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A proposed analytic framework for determining the impact of an antimicrobial resistance intervention

Published online by Cambridge University Press:  16 May 2017

Yrjo T. Grohn Open the ORCID record for Yrjo T. Grohn [Opens in a new window] ,
Carolee Carson ,
Cristina Lanzas ,
Laura Pullum ,
Michael Stanhope  and
Victoriya Volkova
Yrjo T. Grohn*
Affiliation:
Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, USA
Carolee Carson
Affiliation:
Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Ottawa, Ontario, Canada
Cristina Lanzas
Affiliation:
Population Health and Pathobiology, North Carolina State University College of Veterinary Medicine, Raleigh, North Carolina, USA
Laura Pullum
Affiliation:
Oak Ridge National Laboratory, Health Data Sciences Institute, Oak Ridge, Tennessee, USA
Michael Stanhope
Affiliation:
Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, USA
Victoriya Volkova
Affiliation:
Diagnostic Medicine/Pathobiology, Institute of Computational Comparative Medicine, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

Antimicrobial use (AMU) is increasingly threatened by antimicrobial resistance (AMR). The FDA is implementing risk mitigation measures promoting prudent AMU in food animals. Their evaluation is crucial: the AMU/AMR relationship is complex; a suitable framework to analyze interventions is unavailable. Systems science analysis, depicting variables and their associations, would help integrate mathematics/epidemiology to evaluate the relationship. This would identify informative data and models to evaluate interventions. This National Institute for Mathematical and Biological Synthesis AMR Working Group's report proposes a system framework to address the methodological gap linking livestock AMU and AMR in foodborne bacteria. It could evaluate how AMU (and interventions) impact AMR. We will evaluate pharmacokinetic/dynamic modeling techniques for projecting AMR selection pressure on enteric bacteria. We study two methods to model phenotypic AMR changes in bacteria in the food supply and evolutionary genotypic analyses determining molecular changes in phenotypic AMR. Systems science analysis integrates the methods, showing how resistance in the food supply is explained by AMU and concurrent factors influencing the whole system. This process is updated with data and techniques to improve prediction and inform improvements for AMU/AMR surveillance. Our proposed framework reflects both the AMR system's complexity, and desire for simple, reliable conclusions.

Keywords

antimicrobial useantimicrobial resistanceintervention strategyanalytic framework
Type
Review Article
Information
Animal Health Research Reviews , Volume 18 , Issue 1 , June 2017 , pp. 1 - 25
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Copyright
Copyright © Cambridge University Press 2017 

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References

ANSES. ANSES (Agency for Food, Environmental and Occupational Health and Safety, France). Report Sales Survey of Veterinary Medicinal Products Containing Antimicrobials in France 2014. [Available online at https://www.anses.fr/en/system/files/ANMV-Ra-Antibiotiques2014EN.pdf]. (Last accessed on June 1, 2016).Google Scholar
Apley, MD, Bush, EJ, Morrison, RB, Singer, RS and Snelson, H (2012). Use estimates of in-feed antimicrobials in swine production in the United States. Foodborne Pathogens and Disease 9: 272–279.Google Scholar
Austin, DJ, Kakehashi, M and Anderson, RM (1997). The transmission dynamics of antibiotic-resistant bacteria: the relationship between resistance in commensal organisms and antibiotic consumption. Proceedings of the Royal Society of London B 264: 1629–1638.CrossRefGoogle ScholarPubMed
