Monitoring Antimicrobial Resistance and Drug Usage in the Human and Livestock Sector and Foodborne Antimicrobial Resistance in Six European Countries

Abstract

Introduction

Antimicrobial resistance (AMR), associated with antimicrobial use (AMU), is a major public concern. Surveillance and monitoring systems are essential to assess and control the trends in AMU and AMR. However, differences in the surveillance and monitoring systems between countries and sectors make comparisons challenging. The purpose of this article is to describe all surveillance and monitoring systems for AMU and AMR in the human and livestock sectors, as well as national surveillance and monitoring systems for AMR in food, in six European countries (Spain, Germany, France, the Netherlands, the United Kingdom and Norway) as a baseline for developing suggestions to overcome current limitations in comparing AMU and AMR data.

Methods

A literature search in 2018 was performed to identify relevant peer-reviewed articles and national and European grey reports as well as AMU/AMR databases.

Results

Comparison of AMU and AMR systems across the six countries showed a lack of standardization and harmonization with different AMU data sources (prescription vs sales data) and units of AMU and AMR being used. The AMR data varied by sample type (clinical/non-clinical), laboratory method (disk diffusion, microdilution, and VITEK, among others), data type, ie quantitative (minimum inhibition concentration (MIC) in mg/L/inhibition zone (IZ) in mm) vs qualitative data (susceptible-intermediate-resistant (SIR)), the standards used (EUCAST/CLSI among others), and/or the evaluation criteria adopted (epidemiological or clinical).

Discussion

A One Health approach for AMU and AMR requires harmonization in various aspects between human, animal and food systems at national and international levels. Additionally, some overlap between systems of AMU and AMR has been encountered. Efforts should be made to improve standardization and harmonization and allow more meaningful analyses of AMR and AMU surveillance data under a One Health approach.

Keywords:

• AMR
• AMU
• food-producing animals
• harmonization
• monitoring
• surveillance

Acknowledgments

This work was carried out within the framework of the ARDIG project, the European Joint Programme (EJP) on AMU and AMR in humans, food and animals. ARDIG project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 773830.

We thank Mike Brouwer, Jean-Yves Madec, Philippe Glaser, Ines Noll, Karin Gröschner, Alexandra Hoffmann, Robby Markwart (RKI) for their input and collaboration.

