced equity-related variables and indicators using the human health sector as an entry point. Incorporating variables such as location of residence, education level, occupation, socio-economic status, disability, and ethnicity enables an intersectional analysis. This can enhance understanding of who is most affected by AMR and why, and inform effective responses. Recognising that AMR surveillance data often comes from health facilities, we also explore the benefits of complementing it with community-level and community-led approaches to better reflect diverse realities and patterns of AMR across populations and contexts. By integrating equity considerations into AMR
data systems, countries and global stakeholders can strengthen the design, implementation, and targeting of interventions. These steps support more responsive health systems and contribute to AMR solutions that are not only scientifically sound but also socially inclusive. Embedding equity in AMR surveillance is a vital step toward achieving the full promise of One Health – ensuring that responses are informed, effective, and reflective of the diverse communities they are meant to serve.
report AMR data systematically across sectors and settings. These systems also include the capacity to capture variables such as sex, age, and infection origin (community-acquired or healthcare-associated). This can facilitate the use of equity indicators and provide a foundation for more inclusive and responsive AMR analysis. This commentary highlights the value of building on these existing systems by expanding the routine collection and analysis of both basic and advanced equity-related variables and indicators using the human health sector as an entry point. Incorporating variables such as location of residence, education level, occupation, socio-economic status, disability, and ethnicity enables an intersectional analysis. This can enhance understanding of who is most affected by AMR and why, and inform effective responses. Recognising that AMR surveillance data often comes from health facilities, we also explore the benefits of complementing it with community-level and community-led approaches to better reflect diverse realities and patterns of AMR across populations and contexts. By integrating equity considerations into AMR
data systems, countries and global stakeholders can strengthen the design, implementation, and targeting of interventions. These steps support more responsive health systems and contribute to AMR solutions that are not only scientifically sound but also socially inclusive. Embedding equity in AMR surveillance is a vital step toward achieving the full promise of One Health – ensuring that responses are informed, effective, and reflective of the diverse communities they are meant to serve.
| Original language | English |
|---|---|
| Article number | 0026 |
| Journal | CABI Agriculture and Bioscience |
| Volume | 4 |
| Issue number | 1 |
| DOIs |
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| Publication status | Published - 30 Sept 2025 |
