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Andersen VD, Møller FD, Jensen MS, Aarestrup FM, Vigre H. The quantitative effect of antimicrobial usage in Danish pig farms on the abundance of antimicrobial resistance genes in slaughter pigs. Prev Vet Med 2023; 214:105899. [PMID: 36940534 DOI: 10.1016/j.prevetmed.2023.105899] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 02/27/2023] [Accepted: 03/07/2023] [Indexed: 03/21/2023]
Abstract
Research has long established the connection between antimicrobial use (AMU) and antimicrobial resistance (AMR) in production animals, and shown that the ceasing of AMU reduces AMR. Our previous study of Danish slaughter-pig production found a quantitative relationship between lifetime AMU and abundance of antimicrobial resistance genes (ARGs). This study aimed to generate further quantitative knowledge on how changes in AMU in farms influence the abundance of ARGs both with immediate effect and over time. The study included 83 farms that were visited from 1 to 5 times. From each visit, a pooled faecal sample was produced. The abundance of ARGs was obtained by metagenomics. We used two-level linear mixed models for estimating the effect of AMU on the abundance of ARGs against six antimicrobial classes. The lifetime AMU of each batch was calculated from usage during their three rearing periods; as piglets, weaners and slaughter pigs (rearing pathway). AMU at farm level was estimated as the mean lifetime AMU of the sampled batches from each farm. At batch level, AMU was measured as the deviation between the batch-specific lifetime AMU and the general mean lifetime AMU at the farm. For peroral tetracycline and macrolide use there was a significant quantitative linear effect on the abundance of ARGs in batches within individual farms, indicating an immediate effect of changed AMU from batch to batch within farms. These estimated effects between batches within farms were approximately 1/2-1/3 of the effect estimated between farms. For all antimicrobial classes, the effect of the mean farm-level AMU and the abundance of ARGs present in the faeces of slaughter pigs was significant. This effect was identified only for peroral use, except for lincosamides, where the effect was for parenteral use. The results also indicated that the abundance of ARGs against a specific antimicrobial class also increased by the peroral usage of one or several other antimicrobial classes, except for ARGs against beta-lactams. These effects were generally lower than the AMU effect of the specific antimicrobial class. Overall, the farm peroral mean lifetime AMU affected the abundance of ARGs at antimicrobial class level and abundance of ARGs of other classes. However, the difference of AMU of the slaughter-pig batches affected only the abundance of ARGs at the same antimicrobial class level in the same antimicrobial class. The results do not exclude that parenteral usage of antimicrobials may have an effect on the abundance of ARGs.
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Affiliation(s)
- V D Andersen
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - F D Møller
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - M S Jensen
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - F M Aarestrup
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - H Vigre
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
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Bangsgaard EO, Andersen VD, Græsbøll K, Christiansen LE. The ALEX algorithm - estimating average lifetime antimicrobial exposure of danish slaughter pigs in a fast, automated and robust way. Prev Vet Med 2023; 212:105829. [PMID: 36623359 DOI: 10.1016/j.prevetmed.2022.105829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 12/27/2022]
Abstract
Calculating and estimating antimicrobial exposure at specific batch level is key to understanding consumption patterns of antimicrobials in the Danish pig sector. Understanding consumption and trading patterns can assist in developing treatment plans at national levels and might lead to reducing antimicrobial resistance levels. The ALEX algorithm is a fast, automated and robust algorithm developed to estimate the average lifetime antimicrobial exposure of Danish slaughter pigs. The algorithm estimates antimicrobial exposure in the different life stages of the pig (piglet, weaner and finisher) together with the type of production network (the number of farms within a network and ownership of these). We present the algorithm and give two examples of usage. Furthermore, we compare the ALEX algorithm with an acknowledged exposure estimation algorithm, and we present a sensitivity analysis.
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Affiliation(s)
- Elisabeth Ottesen Bangsgaard
- Department of Applied Mathematics and Computer Science, Technical University of Denmark Richard Petersens Plads, Bygning 324, Denmark.
| | | | - Kaare Græsbøll
- Department of Applied Mathematics and Computer Science, Technical University of Denmark Richard Petersens Plads, Bygning 324, Denmark.
