Building the European Antimicrobial Resistance Surveillance network in veterinary medicine (EARS-Vet)

Mader, Rodolphe; Damborg, Peter; Amat, Jean-Philippe; Bengtsson, Björn; Bourély, Clémence; Broens, Els M.; Busani, Luca; Crespo-Robledo, Paloma; Filippitzi, Maria-Eleni; Fitzgerald, William; Kaspar, Heike; Madero, Cristina Muñoz; Norström, Madelaine; Nykäsenoja, Suvi; Pedersen, Karl; Pokludová, Lucie; Urdahl, Anne Margrete; Vatopoulos, Alkiviadis; Zafeiridis, Christos; Madec, Jean‐Yves

doi:10.2807/1560-7917.es.2021.26.4.2001359

Cited by 59 publications

(63 citation statements)

References 5 publications

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“…Therefore, national surveillance programs are urgently required. To date, there are several international surveillance networks, such as the Global Antimicrobial Resistance and Use Surveillance System (GLASS), the European Antimicrobial Resistance Surveillance Network (EARS-Net), the China Antimicrobial Resistance Surveillance System (CARSS), and the China Antimicrobial Surveillance Network (CHINET) ( 8 – 10 ). However, these networks mainly focus on AMR surveillance in adult populations, instead of addressing that in children.…”

Section: Introductionmentioning

confidence: 99%

Bacterial Epidemiology and Antimicrobial Resistance Profiles in Children Reported by the ISPED Program in China, 2016 to 2020

Jing

et al. 2021

Microbiol Spectr

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AMR, especially that involving multidrug-resistant organisms (MDROs), is recognized as a global threat to human health; AMR renders infections increasingly difficult to treat, constituting an enormous economic burden and producing tremendous negative impacts on patient morbidity and mortality rates. There are many surveillance programs in the world to address AMR profiles and MDRO prevalence in humans.

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Section: Introductionmentioning

confidence: 99%

Bacterial Epidemiology and Antimicrobial Resistance Profiles in Children Reported by the ISPED Program in China, 2016 to 2020

Jing

et al. 2021

Microbiol Spectr

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“…While the European Food Safety Authority (EFSA) collects data on non-clinical isolates on the European level, limited data on clinical isolates from diagnostic submissions from livestock are collected in Europe. Currently, only the VetPath and MycoPath initiatives funded by the pharmaceutical sector in Europe publish such data [16][17][18], although there is a call to launch the European Antimicrobial Resistance Surveillance network in veterinary medicine [19].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Phenotypical Antimicrobial Resistance between Clinical and Non-Clinical E. coli Isolates from Broilers, Turkeys and Calves in Four European Countries

et al. 2021

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Livestock data on antimicrobial resistance (AMR) are commonly collected from bacterial populations of clinical and non-clinical isolates. In contrast to data on non-clinical isolates from livestock, data on clinical isolates are not harmonized in Europe. The Normalized Resistance Interpretation (NRI) method was applied to overcome the lack of harmonization of laboratory methods and interpretation rules between monitoring systems. Statistical analyses were performed to identify associations between the isolate type (clinical vs. non-clinical) and resistance to four antimicrobials (ampicillin, tetracycline, gentamicin, and nalidixic acid) per animal category in Germany and France. Additional statistical analyses comparing clinical and non-clinical isolates were performed with the available data on the same antimicrobial panel and animal categories from the UK and Norway. Higher resistance prevalence was found in clinical isolates compared to non-clinical isolates from calves to all antimicrobials included in Germany and France. It was also found for gentamicin in broilers from France. In contrast, in broilers and turkeys from Germany and France and in broilers from the UK, a higher resistance level to ampicillin and tetracycline in non-clinical isolates was encountered. This was also found in resistance to gentamicin in isolates from turkeys in Germany. Resistance differed within countries and across years, which was partially in line with differences in antimicrobial use patterns. Differences in AMR between clinical and non-clinical isolates of Escherichia coli are associated with animal category (broiler, calf, and turkey) and specific antimicrobials. The NRI method allowed comparing results of non-harmonized AMR systems and might be useful until international harmonization is achieved.

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“…We also consulted the EARS‐Vet Network (Mader et al., 2021 ) members, and data from the FINRES reports were shared with us.…”

Section: Appendix a – Additional Mic Data Sources Consideredmentioning

confidence: 99%

Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 1: Methodology, general data gaps and uncertainties

Koutsoumanis¹,

Allende²,

Álvarez‐Ordóñez³

et al. 2021

EFS2

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The European Commission requested EFSA to assess, in collaboration with EMA, the specific concentrations of antimicrobials resulting from cross-contamination in non-target feed for foodproducing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in microbial agents relevant for human and animal health, as well as the levels of the antimicrobials which could have a growth promotion/increase yield effect. The assessment was performed for 24 antimicrobial active substances, as specified in the mandate. This scientific opinion describes the methodology used, and the main associated data gaps and uncertainties. To estimate the antimicrobial levels in the non-target feed that would not result in emergence of, and/or selection for, resistance, a model was developed. This 'Feed Antimicrobial Resistance Selection Concentration' (FARSC) model is based on the minimal selective concentration (MSC), or the predicted MSC (PMSC) if MSC for the most susceptible bacterial species is unavailable, the fraction of antimicrobial dose available for exposure to microorganisms in the large intestine or rumen (considering pharmacokinetic parameters), the daily faecal output or rumen volume and the daily feed intake. Currently, lack of data prevents the establishment of PMSC and/or FARSC for several antimicrobials and animal species. To address growth promotion, data from an extensive literature search were used. Specific assessments of the different substances grouped by antimicrobial classes are addressed in separate scientific opinions. General conclusions and recommendations were made.

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Building the European Antimicrobial Resistance Surveillance network in veterinary medicine (EARS-Vet)

Cited by 59 publications

References 5 publications

Bacterial Epidemiology and Antimicrobial Resistance Profiles in Children Reported by the ISPED Program in China, 2016 to 2020

Bacterial Epidemiology and Antimicrobial Resistance Profiles in Children Reported by the ISPED Program in China, 2016 to 2020

Comparison of Phenotypical Antimicrobial Resistance between Clinical and Non-Clinical E. coli Isolates from Broilers, Turkeys and Calves in Four European Countries

Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 1: Methodology, general data gaps and uncertainties

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