Abstract

It is commonly asserted that agricultural production systems must use fewer antibiotics in food-producing animals in order to mitigate the global spread of antimicrobial resistance (AMR). In order to assess the cost-effectiveness of such interventions, especially given the potential trade-off with rural livelihoods, we must quantify more precisely the relationship between food-producing animal antimicrobial use and AMR in humans. Here, we outline and compare methods that can be used to estimate this relationship, calling on key literature in this area. Mechanistic mathematical models have the advantage of being rooted in epidemiological theory, but may struggle to capture relevant non-epidemiological covariates which have an uncertain relationship with human AMR. We advocate greater use of panel regression models which can incorporate these factors in a flexible way, capturing both shape and scale variation. We provide recommendations for future panel regression studies to follow in order to inform cost-effectiveness analyses of AMR containment interventions across the One Health spectrum, which will be key in the age of increasing AMR.

Highlights

  • Antimicrobial resistance (AMR) is an archetypally One Health problem, with increasingly profound global consequences for human health [1,2]

  • Tionary principle,impact whichon argues for need the restriction of theby use in food-producing animals of Without quantifying the empirical relationship between food-producing animal and human antibiotics of critical medical importance to humans, we argue that such decisions, which it is to assess thesupported health economic worthwhileness may have a large AMR, impact onimpossible farmers, need to be by quantification of likely of targeting food-producing animal Antimicrobial use (AMU), and difficult to make national-level policy effect

  • In a subsequent stratified meta-analysis focusing on food-producing animal AMR outcomes in the same body of literature [31], the authors found that the ostensible effectiveness of interventions was influenced considerably by the underlying prevalence of food-producing animal AMU, again making results difficult to generalise across settings

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Summary

Background

Antimicrobial resistance (AMR) is an archetypally One Health problem, with increasingly profound global consequences for human health [1,2]. Antimicrobial use (AMU) in food-producing animals considerably outweighs that in humans; and there is evidence of the transfer of resistant bacteria and genes (resistomes) from food-producing animals to humans via the food chain, through direct contact with livestock and indirectly (via contamination of crops and the environment by animal manure and slurry, through waterways in aquaculture, etc.) [3,4,5,6,7,8] This can contribute to the prevalence of AMR pathogens in humans. Where resistance is transmitted with ease from humans to foodproducing animals, a pool of resistance may be maintained in those animals even when agricultural AMU is low [23,24] This necessitates a multi-sectoral approach, and suggests that reducing food-producing animal use alone may have only a modest effect on AMR carriage and disease burden in humans [2]. Food-Producing Animal Antimicrobial Use. (Rectangles represent reservoirs of resistance, ovals represent introduction of antimicrobials into the system, and crosses represent the interruption of represent introduction of antimicrobials into the system, and crosses represent the interruption of transmission or selection mechanisms.)

Present Quantification
Alternative Ways of Assessing This Relationship
Transmission Dynamic Mathematical Models
Advantages and Limitations of this Method
Future Research Using This Method
Panel Regression Models
Advantages and Limitations of This Method
Recommendations for Future Analysis
Methods
Final Remarks
Relevant Findings
Full Text
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