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Bangsgaard EO, Græsbøll K, Andersen VD, Clasen J, Jasinskytė D, Hansen JE, Folkesson A, Christiansen LE. Mixed effect modeling of tetracycline resistance levels in Danish slaughter pigs. Prev Vet Med 2021; 191:105362. [PMID: 33895502 DOI: 10.1016/j.prevetmed.2021.105362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/10/2021] [Accepted: 04/12/2021] [Indexed: 11/24/2022]
Abstract
Mathematical and statistical modeling can be a very useful tool in understanding and fighting antimicrobial resistance (AMR). Here we present investigations of mixed effect models of varying complexity in order to identify and address possible management factors affecting the tetracycline AMR levels in Danish pig farms. Besides antimicrobial exposure during pigs life cycle, the type of production seems to also have an influence. The results concludes that not only fully integrated farms (CHR integrated) but also farms in a production network with a single ownership (CVR integrated) might have a preventive effect on levels of tetracycline AMR compared to more complex trading patterns.
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Affiliation(s)
| | - Kaare Græsbøll
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
| | | | - Julie Clasen
- Department of Bioengineering and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Džiuginta Jasinskytė
- Department of Bioengineering and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Julie Elvekjær Hansen
- Department of Bioengineering and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Anders Folkesson
- Department of Bioengineering and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Lasse Engbo Christiansen
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
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Andersen VD, Jensen MS, Munk P, Vigre H. Robustness in quantifying the abundance of antimicrobial resistance genes in pooled faeces samples from batches of slaughter pigs using metagenomics analysis. J Glob Antimicrob Resist 2021; 24:398-402. [PMID: 33626417 DOI: 10.1016/j.jgar.2021.02.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 01/15/2021] [Accepted: 02/03/2021] [Indexed: 10/22/2022] Open
Abstract
OBJECTIVES With the continued spread of antimicrobial resistance (AMR) in animals, it is important to assess its occurrence throughout a microbiome quantitatively in order to evaluate significantly affecting factors, e.g. antimicrobial usage. Metagenomics methods make it possible to measure the abundance of AMR genes in complex samples such as pooled faeces samples from batches of slaughter pigs. This study was performed to determine the random error in pooled samples from batches of pigs at slaughter and the measurement error from the metagenomics processes. METHODS In four farms, two pooled samples were obtained from a batch of slaughter pigs by two individual samplers, and each pooled sample was thereafter processed twice. Hierarchically clustered heatmaps were applied to evaluate dissimilarities between samples. The coefficient of variation was used to calculate the percentage difference between samples from the same farm. RESULTS Results of the analysis revealed that it was not possible to quantitatively separate the variation arising from sampling and metagenomics processes. They both contributed to the overall measurement error in batches of slaughter pigs. CONCLUSION Sampling of single pigs in 30 randomly selected pig pens within the farms provides a composition representative for frequently occurring AMR genes present within the farms, while rare genes were not dispersed in a similar manner. Aggregating the resistance abundance at gene family or antimicrobial class level will reduce the apparent variation originating from errors in sampling and metagenomics processing.
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Affiliation(s)
- Vibe Dalhoff Andersen
- The National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Kemitorvet, Kgs. Lyngby, Denmark.
| | - Marie Stengaard Jensen
- The National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Kemitorvet, Kgs. Lyngby, Denmark
| | - Patrick Munk
- The National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Kemitorvet, Kgs. Lyngby, Denmark
| | - Håkan Vigre
- The National Food Institute, Research Group for Genomic Epidemiology, Technical University of Denmark, Kemitorvet, Kgs. Lyngby, Denmark
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Sanders P, Vanderhaeghen W, Fertner M, Fuchs K, Obritzhauser W, Agunos A, Carson C, Borck Høg B, Dalhoff Andersen V, Chauvin C, Hémonic A, Käsbohrer A, Merle R, Alborali GL, Scali F, Stärk KDC, Muentener C, van Geijlswijk I, Broadfoot F, Pokludová L, Firth CL, Carmo LP, Manzanilla EG, Jensen L, Sjölund M, Pinto Ferreira J, Brown S, Heederik D, Dewulf J. Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes. Front Vet Sci 2020; 7:540. [PMID: 33195490 PMCID: PMC7475698 DOI: 10.3389/fvets.2020.00540] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 07/10/2020] [Indexed: 01/11/2023] Open
Abstract
The acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims.
