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Monitoring antimicrobial resistance trends in commensal escherichia coli from livestock, the Netherlands, 1998 to 2016

  • Ayla Hesp*
  • , Kees Veldman
  • , Jeanet van der Goot
  • , Dik Mevius
  • , Gerdien van Schaik
  • *Corresponding author for this work
    • Wageningen University & Research
    • Utrecht University

    Research output: Contribution to journal › Article › Academic › peer-review

    Abstract

    Background: Monitoring of antimicrobial resistance (AMR) in animals is essential for public health surveillance. To enhance interpretation of monitoring data, evaluation and optimisation of AMR trend analysis is needed. Aims: To quantify and evaluate trends in AMR in commensal Escherichia coli, using data from the Dutch national AMR monitoring programme in livestock (1998-2016). Methods: Faecal samples were collected at slaughter from broilers, pigs and veal calves. Minimum inhibitory concentration values were obtained by broth microdilution for E. coli for 15 antimicrobials of eight antimicrobial classes. A Poisson regression model was applied to resistant isolate counts, with explanatory variables representing time before and after 2009 (reference year); for veal calves, sampling changed from 2012 represented by an extra explanatory variable. Results: Resistant counts increased significantly from 1998-2009 in broilers and pigs, except for tetracyclines and sulfamethoxazole in broilers and chloramphenicol and aminoglycosides in pigs. Since 2009, resistant counts decreased for all antimicrobials in broilers and for all but the phenicols in pigs. In veal calves, for most antimicrobials no significant decrease in resistant counts could be determined for 2009-16, except for sulfamethoxazole and nalidixic acid. Within animal species, antimicrobialspecific trends were similar. Conclusions: Using Dutch monitoring data from 1998-2016, this study quantified AMR trends in broilers and slaughter pigs and showed significant trend changes in the reference year 2009. We showed that monitoring in commensal E. coli isuseful to quantify trends and detect trend changes in AMR. This model is applicable to similar data from other European countries.

    Original languageEnglish
    Article number1800438
    Number of pages13
    JournalEurosurveillance
    Volume24
    Issue number25
    DOIs
    Publication statusPublished - 20 Jun 2019

    Funding

    Funding statement: This research was supported by the Ministry of Agriculture, Nature and Food Quality (WOT-01-001-003) and Wageningen Bioveterinary Research.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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