Austin, DJ, Kristinsson, KG and Anderson, RM (1999). The relationship between the volume of antimicrobial consumption in human communities and the frequency of resistance. Proceedings of the National Academy of Sciences of the United States of America 96: 1152–1156.Google Scholar
Bager, F, Madsen, M, Christensen, J and Aarestrup, FM (1997). Avoparcin used as a growth promoter is associated with the occurrence of vancomycin-resistant Enterococcus faecium on Danish poultry and pig farms. Preventive Veterinary Medicine 31: 95–112.Google Scholar
Baudrit, C, Sicard, M, Wuillemin, PH and Perrot, N (2010). Towards a global modelling of the Camembert- type cheese ripening process by coupling heterogeneous knowledge with dynamic Bayesian networks. Journal of Food Engineering 98: 283–293.Google Scholar
Beconi-Barker, MG, Roof, RD, Vidmar, TJ, Hornish, RE, Smith, EB, Gatchell, CL and Gilbertson, TJ (1996). Ceftiofur sodium: absorption, distribution, metabolism, and excretion in target animals and its determination by high-performance liquid chromatography. Veterinary Drug Residues 636: 70–84.Google Scholar
Benedict, KM, Gow, SP, McAllister, TA, Booker, CW, Hannon, SJ, Checkley, SL, Noyes, NR and Morley, PS (2015). Antimicrobial resistance in Escherichia coli recovered from feedlot cattle and associations with antimicrobial use. PLoS ONE 10: e0143995.Google Scholar
Berge, AC, Moore, DA and Sischo, WM (2006). Field trial evaluating the influence of prophylactic and therapeutic antimicrobial administration on antimicrobial resistance of fecal Escherichia coli in dairy calves. Applied and Environmental Microbiology 72: 3872–3878.Google Scholar
Bradley, P, Gordon, NC, Walker, TM, Dunn, L, Heys, S, Huang, B, Earle, S, Pankhurst, LJ, Anson, L, de Cesare, M, Piazza, P, Votintseva, AA, Golubchik, T, Wilson, DJ, Wyllie, DH, Diel, R, Niemann, S, Feuerriegel, S, Kohl, TA, Ismail, N, Omar, SV, Smith, EG, Buck, D, McVean, G, Walker, AS, Peto, TEA, Crook, DW and Iqbal, Z (2015). Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis . Nature Communications 6: 10063.Google Scholar
Callens, B, Persoons, D, Maes, D, Laanen, M, Postma, M, Boyen, F, Haesebrouck, F, Butaye, P, Catry, B and Dewulf, J (2012). Prophylactic and metaphylactic antimicrobial use in Belgian fattening pig herds. Preventive Veterinary Medicine 106: 53–62.Google Scholar
Carman, RJ, Simon, MA, Petzold, HE, Wimmer, RF, Batra, MR, Fernandez, AH, Miller, MA and Bartholomew, M (2005). Antibiotics in the human food chain: establishing no effect levels of tetracycline, neomycin, and erythromycin using a chemostat model of the human colonic microflora. Regulatory Toxicology and Pharmacology 43: 168–180.Google Scholar
Carmo, LP, Schüpbach-Regula, G, Müntener, C, Chevance, A, Moulin, G and Magouras, I (2015). Stratification of Veterinary Antimicrobial Sales per Species – The Swiss Example. Merida, Mexico: International Society for Veterinary Epidemiology and Economics, Oral presentation.Google Scholar
Carson, CA, Reid-Smith, R, Irwin, RJ, Martin, WS and McEwen, SA (2008). Antimicrobial use on 24 beef farms in Ontario. Canadian Journal of Veterinary Research 72: 109–118.Google ScholarPubMed
Cazer, CL, Volkova, VV and Gröhn, YT (2014). Use of pharmacokinetic modeling to assess antimicrobial pressure on enteric bacteria of beef cattle fed chlortetracycline for growth promotion, disease control, or treatment. Foodborne Pathogens and Disease 11: 403–411.Google Scholar
Centers for Disease Control and Prevention. NARMS Annual Reports. [Available online at http://www.cdc.gov/narms/reports/] (Last accessed on Oct. 26, 2016).Google Scholar
Chauvin, C, Le Bouquin-Leneveu, S, Hardy, A, Haguet, D, Orand, JP and Sanders, P (2005). An original system for the continuous monitoring of antimicrobial use in poultry production in France. Journal of Veterinary Pharmacology and Therapeutics 28: 515–523.Google Scholar
