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Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
Published on: July 19, 2024
Interventions to address antimicrobial resistance in migrants: a systematic review
Lucy Lammie1, Amelia Williams-Walker1, Laura B Nellums2
1Institute of Infection and Immunity, St George's School of Health and Medical Sciences, City St George's University, London, UK.
Background:
Antimicrobial resistance (AMR) is a major global health threat that disproportionately affects structurally marginalized groups, including migrants. Yet migrants are largely absent from AMR surveillance systems and response strategies, creating health inequities and undermining global containment efforts. This systematic review examines the evidence base for interventions targeting AMR in migrant populations, with three objectives to summarize existing research; to identify gaps in data collection, intervention design and outcome measurement; and to propose a path towards more equitable, migrant-inclusive AMR responses.
Methods:
We systematically searched MEDLINE, Embase and PubMed (January 2000-December 2025), following PRISMA guidelines using terms related to migration, AMR and interventions. Tuberculosis studies were excluded and we prioritized interventions addressing WHO Critical and High-Priority pathogens.
Results:
Of 4039 records screened, only four studies met inclusion criteria, therefore we performed a narrative synthesis.
Discussion:
Across these studies we identified three persistent gaps: (i) surveillance and monitoring rarely stratified data by migration status, ethnicity or country of origin; (ii) interventions were almost exclusively hospital-based, with little attention to community settings or care pathways; and (iii) outcome measurement was limited, with a narrow focus on microbiological endpoints and few robust clinical or equity-sensitive outcomes. Current evidence on AMR interventions for migrants is scarce, fragmented and insufficient to guide policy. Future work should prioritize high-quality, disaggregated surveillance data, contextually appropriate study designs and community-based care models, enabling rigorous, equity-driven evaluation of interventions.
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