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Affiliation(s)
- Pim Sanders
- The Netherlands Veterinary Medicines Institute (SDa), Utrecht, Netherlands
| | - Wannes Vanderhaeghen
- Centre of Expertise on Antimicrobial Consumption and Resistance in Animals (AMCRA), Brussels, Belgium
| | - Mette Fertner
- Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Klemens Fuchs
- Department for Data, Statistics and Risk Assessment, Austrian Agency for Health and Food Safety, Vienna, Austria
| | - Walter Obritzhauser
- Unit of Veterinary Public Health and Epidemiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria
| | - Agnes Agunos
- Public Health Agency of Canada, Guelph, ON, Canada
| | | | - Birgitte Borck Høg
- Division for Risk Assessment and Nutrition, National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - Vibe Dalhoff Andersen
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - Claire Chauvin
- Epidemiology, Health and Welfare Unit, French Agency for Food, Environmental and Occupational Health & Safety, Ploufragan, France
| | - Anne Hémonic
- IFIP-Institut du Porc, Domaine de la Motte au Vicomte, Le Rheu, France
| | - Annemarie Käsbohrer
- Unit of Veterinary Public Health and Epidemiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria.,Unit for Epidemiology, Zoonoses and Antimicrobial Resistance, Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Roswitha Merle
- Institute for Veterinary Epidemiology and Biostatistics, Freie Universität Berlin, Berlin, Germany
| | - Giovanni L Alborali
- Istituto Zooprofilattico Sperimentale della Lombardia e Dell'Emilia Romagna, Brescia, Italy
| | - Federico Scali
- Istituto Zooprofilattico Sperimentale della Lombardia e Dell'Emilia Romagna, Brescia, Italy
| | | | - Cedric Muentener
- Institute of Veterinary Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | | | | | - Lucie Pokludová
- Institute for State Control of Veterinary Biologicals and Medicines, Brno, Czechia
| | - Clair L Firth
- Unit of Veterinary Public Health and Epidemiology, Institute of Food Safety, Food Technology and Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria
| | - Luís P Carmo
- Vetsuisse Faculty, Veterinary Public Health Institute, University of Bern, Bern, Switzerland
| | - Edgar Garcia Manzanilla
- Moorepark Animal and Grassland Research Center, Teagasc, Irish Agriculture and Food Development Authority, Cork, Ireland.,School Veterinary Medicine, University College Dublin, Dublin, Ireland
| | - Laura Jensen
- Danish Veterinary and Food Administration, Glostrup, Denmark
| | - Marie Sjölund
- Department of Animal Health and Antimicrobial Strategies, National Veterinary Institute, Uppsala, Sweden
| | | | - Stacey Brown
- Veterinary Medicines Directorate, Addlestone, United Kingdom
| | - Dick Heederik
- The Netherlands Veterinary Medicines Institute (SDa), Utrecht, Netherlands
| | - Jeroen Dewulf
- Veterinary Epidemiology Unit, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
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Andersen VD, Aarestrup FM, Munk P, Jensen MS, de Knegt LV, Bortolaia V, Knudsen BE, Lukjancenko O, Birkegård AC, Vigre H. Predicting effects of changed antimicrobial usage on the abundance of antimicrobial resistance genes in finisher' gut microbiomes. Prev Vet Med 2019; 174:104853. [PMID: 31783288 DOI: 10.1016/j.prevetmed.2019.104853] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 11/18/2019] [Accepted: 11/18/2019] [Indexed: 11/30/2022]
Abstract
It is accepted that usage of antimicrobials (AMs) in food animals causes the emergence and spread of antimicrobial resistance (AMR) in this sector, while also contributing to the burden of AMR in humans. Curbing the increasing occurrence of AMR in food animals requires in-depth knowledge of the quantitative relationship between antimicrobial usage (AMU) and AMR to achieve desired resistance reductions from interventions targeting AMU. In the observational study, the relationships between lifetime AMU in 83 finisher batches from Danish farms and the AMR gene abundances of seven antimicrobial classes in their gut microbiomes were quantified using multi-variable linear regression models. These relationships and the national lifetime AMU in pigs were included in the predictive modelling that allowed for testing of scenarios with changed lifetime AMU for finishers produced in Denmark in 2014. A total of 50 farms from the observational study were included in validating the observational study and the predictive modelling. The results from the observational study showed that the relationship was linear, and that the parenteral usage of AMs had a high effect on specific AM-classes of resistance, whereas the peroral usage had a lower but broader effect on several classes. Three different scenarios of changed lifetime AMU were simulated in the predictive modelling. When all tetracycline usage ceased, the predicted interval reductions of aminoglycoside, lincosamide and tetracycline resistance were 4-42 %, 0-8 % and 9-18 %, respectively. When the peroral tetracycline usage of the 10 % highest users was replaced with peroral macrolide usage, the tetracycline resistance fell by 1-2 % and the macrolide and MLSb resistance increased by 5-8 %. When all extended-spectrum penicillin usage was replaced with parenteral lincosamide usage, the beta-lactam resistance fell by 2-7 %, but the lincosamide usage and resistance increased by 194 % and 10-45 %, respectively. The external validation provided results within the 95 % CI of the predictive modelling outcome at national level, while the external validation at farm level was less accurate. In conclusion, interventions targeting AMU will reduce AMR abundance, though differently depending on the targeted AM-class and provided the reduction of one AM-class usage is not replaced with usage of another AM-class. Predicting several classes of AMR gene abundance simultaneously will support stakeholders when deciding on interventions targeting AMU in the finisher production to avoid adverse and unforeseen effects on the AMR abundance. This study provides a sound predictive modelling framework for further development, including the dynamics of AMU on AMR in finishers at national level.
