Antimicrobial usage (AMU) in livestock has been shown to be an important driver of antimicrobial resistance (AMR) in animals and is associated with resistance in humans, with a recent meta-analysis showing a 24% absolute reduction in the prevalence of antibiotic-resistant bacteria in humans with interventions that reduce antibiotic use in animals (Tang et al. 2017). Infections are often caused by different strains in animals and humans, however as the resistance genes themselves are mobile this does not preclude the role of AMU in livestock driving emergence of AMR in human pathogens.
Agriculture’s share of global antibiotic consumption is high and rising, as the demand for animal protein increases, especially in low- and middle-income countries (LMICs). In much of Latin America (and other parts of the world) feedlot beef production, which is intensive and features high AMU, is increasingly being used over less intensive, grass-fed, low-AMU production. The reason for this is attributed to increasing land prices, erosion, and competition from other agricultural production.
Ironically, as international efforts to tackle AMR increase (e.g. the FAO, OIE and WHO Memorandum of Understanding, signed on 30 May 2018) one of the remaining largely extensive, low-AMU livestock systems is moving towards intensive, high AMU production. Without considering the important role that the farmed and natural environment plays in contributing to the overall burden of AMR infection, and taking steps to reduce environmental AMR, efforts in other sectors may not prevent the post-antibiotic era that threatens modern medicine.
“El Trebol”, a feedlot located near Roque Perez in the Province of Buenos Aires.
The Guachera of a dairy farm in Lobos Province, Buenos Aires.
This £1.2 M DHSC/UKAid-funded project, administered by BBSRC, focuses on feedlot beef production in Argentina, a country that currently sits at the top of the LMIC development scale. Through multidisciplinary research, we will generate an integrated approach to considering AMR in a One Health context and produce a ‘framework blueprint’ for an integrated surveillance, analysis, interpretation, modelling and policy translation approach that can be utilised for any livestock system in any LMIC to facilitate decision making, help implement incentives and inform new policy around interventions to reduce AMU, AMR and risks to human health.
The project is a fully collaborative Argentina–UK endeavour, with research questions co-developed with a consortium including the National Institute of Infectious Diseases (INEI – ANLIS), the National Institute of Agricultural Technology (INTA), the National Service for Agrifood Health and Quality (SENASA) and the Institute of Microbiology and Parasitology (IMPAM) in Argentina.
Project outputs will inform how interventions to reduce antimicrobial usage can reduce AMR in a cost-effective manner, which will enable improvements in livestock management practice whilst protecting countries from the financial, societal and health burdens imposed by AMR attributable to livestock production.
The University of Exeter’s research team is involved in delivering the following work packages:
Evidence synthesis (Professor Ruth Garside, Dr Anne Leonard). Conducting a systematic mapping exercise to provide objective data on existing evidence and knowledge gaps relating to AMU and AMR in feedlot systems. Findings will be presented with an accompanying narrative to describe the nature, events and distribution of the relevant research.
Evolution experiments under environmental antibiotic residuescenarios (Professor William Gaze, Dr Aimee Murray). Taking antibiotic residue and AMR/concentration in impacted environments characterised in selected Argentinian feedlot systems and surrounding areas, including in soil and water, and using lab-based and field-based bacterial evolution experiments to determine risk of selection for AMR occurring in soil and aquatic environments.
Data modelling (Professor Stuart Townley). Underpinning the ‘framework blueprint’ with mathematical modelling, using existing, new and simulated data.
Economic analysis (Professor Dominic Moran). Considering the relative cost of interventions and constructing Marginal Abatement Cost Curves (MACC) to accumulate and analyse data on measure implementation cost and effectiveness. This cost-effectiveness analysis will provide the basis for rational policy design and interventions to promote the lowest cost of cost-saving interventions as a priority.
Informing policy (Dr Emma Pitchforth). Identifying relevant stakeholders in terms of the stages of causation and actions; holding policy engagement events to develop policy-focused briefings appropriate to local, national and international stakeholders; and developing and disseminating policy briefs.