|Title||Monitoring antimicrobial resistance trends in commensal Escherichia coli from livestock, the Netherlands, 1998 to 2016|
|Author(s)||Hesp, Ayla; Veldman, Kees; Goot, Jeanet van der; Mevius, Dik; Schaik, G. van|
|Source||Eurosurveillance 24 (2019)25. - ISSN 1025-496X|
Bacteriology & Epidemiology
Diagnostics & Crisis Organization
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||AMR - antimicrobial resistance - Escherichia coli - monitoring - quantitative - surveillance - trend analysis|
BackgroundMonitoring 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.AimsTo quantify and evaluate trends in AMR in commensal Escherichia coli, using data from the Dutch national AMR monitoring programme in livestock (1998-2016).MethodsFaecal 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.ResultsResistant 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, antimicrobial-specific trends were similar.ConclusionsUsing 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 is useful to quantify trends and detect trend changes in AMR. This model is applicable to similar data from other European countries.