CIPARS (Canadian Integrated Program for Antimicrobial Resistance Surveillance) (2012). Annual Report. [Available online at http://www.phac-aspc.gc.ca/cipars-picra/2012/annu-report-rapport-eng.php] (Last accessed on June 1, 2016).Google Scholar
Cornejo, OE, Lefébure, T, Bitar, PD, Lang, P, Richards, VP, Eilertson, K, Do, T, Beighton, D, Zeng, L, Ahn, SJ, Burne, RA, Siepel, A, Bustamante, CD and Stanhope, MJ (2013). Evolutionary and population genomics of the cavity causing bacteria Streptococcus mutans . Molecular Biology and Evolution 30: 881–893.CrossRefGoogle ScholarPubMed
DANMAP. (Danish Integrated Antimicrobial Resistance Monitoring and Research Programme) (2014). Use of antimicrobial agents and occurrence of antimicrobial resistance in food animals, food and humans in Denmark. [Online] [Cited March 31, 2016]. [Available online at http:// www.danmap.org/] (last accessed on June 1, 2016).Google Scholar
DANMAP. (Danish Integrated Antimicrobial Resistance Monitoring and Research Programme) (2015). Use of antimicrobial agents and occurrence of antimicrobial resistance in food animals, food and humans in Denmark. [Online] [Cited February 1, 2017]. [Available online at http:// www.danmap.org/] (last accessed on February 1, 2017).Google Scholar
Deckert, A, Gow, S, Rosengren, L, Leger, D, Avery, B, Daignault, D, Dutil, L, Reid-Smith, R and Irwin, R (2010). Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) farm program: results from finisher pig surveillance. Zoonoses and Public Health 57: 71–84.Google Scholar
Dunlop, RH, McEwen, SA, Meek, AH, Black, WD, Clarke, RC and Friendship, RM (1998). Individual and group antimicrobial usage rates on 34 farrow-to-finish swine farms in Ontario, Canada. Preventive Veterinary Medicine 34: 247–264.Google Scholar
European Centre for Disease Prevention and Control (2016). Antimicrobial resistance strategies and action plans. [Available online at http://ecdc.europa.eu/en/healthtopics/Healthcare-associated_infections/guidance-infection-prevention-control/Pages/antimicrobial-resistance-strategies-action-plans.aspx]Google Scholar
European Commission (2016). Antimicrobial Resistance (AMR) Action Plan 2011–2016 Evaluation Key Findings. Ministerial Conference on Antimicrobial Resistance, Amsterdam 9–10 February 2016. [Available online at http://ec.europa.eu/dgs/health_food-safety/amr/docs/news_20160210_amr-factsheet.pdf] (Last accessed on February 1, 2017).Google Scholar
EFSA (2006). ECDC/EFSA/EMA first joint report on the integrated analysis of the consumption of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from humans and food-producing animals. [Available online at http://www.efsa.europa.eu/en/efsajournal/pub/4006EF]Google Scholar
ESVAC. ESVAC (European Surveillance of Veterinary Antimicrobial Consumption). Draft ESVAC Vision and Strategy 2016–2020. [Available online at http://www.ema.europa.eu/docs/en_GB/document_library/Regulatory_and_procedural_guideline/2016/04/WC500204522.pdf]. (Last accessed on June 1, 2016).Google Scholar
European Medicines Agency (2015). Revised ESVAC reflection paper on collecting data on consumption of antimicrobial agents per animal species, on technical units of measurement and indicators for reporting consumption of antimicrobial agents in animals. EMA/286416/2012-Rev.1 10 Oct 2013. [Available online at http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/12/WC500136456.pdf] (Last accessed on Dec. 17, 2015).Google Scholar
EVIRA. EVIRA (Finnish Food Safety Authority). [Available online at https://www.evira.fi/en/animals/animal-health-and-diseases/animal-medication/european-antibiotic-awareness-day/antibiotic-use-for-animals-in-finland/). (Last accessed on June 1, 2016).Google Scholar
FDA-CVM (2004). Guidance for Industry #52. Assessment of the effects of antimicrobial residues from food of animal origin on the human intestinal flora.Google Scholar
FDA-CVM (2012). Guidance for Industry #159. Studies to evaluate the safety of residues of veterinary drugs in human food: general approach to establish a microbiological ADI.Google Scholar
