Mapping the patterns and drivers of antibiotic use and environmental resistance in the Argentine beef industry.
Lead Research Organisation:
University of Liverpool
Department Name: Epidemiology and Population Health
Abstract
This project will build upon preliminary work conducted by Argentine and UK partners which has already identified the presence of AMR in beef feedlots and generated the first large-scale dataset of beef farm antibiotic usage data (334 farms) anywhere in the world. It will also build upon a small existing grant of £7,700 from UK ODA seed fund to help UoL academics develop a 'UK-Argentine Beef Antibiotic Research Network' which will be used to collect and analysis samples to optimize qPCR gene selection for environmental AMR quantification in beef farms, planned for Jan-June 2019. This preliminary work provides a very robust starting point for this project.
The project will use veterinary and epidemiology expertise and experience in quantifying antibiotic usage and agri-health economics expertise in mapping food value chains to build a theoretical antibiotic surveillance framework. This framework will be assessed against the available sources of information in other LMIC's to test its transferability especially in less well developed livestock systems including Kenya and Ethiopia, through existing projects which the UK the collaborators are engaged in (HORN project).
The system would integrate all the available information on antibiotic prescribing and antibiotic usage along with the farm management practices across the whole range of beef farming systems in Argentina. We will then categorize antibiotic use at farm level recruiting between 200 - 1000 farms from an existing representative network of 4500 farms (organized via SENASA) into different management system types (eg. breeding, growing, feedlot finishing) and correlate the management practices used in these farms with their patterns of antibiotic usage by using the surveillance framework. The environmental AMR population load and diversity will be assessed in a stratified random sub-sample of (n = 50) of the farms according to management system type and AMU level & usage practices. Multi-level modelling, cluster and principal component analysis will be used to quantify the agreement between the classification of farms based upon the AMU surveillance framework and the microbiological results to validate the efficacy of this means of risk assessment.
Deeper molecular analysis will be conducted on samples from farms with evidence of the most significant AMR diversity and load relating to High Priority Critically important antibiotics. This will include whole genome metagenomics and culture based antibiotic phenotype sensitivity to understand the population structure of the resistance profile of the most significant AMR environments.
This phase of the project will allow us to use risk factor analysis to identify critical control points in the mode of antibiotic use in beef farms. This will be achieved by linking the molecular epidemiology data to detailed quantitative and qualitative interviews with farmers to understand the drivers of antibiotic use.
The final phase of the project will co-develop practical AMR reduction interventions and policy advice of regulatory authorities. All the interventions recommended will be based up the risk factor analysis and their economic impact tested by cost - effectiveness analysis to identify in a clear a reproducible manner the most appropriate control measures for each farm management system. The qualitative interviews conducted with each farmer in the study will inform decision making on barriers to adoption of individual measures and feed into the co-development of policy advice to the beef industry. The collaboration provides the exciting opportunity to compare and contrast approaches in the UK and Argentina to maximizing farmer adoption of new practices and advice.
The project would employ two post-doctoral researchers (PDRAs) directly through the UoL. Whilst these two PDRA's will be employed by UoL they will be supervised jointly by UK and Argentine partner senior academics.
The project will use veterinary and epidemiology expertise and experience in quantifying antibiotic usage and agri-health economics expertise in mapping food value chains to build a theoretical antibiotic surveillance framework. This framework will be assessed against the available sources of information in other LMIC's to test its transferability especially in less well developed livestock systems including Kenya and Ethiopia, through existing projects which the UK the collaborators are engaged in (HORN project).
The system would integrate all the available information on antibiotic prescribing and antibiotic usage along with the farm management practices across the whole range of beef farming systems in Argentina. We will then categorize antibiotic use at farm level recruiting between 200 - 1000 farms from an existing representative network of 4500 farms (organized via SENASA) into different management system types (eg. breeding, growing, feedlot finishing) and correlate the management practices used in these farms with their patterns of antibiotic usage by using the surveillance framework. The environmental AMR population load and diversity will be assessed in a stratified random sub-sample of (n = 50) of the farms according to management system type and AMU level & usage practices. Multi-level modelling, cluster and principal component analysis will be used to quantify the agreement between the classification of farms based upon the AMU surveillance framework and the microbiological results to validate the efficacy of this means of risk assessment.
Deeper molecular analysis will be conducted on samples from farms with evidence of the most significant AMR diversity and load relating to High Priority Critically important antibiotics. This will include whole genome metagenomics and culture based antibiotic phenotype sensitivity to understand the population structure of the resistance profile of the most significant AMR environments.
This phase of the project will allow us to use risk factor analysis to identify critical control points in the mode of antibiotic use in beef farms. This will be achieved by linking the molecular epidemiology data to detailed quantitative and qualitative interviews with farmers to understand the drivers of antibiotic use.
