Antimicrobial resistance clusters in commensal Escherichia coli from livestock

Ayla Hesp*, Cajo ter Braak, Jeanet van der Goot, Kees Veldman, Gerdien van Schaik, Dik Mevius

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)


To combat antimicrobial resistance (AMR), policymakers need an overview of evolution and trends of AMR in relevant animal reservoirs, and livestock is monitored by susceptibility testing of sentinel organisms such as commensal E. coli. Such monitoring data are often vast and complex and generates a need for outcome indicators that summarize AMR for multiple antimicrobial classes. Model-based clustering is a data-driven approach that can help to objectively summarize AMR in animal reservoirs. In this study, a model-based cluster analysis was carried out on a dataset of minimum inhibitory concentrations (MIC), recoded to binary variables, for 10 antimicrobials of commensal E. coli isolates (N = 12,986) derived from four animal species (broilers, pigs, veal calves and dairy cows) in Dutch AMR monitoring, 2007–2018. This analysis revealed four clusters in commensal E. coli in livestock containing 201 unique resistance combinations. The prevalence of these combinations and clusters differs between animal species. Our results indicate that to monitor different animal populations, more than one indicator for multidrug resistance seems necessary. We show how these clusters summarize multidrug resistance and have potential as monitoring outcome indicators to benchmark and prioritize AMR problems in livestock.

Original languageEnglish
Pages (from-to)194-202
JournalZoonoses and Public Health
Issue number3
Early online dateJan 2021
Publication statusPublished - 2021


  • antimicrobial drug resistance
  • cluster analysis
  • E. coli
  • epidemiological monitoring
  • multidrug resistance
  • policy making


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