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Affiliation(s)
- V D Andersen
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - F M Aarestrup
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
| | - P Munk
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - M S Jensen
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - L V de Knegt
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - V Bortolaia
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - B E Knudsen
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - O Lukjancenko
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - A C Birkegård
- The National Veterinary Institute, Technical University of Denmark, Lyngby, Denmark
| | - H Vigre
- The National Food Institute, Technical University of Denmark, Lyngby, Denmark.
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7
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Birkegård AC, Andersen VD, Halasa T, Jensen VF, Toft N, Vigre H. Computional algorithm for lifetime exposure to antimicrobials in pigs using register data—The LEA algorithm. Prev Vet Med 2017; 146:173-180. [DOI: 10.1016/j.prevetmed.2017.08.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Revised: 08/07/2017] [Accepted: 08/10/2017] [Indexed: 10/19/2022]
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8
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Andersen VD, Hald T. Interventions Aimed at Reducing Antimicrobial Usage and Resistance in Production Animals in Denmark. NAM Perspect 2017. [DOI: 10.31478/201707h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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9
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Munk P, Andersen VD, de Knegt L, Jensen MS, Knudsen BE, Lukjancenko O, Mordhorst H, Clasen J, Agersø Y, Folkesson A, Pamp SJ, Vigre H, Aarestrup FM. A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds. J Antimicrob Chemother 2016; 72:385-392. [PMID: 28115502 DOI: 10.1093/jac/dkw415] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 08/28/2016] [Accepted: 08/31/2016] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVES Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring. METHODS We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing. RESULTS Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment. CONCLUSIONS We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.
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Affiliation(s)
- Patrick Munk
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Vibe Dalhoff Andersen
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Leonardo de Knegt
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Marie Stengaard Jensen
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Berith Elkær Knudsen
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Oksana Lukjancenko
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Hanne Mordhorst
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Julie Clasen
- Section for Bacteriology and Pathology, National Veterinary Institute, Technical University of Denmark, Bülowsvej 27, 1870 Frederiksberg C, Denmark
| | - Yvonne Agersø
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Anders Folkesson
- Section for Bacteriology and Pathology, National Veterinary Institute, Technical University of Denmark, Bülowsvej 27, 1870 Frederiksberg C, Denmark
| | - Sünje Johanna Pamp
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Håkan Vigre
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
| | - Frank Møller Aarestrup
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Søltofts Plads, Building 221, 2800 Kgs Lyngby, Denmark
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10
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Andersen VD, Jensen VF, Vigre H, Andreasen M, Agersø Y. The use of third and fourth generation cephalosporins affects the occurrence of extended-spectrum cephalosporinase-producing Escherichia coli in Danish pig herds. Vet J 2015; 204:345-50. [PMID: 25935558 DOI: 10.1016/j.tvjl.2015.03.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Revised: 03/12/2015] [Accepted: 03/13/2015] [Indexed: 10/23/2022]
Abstract