The final phase of the project will co-develop practical AMR reduction interventions and policy advice of regulatory authorities. All the interventions recommended will be based up the risk factor analysis and their economic impact tested by cost - effectiveness analysis to identify in a clear a reproducible manner the most appropriate control measures for each farm management system. The qualitative interviews conducted with each farmer in the study will inform decision making on barriers to adoption of individual measures and feed into the co-development of policy advice to the beef industry. The collaboration provides the exciting opportunity to compare and contrast approaches in the UK and Argentina to maximizing farmer adoption of new practices and advice.
The project would employ two post-doctoral researchers (PDRAs) directly through the UoL. Whilst these two PDRA's will be employed by UoL they will be supervised jointly by UK and Argentine partner senior academics.
Technical Summary
The aim of the project is to develop an antimicrobial surveillance framework in the Argentine beef production sector that describes the correlation between usage levels and management practices with excretion of AMR and how this contributes to environmental AMR loading. This would serve as a robust evidence base for the development of policy in Argentina and would serve as a model for other LMIC's in South America and Africa. The diversity of beef cattle management systems in Argentina from; extensive to intensive, large and small scale, traditional to vertically-integrated, provides the ideal sampling frame to identify AMR selection risk factors in management systems that can be found in many livestock dependent LMICs in South America and beyond.
The system will integrate all the available information on human behaviour and economics of antibiotic prescribing and antibiotic usage along with the farm management practices across the whole range of beef farming systems in Argentina. We will then categorise farms into different management system types (eg. breeding, growing, feedlot finishing) and correlate the management practices used in these farms with their patterns of antibiotic usage by using the surveillance framework. The environmental AMR population load and diversity will be assessed in a stratified random sample of the farms according to management system type and AMU level & usage practices. Multi-level modelling, cluster and principal component analysis will be used to quantify the agreement between the classification of farms based upon the AMU surveillance framework and the microbiological results to validate the efficacy of this means of risk assessment. In addition to the validation of the surveillance framework, the project would identify farm management and cattle husbandry risk factors for environmental AMR contamination. The risk factor analysis would form the evidence base upon which targeted interventions will be co-developed with all parties.
The system will integrate all the available information on human behaviour and economics of antibiotic prescribing and antibiotic usage along with the farm management practices across the whole range of beef farming systems in Argentina. We will then categorise farms into different management system types (eg. breeding, growing, feedlot finishing) and correlate the management practices used in these farms with their patterns of antibiotic usage by using the surveillance framework. The environmental AMR population load and diversity will be assessed in a stratified random sample of the farms according to management system type and AMU level & usage practices. Multi-level modelling, cluster and principal component analysis will be used to quantify the agreement between the classification of farms based upon the AMU surveillance framework and the microbiological results to validate the efficacy of this means of risk assessment. In addition to the validation of the surveillance framework, the project would identify farm management and cattle husbandry risk factors for environmental AMR contamination. The risk factor analysis would form the evidence base upon which targeted interventions will be co-developed with all parties.
Planned Impact
The Argentine beef industry as a whole will benefit from the independent and robust antibiotic surveillance framework that will demonstrate to export markets the commitment to responsible antibiotic stewardship and verifiable monitoring of antibiotic use. Individual Argentine farm businesses will benefit through adoption of evidence based recommendations on means to reduce antibiotic use whilst maintain high productivity, health and efficiency.
The Argentine statutory regulatory authorities responsible for veterinary medicines will benefit from the development of a robust monitoring system that can be applied to many different objectives and to satisfy the reporting requirements of international organizations such as WHO on antibiotic usage.
The environment will benefit from improved management of antibiotic use in beef cattle, through reduced contamination and the adoption of recommendations to reduce use in the beef production system and improve the management of waste products to contain AMR within the farm environment. Argentine veterinarians working with beef farmers will benefit through knowledge transfer activities throughout Argentina in the final year of the project that will discuss in detail the findings of the study and communicate the ways in which they can work with their clients to improve animal health, animal production and reduce unnecessary antibiotic use. Other LMIC's will benefit from the surveillance framework in this project that can be applied and adapted for other situations - this will be most impactful in countries with large beef cattle populations and the development of commercial and intensifying farming systems. These developments are becoming more important as population growth in LMIC's drives greater demand for animal protein and increasing urbanization of populations drives greater need for efficient, professionalized agriculture. The development and use of this antibiotic surveillance framework will be a major benefit for agricultural systems undergoing these developments as a tool to normalize the responsible use of antibiotics and engrain the positive attitudes towards antibiotic stewardship into the culture of these developing livestock sectors.
Outputs of the project will include peer reviewed publications describing the antibiotic usage and AMR in the environment in respected scientific journals and presented at international conferences relating to both AMR, environmental microbiology, cattle veterinary science and antibiotic stewardship.
