Chapter 29 : Source Attribution and Risk Assessment of Antimicrobial Resistance

MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.

Preview this chapter:
Zoom in

Source Attribution and Risk Assessment of Antimicrobial Resistance, Page 1 of 2

| /docserver/preview/fulltext/10.1128/9781555819804/9781555819798_Chap29-1.gif /docserver/preview/fulltext/10.1128/9781555819804/9781555819798_Chap29-2.gif


Antimicrobial use in humans and animals has been identified as a main driver of antimicrobial resistance (AMR), and bacteria harboring resistance to antimicrobials can be found in humans, animals, foods, and the environment. As a consequence, humans can be exposed to antimicrobial-resistant bacteria through a wide range of sources and transmission pathways. To inform policies aimed at reducing the burden of AMR in animals and foods, risk managers need evidence about the most important sources and transmission routes and the critical points throughout the production chain for the prevention and control of AMR. While this process is complex and deeply reliant on the integration of surveillance data from humans, animals, and foods, it is supported by scientific disciplines that have evolved rapidly in the past decades, including source attribution and quantitative risk assessment.

Citation: Pires S, Duarte A, Hald T. 2018. Source Attribution and Risk Assessment of Antimicrobial Resistance, p 619-635. In Schwarz S, Cavaco L, Shen J (ed), Antimicrobial Resistance in Bacteria from Livestock and Companion Animals. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.ARBA-0027-2017
Highlighted Text: Show | Hide
Loading full text...

Full text loading...


Image of Figure 1
Figure 1

Routes of transmission of zoonotic pathogens and points of source attribution. Adapted from reference .

Citation: Pires S, Duarte A, Hald T. 2018. Source Attribution and Risk Assessment of Antimicrobial Resistance, p 619-635. In Schwarz S, Cavaco L, Shen J (ed), Antimicrobial Resistance in Bacteria from Livestock and Companion Animals. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.ARBA-0027-2017
Permissions and Reprints Request Permissions
Download as Powerpoint


