ReviewFrontiers in veterinary science2019
Antimicrobial Policies in United States Beef Production: Choosing the Right Instruments to Reduce Antimicrobial Use and Resistance Under Structural and Market Constraints.
Review in Frontiers in veterinary science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Mapping Variability in Bovine Respiratory Disease Risk Factors in Beef Production Systems: A Scoping Review.Animals : an open access journal from MDPI · 2026Review
- Systematic mapping of threats to U.S. beef production.Translational animal science · 2026Review
- Beef Cattle Farmers' Knowledge, Attitudes, and Practices Toward On-Farm Biosecurity, Antimicrobial Use, and Antimicrobial Resistance in Illinois, United States of America.Antibiotics (Basel, Switzerland) · 2025Article
- The Marginal Abatement Cost of Antimicrobials for Dairy Cow Mastitis: A Bioeconomic Optimization Perspective.Veterinary sciences · 2023Article
- Economic evaluation of antimicrobial use practices in animal agriculture: a case of poultry farming.JAC-antimicrobial resistance · 2022Article
- System Economic Costs of Antibiotic Use Elimination in the US Beef Supply Chain.Frontiers in veterinary science · 2021Article
- Prevalence and Risk Factors Associated With Antimicrobial Resistance in Bacteria Related to Bovine Respiratory Disease-A Broad Cross-Sectional Study of Beef Cattle at Entry Into Canadian Feedlots.Frontiers in veterinary science · 2021Article
- Age Dependence of Antimicrobial Resistance Among Fecal Bacteria in Animals: A Scoping Review.Frontiers in veterinary science · 2020Article
- Economic effects of policy options restricting antimicrobial use for high risk cattle placed in U.S. feedlots.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial use (AMU) in animal agriculture contributes to the selection of resistant bacteria, potentially constituting a public health threat. To address antimicrobial resistance, public policies set by governments, as well as intra-sectoral approaches, can be implemented. In this paper, we explore how common policy instruments such as regulations, economic incentives, and voluntary agreements could help reduce AMU in beef production. We first describe the structure of the beef supply chain which directly influences the choice of policy instruments. We describe how externalities and imperfect information affect this system. We then discuss how five policy instruments would each perform to achieve a reduction in AMU. Bovine respiratory disease complex (BRD) represents the major driver of AMU in beef production; consequently, reducing its incidence would decrease significantly the amounts of antimicrobials administered. We consider control options for BRD at different stages of the beef supply chain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.