Beyond these conventional academic routes to impact this project will also generate a 'tool-box' of outputs that can be adopted by individual beef farmers, the Argentine beef industry and adapted for other LMIC's:Tool-box to reduce environmental AMR from beef production
- An antibiotic surveillance framework that identifies the repositories of data on beef cattle production and antibiotic usage/sales/prescriptions along with the barriers and opportunities for data integration from these diverse sources.
- A between farm antibiotic usage benchmarking system based upon the surveillance framework and validated by this project through targeted molecular microbiology by qPCR and whole genome metagenomics. This benchmarking system would be flexible enough to be operated at local or national levels, organized by farmer co-operatives, breeding companies, processors, veterinary practices or regulatory authorities.
- A comprehensive set of best practice recommendations for specific ways to reduce risk of AMR contamination of the environment that would be drawn from the risk factor analysis conducted as part of this project. The areas of highest risk areas of beef production would be addressed through comparison between high and low AMR farms in Argentina and refined using evidence from the in-depth qualitative interviews conducted with farmer participants.
The Argentine statutory regulatory authorities responsible for veterinary medicines will benefit from the development of a robust monitoring system that can be applied to many different objectives and to satisfy the reporting requirements of international organizations such as WHO on antibiotic usage.
The environment will benefit from improved management of antibiotic use in beef cattle, through reduced contamination and the adoption of recommendations to reduce use in the beef production system and improve the management of waste products to contain AMR within the farm environment. Argentine veterinarians working with beef farmers will benefit through knowledge transfer activities throughout Argentina in the final year of the project that will discuss in detail the findings of the study and communicate the ways in which they can work with their clients to improve animal health, animal production and reduce unnecessary antibiotic use. Other LMIC's will benefit from the surveillance framework in this project that can be applied and adapted for other situations - this will be most impactful in countries with large beef cattle populations and the development of commercial and intensifying farming systems. These developments are becoming more important as population growth in LMIC's drives greater demand for animal protein and increasing urbanization of populations drives greater need for efficient, professionalized agriculture. The development and use of this antibiotic surveillance framework will be a major benefit for agricultural systems undergoing these developments as a tool to normalize the responsible use of antibiotics and engrain the positive attitudes towards antibiotic stewardship into the culture of these developing livestock sectors.
Outputs of the project will include peer reviewed publications describing the antibiotic usage and AMR in the environment in respected scientific journals and presented at international conferences relating to both AMR, environmental microbiology, cattle veterinary science and antibiotic stewardship.
Beyond these conventional academic routes to impact this project will also generate a 'tool-box' of outputs that can be adopted by individual beef farmers, the Argentine beef industry and adapted for other LMIC's:Tool-box to reduce environmental AMR from beef production
- An antibiotic surveillance framework that identifies the repositories of data on beef cattle production and antibiotic usage/sales/prescriptions along with the barriers and opportunities for data integration from these diverse sources.
- A between farm antibiotic usage benchmarking system based upon the surveillance framework and validated by this project through targeted molecular microbiology by qPCR and whole genome metagenomics. This benchmarking system would be flexible enough to be operated at local or national levels, organized by farmer co-operatives, breeding companies, processors, veterinary practices or regulatory authorities.
- A comprehensive set of best practice recommendations for specific ways to reduce risk of AMR contamination of the environment that would be drawn from the risk factor analysis conducted as part of this project. The areas of highest risk areas of beef production would be addressed through comparison between high and low AMR farms in Argentina and refined using evidence from the in-depth qualitative interviews conducted with farmer participants.
Description | Antibiotic use in the Argentine beef industry is complex and diverse across the different geographical regions and production systems. |
Exploitation Route | Critically important for policy makers in their design of benchmarking and surveillance systems for AMU and AMR in LMIC's |
Sectors | Agriculture Food and Drink Environment Pharmaceuticals and Medical Biotechnology |
Description | Iceberg Diseases of Welsh Livestock Farming Systems (AMR) |
Amount | £67,300 (GBP) |
Organisation | Hybu Cig Cymru |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2019 |
End | 07/2023 |
Description | AMR bioinformatics exploration DTP PhD |
Organisation | University of Nottingham |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Collaboration in greater depth analysis of the metagenomic sequence data - our project contributed teh sequence data and metadata, UoN collaborators contributed their computer science and bioinformatics expertise and supervision of the BBSRC DTP student which Dr Davies also contributed to as an external supervisor. |
Collaborator Contribution | Collaboration in greater depth analysis of the metagenomic sequence data - our project contributed teh sequence data and metadata, UoN collaborators contributed their computer science and bioinformatics expertise and supervision of the BBSRC DTP student which Dr Davies also contributed to as an external supervisor. |
Impact | none as yet, too soon |
Start Year | 2023 |