FDA (2013). Animal Drug User Fee Act. [Available online at http://www.fda.gov/ForIndustry/UserFees/AnimalDrugUserFeeActADUFA/default.htm]Google Scholar
FDA (2015). Department of Health and Human Services, Center for Veterinary Medicine. 2013 - Summary Report on Antimicrobials Sold or Distributed for Use in Food-Producing Animals. [Online] [Cited March 31, 2016]. [Available online at http://www.fda.gov/downloads/ForIndustry/UserFees/AnimalDrugUserFeeActADUFA/UCM440584.pdf](Last accessed on June 1, 2016).Google Scholar
Foster, DM, Jacob, ME, Warren, CD and Papich, MG (2016). Pharmacokinetics of enrofloxacin and ceftiofur in plasma, interstitial fluid, and gastrointestinal tract of calves after subcutaneous injection, and bactericidal impacts on representative enteric bacteria. Journal of Veterinary Pharmacology and Therapeutics 39: 62–71.Google Scholar
Friedman, J, Hastie, T and Tibshirani, R (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics (Oxford, England) 9: 432–441.Google Scholar
Garcia-Migura, L, Hendriksen, RS, Fraile, L and Aarestrup, FM (2014). Antimicrobial resistance of zoonotic and commensal bacteria in Europe: the missing link between consumption and resistance in veterinary medicine. Veterinary Microbiology 170: 1–9.Google Scholar
Gilbertson, TJ, Hornish, RE, Jaglan, PS, Koshy, KT, Nappier, JL, Stahl, GL, Cazers, AR, Nappier, JM and Kubicek, MF (1990). Environmental fate of ceftiofur sodium, a cephalosporin antibiotic. Role of animal excreta in its decomposition. Journal of Agricultural and Food Chemistry 38: 890–894.Google Scholar
Gomez, S, Jensen, P and Arenas, A (2009). Analysis of community structure in networks of correlated data. Physical Review E 80: 016114.Google Scholar
Gordon, NC, Price, JR, Cole, K, Everitt, R, Morgan, M, Finney, J, Kearns, AM, Pichon, B, Young, B, Wilson, DJ, Llewelyn, MJ, Paul, J, Peto, TE, Crook, DW, Walker, AS and Golubchik, T (2014). Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing. Journal of Clinical Microbiology 52: 1182–1191.Google Scholar
Grave, K, Jensen, VF, McEwen, S and Kruse, H (2006). Monitoring of antimicrobial usage in animals: methods and applications. Aarestrup, FM (ed) Antimicrobial Resistance in Bacteria of Animal Origin. Washington: ASM Press.Google Scholar
Hall, BG, Ehrlich, GD and Hu, FZ (2010). Pan-genome analysis provides much higher strain typing resolution than multi-locus sequence typing. Microbiology 156: 1060–1068.Google Scholar
Harada, K, Asai, T, Ozawa, M, Kojima, A and Takahashi, T (2008). Farm-level impact of therapeutic antimicrobial use on antimicrobial-resistant populations of Escherichia coli isolates from pigs. Microbial Drug Resistance 14: 239–244.Google Scholar
Hornish, RE and Kotarski, SF (2002). Cephalosporins in veterinary medicine - ceftiofur use in food animals. Current Topics in Medicinal Chemistry 2: 717–731.Google Scholar
HPRA. HPRA (Health Products Regulatory Authority, Ireland). Report on consumption of veterinary antibiotics in Ireland during 2014. [Available online at https://www.hpra.ie/docs/default-source/publications-forms/newsletters/report-on-consumption-of-veterinary-antibiotics-in-ireland-during-2014.pdf?sfvrsn=9). (Last accessed on June 1, 2016).Google Scholar
Izadi, M, Charland, K and Buckeridge, D (2014). Using dynamic Bayesian networks for incorporating non-traditional data sources in public health surveillance. World Wide Web and Public Health Intelligence: papers from the AAAI-14 Workshop.Google Scholar
Jaspers, S, Aerts, M, Verbeke, G and Beloeil, PA (2014). Estimation of the wild-type minimum inhibitory concentration value distribution. Statistics in Medicine 33: 289–303.Google Scholar