1. Pires SM,, Evers EG,, van Pelt W,, Ayers T,, Scallan E,, Angulo FJ,, Havelaar A,, Hald T,, Schroeter A,, Brisabois A,, Thebault A,, Käsbohrer A,, Schroeder C,, Frank C,, Guo C,, Wong DLF,, Döpfer D,, Snary E,, Nichols G,, Spitznagel H,, Wahlström H,, David J,, Pancer K,, Stark K,, Forshell LP,, Nally P,, Sanders P,, Hiller P, Med-Vet-Net Workpackage 28 Working Group . 2009. Attributing the human disease burden of foodborne infections to specific sources. Foodborne Pathog Dis 6 : 417 424.[CrossRef][PubMed]
2. Mullner P,, Jones G,, Noble A,, Spencer SEF,, Hathaway S,, French NP . 2009. Source attribution of food-borne zoonoses in New Zealand: a modified Hald model. Risk Anal 29 : 970 984.[CrossRef][PubMed]
3. Hald T,, Vose D,, Wegener HC,, Koupeev T . 2004. A Bayesian approach to quantify the contribution of animal-food sources to human salmonellosis. Risk Anal 24 : 255 269.[CrossRef][PubMed]
4. de Knegt LV,, Pires SM,, Hald T . 2015. Using surveillance and monitoring data of different origins in a Salmonella source attribution model: a European Union example with challenges and proposed solutions. Epidemiol Infect 143 : 1148 1165.[CrossRef][PubMed]
5. Pires SM,, Vigre H,, Makela P,, Hald T . 2010. Using outbreak data for source attribution of human salmonellosis and campylobacteriosis in Europe. Foodborne Pathog Dis 7 : 1351 1361.[CrossRef][PubMed]
6. Guo C,, Hoekstra RM,, Schroeder CM,, Pires SM,, Ong KL,, Hartnett E,, Naugle A,, Harman J,, Bennett P,, Cieslak P,, Scallan E,, Rose B,, Holt KG,, Kissler B,, Mbandi E,, Roodsari R,, Angulo FJ,, Cole D . 2011. Application of Bayesian techniques to model the burden of human salmonellosis attributable to U.S. food commodities at the point of processing: adaptation of a Danish model. Foodborne Pathog Dis 8 : 509 516.[CrossRef][PubMed]
7. Pires SM,, Evers EG,, van Pelt W,, Ayers T,, Scallan E,, Angulo FJ,, Havelaar A,, Hald T, Med-Vet-Net Workpackage 28 Working Group . 2009. Attributing the human disease burden of foodborne infections to specific sources. Foodborne Pathog Dis 6 : 417 424.[CrossRef][PubMed]
8. FAO . 1999. Principles and Guidelines for the Conduct of Microbiological Risk Assessment. FAO, Rome, Italy.
9. Office International des Epizooties . 2002. International Animal Health Code, eleventh edition. Rue de Prony 12, 75017 Paris, France.
10. USDA . 2012. Microbial Risk Assessment Guideline: Pathogenic Microorganisms with Focus on Food and Water. Prepared by the Interagency Microbiological Risk Assessment Guideline Workgroup Microbial Risk Assessment Guideline. US Department of Agriculture, Washington, DC.
11. Wegener HC . 2010. Danish initiatives to improve the safety of meat products. Meat Sci 84 : 276 283.[CrossRef][PubMed]
12. Snary EL,, Swart AN,, Hald T . 2016. Quantitative microbiological risk assessment and source attribution for Salmonella: taking it further. Risk Anal 36 : 433 436.[CrossRef][PubMed]
13. Lester CH,, Frimodt-Møller N,, Sørensen TL,, Monnet DL,, Hammerum AM . 2006. In vivo transfer of the vanA resistance gene from an Enterococcus faecium isolate of animal origin to an E. faecium isolate of human origin in the intestines of human volunteers. Antimicrob Agents Chemother 50 : 596 599.[CrossRef][PubMed]
14. Aarestrup FM . 2015. The livestock reservoir for antimicrobial resistance: a personal view on changing patterns of risks, effects of interventions and the way forward. Philos Trans R Soc Lond B Biol Sci 370 : 20140085.[CrossRef][PubMed]
15. Hald T,, Lo Fo Wong DM,, Aarestrup FM . 2007. The attribution of human infections with antimicrobial resistant Salmonella bacteria in Denmark to sources of animal origin. Foodborne Pathog Dis 4 : 313 326.[CrossRef][PubMed]
16. Vieira AR,, Grass J,, Fedorka-Cray PJ,, Plumblee JR,, Tate H,, Cole DJ . 2016. Attribution of Salmonella enterica serotype Hadar infections using antimicrobial resistance data from two points in the food supply system. Epidemiol Infect 144 : 1983 1990.[CrossRef][PubMed]
17. Evers EG,, Pielaat A,, Smid JH,, van Duijkeren E,, Vennemann FBC,, Wijnands LM,, Chardon JE . 2017. Comparative exposure assessment of ESBL-producing Escherichia coli through meat consumption. PLoS One 12 : e0169589.[CrossRef][PubMed]
18. Barco L,, Barrucci F,, Olsen JE,, Ricci A . 2013. Salmonella source attribution based on microbial subtyping. Int J Food Microbiol 163 : 193 203.[CrossRef][PubMed]
19. Mughini-Gras L,, Barrucci F,, Smid JH,, Graziani C,, Luzzi I,, Ricci A,, Barco L,, Rosmini R,, Havelaar AH,, Van Pelt W,, Busani L . 2014. Attribution of human Salmonella infections to animal and food sources in Italy (2002–2010): adaptations of the Dutch and modified Hald source attribution models. Epidemiol Infect 142 : 1070 1082.[CrossRef][PubMed]
