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<p>Despite progress in antimicrobial resistance (AMR) surveillance, migrants and ethnic minorities, who bear disproportionate AMR burdens, remain underrepresented in programmes. Digital health is common, but we found no interventions using large language models (LLMs) to reduce AMR in these communities. In three workshops, we identified priorities: culturally and linguistically inclusive design; context specific knowledge from community settings; and trust building via community health workers, with data protection and bias mitigation.</p>

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Perspective: large language models and antimicrobial resistance among migrants: an equity imperative

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月14日

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  • Ji Soo Choi,
  • Daniel Pan,
  • Anthony O’Hare,
  • Catrin E. Moore,
  • Fouad Fouad,
  • Manish Pareek,
  • Bethan V. Purse,
  • Dom Brass,
  • Timothy Rawson,
  • Laura B. Nellums,
  • Susanne Lynch,
  • Gill Damont,
  • Greg Barton,
  • Lu Lu,
  • Sophie Jung,
  • Amani Al-Oraibi,
  • Daniel Pan,
  • Ji Soo Choi,
  • Mi Joo Choi,
  • Carolyn Tarrant,
  • Manish Pareek,
  • Katherine Stott,
  • Neil Henney,
  • Rachel Mullen,
  • Suzanne Cutler,
  • Andrew Hoyle,
  • Gavin Abernethy,
  • Simon Powers,
  • Mina Mohaghegh

摘要

Despite progress in antimicrobial resistance (AMR) surveillance, migrants and ethnic minorities, who bear disproportionate AMR burdens, remain underrepresented in programmes. Digital health is common, but we found no interventions using large language models (LLMs) to reduce AMR in these communities. In three workshops, we identified priorities: culturally and linguistically inclusive design; context specific knowledge from community settings; and trust building via community health workers, with data protection and bias mitigation.