Abbreviations

AACTING, Network on quantification of veterinary Antimicrobial usage at herd level and Analysis, CommunicaTion and benchmarkING to improve responsible usage; ADKA, Federal Association of German Hospital Pharmacists; AECOSAN, Spanish Agency for Consumer Affairs, Food Safety and Nutrition; AEMPS, Spanish Agency of Medicaments and Sanitary Products; AHDB, Agriculture and Horticulture Development Board; AMR, Antimicrobial Resistance; AMU, Antimicrobial Use; ANMV, National Agency for Veterinary Medicines; ANSES, French Agency for Food, Environmental and Occupational Health & Safety; ANSM, French National Agency for Medicine and Health Products Safety; APHA, Animal and Plant Health Agency; ARDIG, Antibiotic Resistance Dynamics: the influence of geographic origin and management systems on resistance gene flows within humans, animals and the environment; ARMIN, Antibiotic Resistance Monitoring in Lower Saxony; ARS, Antibiotics Resistance Surveillance; AST, Antibiotic Susceptibility Testing; ATB RAISIN, Antibiotic Consumption Monitoring programme; AVS, Antibiotic Consumption Surveillance; BDCAP, Primary Care Clinical Database; BfR, Federal Institute for Risk Assessment; BEIC, British Egg Industry Council; BIFAP, Database for Pharmacoepidemiological Research in Primary Care; BPC, British Poultry Council Stewardship; BSAC, British Society for Antimicrobial Chemotherapy; BVL, Federal Office of Consumer Protection and Food Safety; CAESAR, Central Asian and Eastern European Surveillance of Antimicrobial Resistance network; CA-SFM, Antibiogram Committee of the French Society for Microbiology; CBP, Clinical Breakpoints; CCLIN, Nosocomial Infection Surveillance Coordination Centers in France; CEESA, European Animal Health Study Center; CLSI, Clinical Laboratory Standard Institute; CPIAS, National Network for the Prevention of Care-Related Infections; DARC, Defra Antibiotic Resistance Coordination; DART, German antibiotic resistance strategy; DCD, Defined Course Dose; DDD, Defined Daily Dose; DGI, German Society for Infectious Diseases; DIMDI, German Institute for Medical Documentation and Information; DIN, German Institute for Standardization; EARS-Net, European Antimicrobial Resistance Surveillance Network; EASSA, European Antimicrobial Susceptibility Surveillance in Animals; ECDC, European Center for Disease Prevention and Control; ECOFF, Epidemiological Cut-Off; EFFORT, Ecology from Farm to Fork Of microbial drug Resistance and Transmission; ECOSS, Electronic Communication of Surveillance in Scotland; EFSA, European Food Safety Authority; EJP, European Joint Programme; EMA, European Medicines Agency; eMB cattle and sheep, Cattle and sheep Electronic Medicine Book; eMB pigs, Pig Electronic Medicine Book; EPPM, Permanent Sample of Medical Prescription; ESAC-Net, European Surveillance of Antimicrobial Consumption Network; ESPAUR, English Surveillance Programme for Antimicrobial Utilisation and Resistance; ESVAC, European Surveillance of Veterinary Antimicrobial Consumption; EU, European Union; EUCAST, European Committee on Antimicrobial Susceptibility Testing; FIDIN, Federation of the Dutch veterinary pharmaceutical industry; GAP, Global Action Plan; GERMAP, Antibiotic Consumption and the Spread of Antibiotic Resistance in Human and Veterinary Medicine in Germany; GERM-VET, German Veterinary Monitoring System; GP, General Practice; HIT, German animal movement and information system; IBEI-TIHO, Institute for Biometry, Epidemiology and Information Processing of the Hanover University of Veterinary Medicine Foundation; IDELE, French Livestock Institute; IFIP, Swine Industry’s French Technical Institute; INAPORC, French Pork Interprofessional Organisation; IQVIA, Human Data Science Company; ISCIII, Carlos III Health Institute; ISD, Information Service Division; ISIS-AR, Infectious Disease Surveillance Information System on Antibiotic Resistance; IZ, Inhibition Zone; JIACRA, Joint Interagency Antimicrobial Consumption and Resistance Analysis; KISS, Hospital Infection Surveillance System; MABUSE, Medical Antimicrobial Use Surveillance and Evaluation; MAPAMA, Ministry of Agriculture, Fisheries and Food; MARAN, Monitoring of Antimicrobial Resistance and Antibiotic Usage in Animals in the Netherlands; Medirund, Central Database for the Mandatory Registration of Antibiotics in Cattle in Netherlands; MIC, Minimum Inhibitory Concentration; MS, Member State; MSIS, Norwegian Surveillance System for Communicable Diseases; NethMap, Consumption of Antimicrobial Agents and Antimicrobial Resistance Among Medically Important Bacteria in the Netherlands; NFSA, Norwegian Food Safety Authority; NHS, National Health Service; NIPH, Norwegian Institute of Public Health; NOIS, Norwegian Surveillance System for Antibiotic Consumption and Healthcare-Associated Infections; NORM, surveillance programme for antimicrobial resistance in human pathogens; NORM-VET, Monitoring Programme for Antimicrobial Resistance in the Veterinary and Food Production sectors; NorPD, Norwegian Prescription Database; NSS, National System Scotland; NVI, Norwegian Veterinary Institute; NVMM, Ministry of Health, Welfare and Sport and the Dutch Society of Medical Microbiology; NVWA, Netherlands Food and Consumer Product Safety Authority; ONERBA, National Observatory of the Epidemiology of Bacterial Antibiotic Resistance; P&CFS, Practitioner and Counter Fraud Services; PEG, Paul Ehrlich Society for Chemotherapy; PHE, Public Health England; PHW, Public Health Wales; PIS, Prescribing Information System; PRAN, National Antibiotic Resistance Plan; PSU, Prescribing Services Unit; QS, Quality and Safety GmbH; RAISIN, Alert, Investigation and Surveillance of Nosocomial Infection Network; RDD, Recommended Daily Dose; RESAPATH, French Surveillance Network for Antimicrobial Resistance in Pathogenic Bacteria of Animal Origin; RIVM, National Institute for Public Health and the Environment; RKI, Robert Koch Institute; SARI, Surveillance of Antimicrobial Use and Bacterial Resistance in Intensive Care Units; SPF, French Health System; SDa, Netherlands Veterinary Medicines Institute; SGSS, Second Generation Surveillance System; SHI, Statutory Health Insurance; SIR, Sensible, Intermediate, Resistant; SNDS, French National Health Data System; SNIIRAM, French National Health Data System; SNIV, National sentinel surveillance network for infectious diseases in nursing homes; SONAAR, Scottish One Health Antimicrobial Use and Antimicrobial Resistance; SRUC, Scotland’s Rural College Veterinary Services and Capital Diagnostics; STAR-PU, Specific Therapeutic Group Age-sex weightings Related Prescribing Units; SWAB, Dutch Foundation of the Working Party on Antibiotic Policy; UK, United Kingdom; UK-VARSS, UK-Veterinary Antibiotic Resistance and Sales Surveillance; VAV, Spanish Veterinary Antimicrobial Resistance Surveillance Network; VetCab, Sentinel project Veterinary Consumption of Antibiotics; VetReg, Veterinary Prescription Register; VMD, Veterinary Medicines Directorate; WHO, World Health Organization; WIdO, Scientific Institute of the AOK; ZOMO, German Zoonosis Monitoring.

Disclosure

The authors declare grants from European Union’s Horizon 2020 research and innovation programme during the conduct of the study. The authors report no other possible conflicts of interest in this work.