Jaspers, S, Ganyani, T, Ensoy, C, Faes, C, Aerts, M (2016). Development and application of statistical methodology for analysis of the phenomenon of multi-drug resistance in the EU: demonstration of analytical approaches using antimicrobial resistance isolate-based data. EFSA Supporting Publications 13: 9.Google Scholar
Jensen, VF, Jacobsen, E and Bager, F (2004). Veterinary antimicrobial-usage statistics based on standardized measures of dosage. Preventive Veterinary Medicine 64: 201–215.Google Scholar
Johnsen, PJ, Townsend, JP, Bøhn, T, Simonsen, GS, Sundsfjord, A and Nielsen, KM (2011). Retrospective evidence for a biological cost of vancomycin resistance determinants in the absence of glycopeptide selective pressures. Journal of Antimicrobial Chemotherapy 66: 608–610.Google Scholar
Kruse, H, Johansen, BK, Rorvik, LM and Schaller, G (1999). The use of avoparcin as a growth promoter and the occurrence of vancomycin-resistant Enterococcus species in Norwegian poultry and swine production. Microbial Drug Resistance 5: 135–139.Google Scholar
Lipsitch, M and Samore, MH (2002). Antimicrobial use and antimicrobial resistance: a population perspective. Emerging Infectious Diseases 8: 347–354.Google Scholar
Love, WJ, Zawack, KA, Booth, JG, Gröhn, YT, Lanzas, C. (2016) Markov Networks of collateral antibiotic resistance: National Antimicrobial Resistance Monitoring System surveillance results from E. coli isolates, 2004–2013. PLoS Computational Biology 12: e1005160. doi: 10.1371/journal. pcbi.1005160. CrossRefGoogle Scholar
Maiden, MCJ, Jansen van Rensburg, MJ, Bray, JE, Earle, SG, Ford, SA, Jolley, KA and McCarthy, ND (2013). MLST revisited: the gene-by-gene approach to bacterial genomics. Nature Reviews Microbiology 11: 728–736.Google Scholar
MARAN (2014). Monitoring of Antimicrobial Resistance and Antibiotic Usage in Animals in the Netherlands in 2013. [Online] [Cited: March 31, 2016]. [Available online at https://www.wageningenur.nl/upload_mm/1/a/1/0704c512-5b42-4cef-8c1b-60e9e3fb2a62_NethMap-MARAN2014.pdf]. (last accessed on June 1, 2016).Google Scholar
Marshall, BM and Levy, SB (2011). Food animals and antimicrobials: impacts on human health. Clinical Microbiology Reviews 24: 718–733.Google Scholar
McDermott, PF, Tyson, GH, Kabera, C, Chen, Y, Li, C, Folster, JP, Ayers, SL, Lam, C, Tate, HP and Zhao, S (2016). The use of whole genome sequencing for detecting antimicrobial resistance in nontyphoidal Salmonella. Antimicrobial Agents and Chemotherapy 60: 5515–5520.Google Scholar
Merle, R, Robanus, M, Hegger-Gravenhorst, C, Mollenhauer, Y, Hajek, P, Käsbohrer, A, Honscha, W and Kreienbrock, L (2014). Feasibility study of veterinary antibiotic consumption in Germany – comparison of ADDs and UDDs by animal production type, antimicrobial class and indication. BMC Veterinary Research 10: 7.Google Scholar
Monnet, DL, López-Lozano, JM, Campillos, P, Burgos, A, Yagüe, A and Gonzalo, N (2001). Making sense of antimicrobial use and resistance surveillance data: application of ARIMA and transfer function models. Clinical Microbiology and Infection 7: 29–36.Google Scholar
Moon, CS, Berke, O, Avery, BP, McEwen, SA, Reid-Smith, RJ, Scott, L and Menzies, P (2011). Rates and determinants of antimicrobial use, including extra-label, on Ontario sheep farms. Canadian Journal of Veterinary Research 75: 1–10.Google Scholar
Newman, MEJ (2004). Analysis of weighted networks. Physical Review E 70: 056131.Google Scholar
Noyes, NR, Benedict, KM, Gow, SP, Waldner, CL, Reid-Smith, RJ, Booker, CW, McAllister, TA and Morley, PS (2016). Modelling considerations in the analysis of associations between antimicrobial use and resistance in beef feedlot cattle. Epidemiology and Infection 144: 1313–1329.CrossRefGoogle ScholarPubMed
Oliver, SP, Murinda, SE and Jayarao, BM (2011). Impact of antibiotic use in adult dairy cows on antimicrobial resistance of veterinary and human pathogens: a comprehensive review. Foodborne Pathogens and Disease 8: 337–355.Google Scholar
