BackgroundAntimicrobial resistance is a public health threat. Because antimicrobial consumption in food-producing animals contributes to the problem, policies restricting the inappropriate or unnecessary agricultural use of antimicrobial drugs are important. However, this link between agricultural antibiotic use and antibiotic resistance has remained contested by some, with potentially disruptive effects on efforts to move towards the judicious or prudent use of these drugs.Main textThe goal of this review is to systematically evaluate the types of evidence available for each step in the causal pathway from antimicrobial use on farms to human public health risk, and to evaluate the strength of evidence within a ‘Grades of Recommendations Assessment, Development and Evaluation‘(GRADE) framework. The review clearly demonstrates that there is compelling scientific evidence available to support each step in the causal pathway, from antimicrobial use on farms to a public health burden caused by infections with resistant pathogens. Importantly, the pathogen, antimicrobial drug and treatment regimen, and general setting (e.g., feed type) can have significant impacts on how quickly resistance emerges or spreads, for how long resistance may persist after antimicrobial exposures cease, and what public health impacts may be associated with antimicrobial use on farms. Therefore an exact quantification of the public health burden attributable to antimicrobial drug use in animal agriculture compared to other sources remains challenging.ConclusionsEven though more research is needed to close existing data gaps, obtain a better understanding of how antimicrobial drugs are actually used on farms or feedlots, and quantify the risk associated with antimicrobial use in animal agriculture, these findings reinforce the need to act now and restrict antibiotic use in animal agriculture to those instances necessary to ensure the health and well-being of the animals.

Aims: To examine factors affecting faecal shedding of the foodborne pathogens Escherichia coli O157:H7 and Salmonella in dairy cattle and evaluate antimicrobial susceptibility of these isolates. Methods: Faecal samples were obtained in replicate from lactating (LAC; n ¼ 60) and non-lactating (NLAC; n ¼ 60) Holstein cattle to determine influence of heat stress, parity, lactation status (LAC vs NLAC) and stage of lactation [£60 or >60 days in milk (DIM)] and cultured for E. coli O157:H7 and Salmonella. A portion of the recovered isolates were examined for antimicrobial susceptibility using the broth microdilution technique. Results: No effects of heat stress were observed. Lactating cows shed more (P < 0AE01) E. coli O157:H7 than NLAC cows (43% vs 32%, respectively). Multiparous LAC cows tended to shed more (P ¼ 0AE06) Salmonella than primiparous LAC cows (39% vs 27%, respectively). Parity did not influence (P > 0AE10) bacterial shedding in NLAC cows. Cows £60 DIM shed more (P < 0AE05) Salmonella than cows >60 DIM. Seventeen Salmonella serotypes were identified with the most prevalent being Senftenberg (18%), Newport (17%) and Anatum (15%). Seventy-nine of the Salmonella isolates were resistant to at least one of the seven antibiotics. Escherichia coli O157:H7 isolates were resistant to 11 different antibiotics with multiple resistance to nine or more antibiotics observed in five isolates. Significance and Impact of the Study: This study demonstrated differences in the shedding patterns of foodborne pathogens due to the stage of the milk production cycle and may help identify times when on-farm pathogen control would be the most effective.

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The discovery of urgently needed antibiotics is hindered by challenges to information sharing. To help address this challenge, The Pew Charitable Trusts launched SPARK: the Shared Platform for Antibiotic Research and Knowledge. SPARK is an online, publicly available, interactive database designed to help scientists build on previous research and generate new insights to advance the field's understanding of Gram-negative permeability. This Viewpoint details how data are selected and integrated into the platform, how scientists can use SPARK to share their data, and the ways the scientific community can access and use these data to develop hypotheses.