Extended-spectrum cephalosporinase resistance is currently the fastest emerging antimicrobial resistance problem worldwide; however, evidence documenting the effect of potential risk factors is limited. The main objective of this study was to investigate the effect of using third and fourth generation cephalosporins on the occurrence of extended-spectrum cephalosporinase-producing Escherichia coli (ESC-Ec) in Danish pig herds. Conventional, integrated, medium to large herds were selected based on information from the Danish Central Husbandry Register and two groups were formed based on the use of third and fourth generation cephalosporins within a specified period, namely, 20 herds with no cephalosporin use (non-exposed) and 19 herds with frequent use (exposed). Data on prescribed antimicrobials were obtained from the National database (VetStat). Management data were obtained through a questionnaire. At the herd level, three pooled faecal samples were collected from sows with their piglets (farrowing pens), weaners, and finishers. ESC-Ec were then identified using selective enrichment. Because several of the herds only had a low number of weaners and/or finishers, analysis was only performed on samples from the farrowing pens. Logistic regression showed a significant effect of using cephalosporins-III/IV on the occurrence of ESC-Ec in the farrowing pens, even when adjusted for use of other antimicrobials 1 year prior to sampling. No confounding effect was identified in relation to management data. The relative risk ESC-Ec in exposed compared to non-exposed was 4.7 (95% confidence interval 2.0-11.5), confirming that regular use of cephalosporins-III/IV was a significant risk factor for the occurrence of ESC-Ec.
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Affiliation(s)
- V D Andersen
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark.
| | - V F Jensen
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark
| | - H Vigre
- National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, DK-2860 Søborg, Denmark
| | - M Andreasen
- Danish Agriculture and Food Council, Pig Research Centre, Axeltorv 3, Copenhagen V, Denmark
| | - Y Agersø
- National Food Institute, Technical University of Denmark, Kemitorvet 204, DK-2800 Lyngby, Denmark
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Jensen VF, de Knegt LV, Andersen VD, Wingstrand A. Temporal relationship between decrease in antimicrobial prescription for Danish pigs and the "Yellow Card" legal intervention directed at reduction of antimicrobial use. Prev Vet Med 2014; 117:554-64. [PMID: 25263135 DOI: 10.1016/j.prevetmed.2014.08.006] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2014] [Revised: 08/10/2014] [Accepted: 08/11/2014] [Indexed: 11/19/2022]
Abstract
The potential effects of the "Yellow Card" intervention, enforced by Danish authorities in December 2010, on the antimicrobial prescription in the Danish pig production were investigated. Data on antimicrobial prescription for pigs during 2002-2012 was obtained from the national database on veterinary prescribed medicines, VetStat. Descriptive analysis of temporal trends in quantitative antimicrobial prescription for pigs on national level was performed for each administration route, age group and disease group. In addition, prescription patterns of the three most prescribed antimicrobial classes (tetracyclines, macrolides and pleuromutilins) for weaners and finishers were studied at herd level. A 25% decline in the total antimicrobial use per pig produced occurred between 2009 and 2011. A decline was observed both in sows and piglets (31%), weaners (34%) and finishers (19%). Reduced prescription of tetracycline, macrolides and pleuromutilins for oral use, mainly for gastrointestinal disease (GI) in weaners and finishers, explained 76% of the total reduction. In 2012, the overall antimicrobial use increased by 10%, as a partial reversal of the preceding changes in prescription pattern. On herd level, the decline and subsequent increase was mainly related to changes in number of herds receiving regular monthly prescriptions. This study demonstrated that the steep decrease in antimicrobial use in the Danish pig production was temporally related with the announcement and introduction of the Yellow Card intervention.
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Affiliation(s)
- V F Jensen
- Department of Epidemiology and Microbial Genomics, The National Food Institute, Technical University of Denmark, Mørkhøj Bygade 26, DK 2860 Søborg, Denmark.
| | - L V de Knegt
- Department of Epidemiology and Microbial Genomics, The National Food Institute, Technical University of Denmark, Mørkhøj Bygade 26, DK 2860 Søborg, Denmark
| | - V D Andersen
- Department of Epidemiology and Microbial Genomics, The National Food Institute, Technical University of Denmark, Mørkhøj Bygade 26, DK 2860 Søborg, Denmark
| | - A Wingstrand
- Department of Epidemiology and Microbial Genomics, The National Food Institute, Technical University of Denmark, Mørkhøj Bygade 26, DK 2860 Søborg, Denmark
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