Perrin-Guyomard, A, Cottin, S, Corpet, DE, Boisseau, J and Poul, JM (2001). Evaluation of residual and therapeutic doses of tetracycline in the human-flora-associated (HFA) mice model. Regulatory Toxicology and Pharmacology 34: 125–136.Google Scholar
Philippe, W and Lionel, J (2006). Complex system reliability modelling with dynamic object oriented Bayesian networks (DOOBN). Reliability Engineering and System Safety 91: 149–162.Google Scholar
Postma, M, Sjölund, M, Collineau, L, Lösken, S, Stärk, KD and Dewulf, J (2015). Assigning defined daily doses animal: a European multi-country experience for antimicrobial products authorized for usage in pigs. Journal of Antimicrobial Chemotherapy 70: 294–302.Google Scholar
Poupard, J, Brown, J, Gagnon, R, Stanhope, MJ and Stewart, C (2002). Methods for data mining from large multinational surveillance studies. Antimicrobial Agents and Chemotherapy 46: 2409–2419.Google Scholar
Ritter, L, Kirby, G and Cerniglia, C (1996). Toxicological Evaluation of Certain Veterinary Drug Residues in Food. (857) Ceftiofur. WHO Food Additives Series 36. Geneva, Switzerland. [Available online at http://www.inchem.org/documents/jecfa/jecmono/v36je01.htm]Google Scholar
Salmon, SA, Watts, JL and Yancey, RJ Jr (1996). In vitro activity of ceftiofur and its primary metabolite, desfuroylceftiofur, against organisms of veterinary importance. Journal of Veterinary Diagnostic Investigation 8: 332–336.Google Scholar
Smid, JH, Swart, AN, Havelaar, AH and Pielaat, A (2011). A practical framework for the construction of a biotracing model: application to Salmonella in the pork slaughter chain. Risk Analysis 33: 1434–1450.Google Scholar
Speksnijder, DC, Mevius, DJ, Bruschke, CJM and Wagenaar, JA (2014). Reduction of veterinary antimicrobial use in the Netherlands. The Dutch Success Model. Zoonoses and Public Health 62(2015) (Suppl 1): 79–87.Google Scholar
Stanhope, MJ, Lefébure, T, Walsh, SL, Becker, JA, Lang, P, Pavinski Bitar, PD, Miller, LA, Italia, MJ and Amrine- Madsen, H (2008). Positive selection in penicillin-binding proteins 1a, 2b, and 2x from Streptococcus pneumoniae and its correlation with amoxicillin resistance development. Infection Genetics and Evolution 8: 331–339.Google Scholar
Stevens, M, Piepers, S, Supré, K, Dewulf, J and De Vliegher, S (2016). Quantification of antimicrobial consumption in adult cattle on dairy herds in Flanders, Belgium, and associations with udder health, milk quality, and production performance. Journal of Dairy Science 99: 2118–2130.Google Scholar
SVARM. SWEDRES|SVARM (2014). (Swedish Veterinary Antimicrobial Resistance Monitoring). Consumption of antibiotics and occurrence of antibiotic resistance in Sweden. [Online] [Cited: March 31, 2016]. [Available online at [http://www.sva.se/en/antibiotika/svarm-reports] (last accessed on June 1, 2016).Google Scholar
Taskar, B and Getoor, L (2007). Introduction to Statistical Relational Learning. Cambridge, Mass: The MIT Press.Google Scholar
Timmerman, T, Dewulf, J, Catry, B, Feyen, B, Opsomer, G, de Kruif, A and Maes, D (2006). Quantification and evaluation of antimicrobial use in group treatments for fattening pigs in Belgium. Preventive Veterinary Medicine 74: 251–263.Google Scholar
Toutain, PL, Ferran, AA, Bousquet-Mélou, A, Pelligand, L and Lees, P (2016). Veterinary medicine needs new green antimicrobial drugs. Frontiers in Microbiology 7: 1196.Google Scholar
USDA APHIS NAHMS Beef Feedlot (2011a). Part I: Management practices on U.S. feedlots with a capacity of 1000 or more head. [Available online at http://www.aphis.usda.gov/animal_health/nahms/feedlot/downloads/feedlot2011/Feed11_dr_PartI.pdf] (Last accessed on June 1, 2016).Google Scholar
USDA APHIS NAHMS Beef Feedlot (2011b). Part III: Trends in health and management practices on U.S. feedlots, 1994–2011. [Available online at http://www.aphis.usda.gov/animal_health/nahms/feedlot/downloads/feedlot2011/Feed11_dr_Part%20III.pdf] (Last accessed on June 1, 2016).Google Scholar
