Animal sources of antimicrobial-resistant bacterial infections in humans: a systematic review

Christina Fastl*, Helena C. De Carvalho Ferreira, Sara Babo Martins, João Sucena Afonso, Carlotta di Bari, Narmada Venkateswaran, Sara Monteiro Pires, Lapo Mughini-Gras, Ben Huntington, Jonathan Rushton, David Pigott, Brecht Devleesschauwer

*Corresponding author for this work

Research output: Contribution to journalReviewpeer-review

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Bacterial antimicrobial resistance (AMR) is among the leading global health challenges of the century. Animals and their products are known contributors to the human AMR burden, but the extent of this contribution is not clear. This systematic literature review aimed to identify studies investigating the direct impact of animal sources, defined as livestock, aquaculture, pets, and animal-based food, on human AMR. We searched four scientific databases and identified 31 relevant publications, including 12 risk assessments, 16 source attribution studies, and three other studies. Most studies were published between 2012 and 2022, and most came from Europe and North America, but we also identified five articles from South and South-East Asia. The studies differed in their methodologies, conceptual approaches (bottom-up, top-down, and complex), definitions of the AMR hazard and outcome, the number and type of sources they addressed, and the outcome measures they reported. The most frequently addressed animal source was chicken, followed by cattle and pigs. Most studies investigated bacteria-resistance combinations. Overall, studies on the direct contribution of animal sources of AMR are rare but increasing. More recent publications tailor their methodologies increasingly towards the AMR hazard as a whole, providing grounds for future research to build on.
Original languageEnglish
Article numbere143
JournalEpidemiology and Infection
Number of pages13
Publication statusPublished - 2023


  • Antibiotic resistance
  • Antimicrobial resistance
  • Human(s)
  • Infectious disease
  • Risk assessment
  • Source attribution


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