USDA APHIS NAHMS Beef Feedlot (2011c). Part IV: Health and health management on U.S. feedlots with a capacity of 1,000 or more head report. [Available online at http://www.aphis.usda.gov/animal_health/nahms/feedlot/downloads/feedlot2011/Feed11_dr_PartIV.pdf] (Last accessed on June 1, 2016).Google Scholar
Varga, C, Rajic, A, McFall, ME, Reid-Smith, RJ, Deckert, AE, Checkley, SL and McEwen, SA (2009a). Associations between reported on-farm antimicrobial use practices and observed antimicrobial resistance in generic fecal Escherichia coli isolated from Alberta finishing swine farms. Preventive Veterinary Medicine 88: 185–192.CrossRefGoogle ScholarPubMed
Varga, C, Rajic, A, McFall, ME, Reid-Smith, RJ and McEwen, SA (2009b). Associations among antimicrobial use and antimicrobial resistance of Salmonella spp. isolates from 60 Alberta finishing swine farms. Foodborne Pathogens and Disease 6: 23–31.Google Scholar
Vieira, AR, Pires, SM, Houe, H and Emborg, HD (2011). Trends in slaughter pig production and antimicrobial consumption in Danish slaughter pig herds, 2002–2008. Epidemiology and Infection 139: 1601–1609.Google Scholar
Volkova, VV, Lanzas, C, Lu, Z and Gröhn, YT (2012). Mathematical model of plasmid-mediated resistance to ceftiofur in commensal enteric Escherichia coli of cattle. PLoS ONE 7: e36738.Google Scholar
Volkova, VV, KuKanich, B and Riviere, JE (2016). Exploring post-treatment reversion of antimicrobial resistance in enteric bacteria of food animals as a resistance mitigation strategy. Foodborne Pathogens and Disease 13: 610–617.Google Scholar
Wagner, BA, Salman, MD, Dargatz, DA, Morley, PS, Wittum, TE and Keefe, TJ (2003). Factor analysis of minimum-inhibitory concentrations for Escherichia coli isolated from feedlot cattle to model relationships among antimicrobial-resistance outcomes. Preventive Veterinary Medicine 57: 127–139.Google Scholar
Walker, TM, Kohl, TA, Omar, SV, Hedge, J, Del Ojo Elias, C, Bradley, P, Iqbal, Z, Feuerriegel, S, Niehaus, KE, Wilson, DJ, Clifton, DA, Kapatai, G, Ip, CL, Bowden, R, Drobniewski, FA, Allix-Béguec, C, Gaudin, C, Parkhill, J, Diel, R, Supply, P, Crook, DW, Smith, EG, Walker, AS, Ismail, N, Niemann, S, Peto, TE and Modernizing Medical Microbiology (MMM) Informatics Group (2015). Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. The Lancet Infectious Diseases 15: 1193–1202.Google Scholar
White House (2015). National Action Plan for Combating Antibiotic Resistant Bacteria. [Available online at https://www.whitehouse.gov/sites/default/files/docs/national_action_plan_for_combating_antibotic-resistant_bacteria.pdf]Google Scholar
Willmann, M, Marschal, M, Hölzl, F, Schröppel, K, Autenrieth, IB and Peter, S (2013). Time series analysis as a tool to predict the impact of antimicrobial restriction in antibiotic stewardship programs using the example of multidrug-resistant Pseudomonas aeruginosa . Antimicrobial Agents and Chemotherapy 57: 1797–1803.Google Scholar
World Health Organization (2015). Global Action Plan on Antimicrobial Resistance. [Available online at http://apps.who.int/iris/bitstream/10665/193736/1/9789241509763_eng.pdf?ua=1]Google Scholar
Yang, Z and Nielsen, R (2000). Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Molecular Biology and Evolution 1: 32–43.Google Scholar
Zawack, K, Li, M, Booth, JG, Love, W, Lanzas, C and Gröhn, YT (2016). Monitoring antimicrobial resistance in the food supply chain and its implications for FDA policy initiatives. Antimicrobial Agents and Chemotherapy 60: 5302–5311.Google Scholar
Zhao, S, Tyson, GH, Chen, Y, Li, C, Mukherjee, S, Young, S, Lam, C, Folster, JP, Whichard, JM and McDermott, PF (2015). Whole-genome sequencing analysis accurately predicts antimicrobial resistance phenotypes in Campylobacter spp. Applied and Environmental Microbiology 82: 459–466.CrossRefGoogle ScholarPubMed