20. Wilson DJ,, Gabriel E,, Leatherbarrow AJH,, Cheesbrough J,, Gee S,, Bolton E,, Fox A,, Fearnhead P,, Hart CA,, Diggle PJ . 2008. Tracing the source of campylobacteriosis. PLoS Genet 4 : e1000203.[CrossRef][PubMed]
21. Pires SM,, Vieira AR,, Hald T,, Cole D . 2014. Source attribution of human salmonellosis: an overview of methods and estimates. Foodborne Pathog Dis 11 : 667 676.[CrossRef][PubMed]
22. de Knegt LV,, Pires SM,, Löfström C,, Sørensen G,, Pedersen K,, Torpdahl M,, Nielsen EM,, Hald T . 2016. Application of molecular typing results in source attribution models: the case of multiple locus variable number tandem repeat analysis (MLVA) of Salmonella isolates obtained from integrated surveillance in Denmark. Risk Anal 36 : 571 588.[CrossRef][PubMed]
23. Boysen L,, Rosenquist H,, Larsson JT,, Nielsen EM,, Sørensen G,, Nordentoft S,, Hald T . 2014. Source attribution of human campylobacteriosis in Denmark. Epidemiol Infect 142 : 1599 1608.[PubMed]
24. Mullner P,, Spencer SEF,, Wilson DJ,, Jones G,, Noble AD,, Midwinter AC,, Collins-Emerson JM,, Carter P,, Hathaway S,, French NP . 2009. Assigning the source of human campylobacteriosis in New Zealand: a comparative genetic and epidemiological approach. Infect Genet Evol 9 : 1311 1319.[CrossRef][PubMed]
25. Little CL,, Pires SM,, Gillespie IA,, Grant K,, Nichols GL . 2010. Attribution of human Listeria monocytogenes infections in England and Wales to ready-to-eat food sources placed on the market: adaptation of the Hald Salmonella source attribution model. Foodborne Pathog Dis 7 : 749 756.[CrossRef][PubMed]
26. Mughini-Gras L,, van Pelt W,, van der Voort M,, Heck M,, Friesema I,, Franz E . 2018. Attribution of human infections with Shiga toxin-producing Escherichia coli (STEC) to livestock sources and identification of source-specific risk factors, The Netherlands (2010–2014). Zoonoses Public Health 65 : e8 e22.[PubMed]
27. Evers EG,, Van Der Fels-Klerx HJ,, Nauta MJ,, Schijven JF,, Havelaar AH . 2008. Campylobacter source attribution by exposure assessment. Int J Risk Assess Manag 8 : 174.[CrossRef]
28. Kosmider RD,, Nally P,, Simons RRL,, Brouwer A,, Cheung S,, Snary EL,, Wooldridge M . 2010. Attribution of human VTEC O157 infection from meat products: a quantitative risk assessment approach. Risk Anal 30 : 753 765.[CrossRef][PubMed]
29. Opsteegh M,, Prickaerts S,, Frankena K,, Evers EG . 2011. A quantitative microbial risk assessment for meatborne Toxoplasma gondii infection in The Netherlands. Int J Food Microbiol 150 : 103 114.[CrossRef][PubMed]
30. FDA . 2003. Quantitative assessment of relative risk to public health from foodborne Listeria monocytogenes among selected categories of ready-to-eat foods. Summary of public comments and FDA/FSIS revisions to risk assessment. https://www.fda.gov/Food/FoodScienceResearch/RiskSafetyAssessment/ucm183966.htm.
31. EFSA . 2009. Scientific opinion: cadmium in food. Scientific opinion of the Panel on Contaminants in the Food Chain. EFSA J 980 : 1139.
32. EFSA . 2010. Scientific opinion on lead in food. EFSA J 8 : 1570.[CrossRef]
33. Cassini A,, Hathaway S,, Havelaar A,, Koopmans M,, Koutsoumanis K,, Messens W,, Müller-Seitz G,, Nørrung B,, Rizzi V,, Scheutz F . 2016. Microbiological risk assessment. EFSA J 14 : 1 10.[CrossRef]
34. EFSA . 2007. Opinion of the scientific panel on contaminants in the food chain [CONTAM] related to the potential increase of consumer health risk by a possible increase of the existing maximum levels for aflatoxins in almonds, hazelnuts and pistachios and derived products. EFSA J 5 : 446.[CrossRef]
35. Carmo LP,, Nielsen LR,, da Costa PM,, Alban L . 2014. Exposure assessment of extended-spectrum beta-lactamases/AmpC beta-lactamases-producing Escherichia coli in meat in Denmark. Infect Ecol Epidemiol 4 : 1 10.[CrossRef][PubMed]
36. Olsen SJ,, MacKinnon LC,, Goulding JS,, Bean NH,, Slutsker L . 2000. Surveillance for foodborne-disease outbreaks: United States, 1993–1997. MMWR CDC Surveill Summ 49 : 1 62.[PubMed]
37. Neimann J,, Engberg J,, Mølbak K,, Wegener HC . 2003. A case-control study of risk factors for sporadic campylobacter infections in Denmark. Epidemiol Infect 130 : 353 366.[CrossRef][PubMed]
38. Painter JA,, Ayers T,, Woodruff R,, Blanton E,, Perez N,, Hoekstra RM,, Griffin PM,, Braden C . 2009. Recipes for foodborne outbreaks: a scheme for categorizing and grouping implicated foods. Foodborne Pathog Dis 6 : 1259 1264.[CrossRef][PubMed]
39. Pires SM,, Vigre H,, Makela P,, Hald T . 2010. Using outbreak data for source attribution of human salmonellosis and campylobacteriosis in Europe. Foodborne Pathog Dis 7 : 1351 1361.[CrossRef][PubMed]
40. Painter JA,, Hoekstra RM,, Ayers T,, Tauxe RV,, Braden CR,, Angulo FJ,, Griffin PM . 2013. Attribution of foodborne illnesses, hospitalizations, and deaths to food commodities by using outbreak data, United States, 1998–2008. Emerg Infect Dis 19 : 407 415.[CrossRef][PubMed]
41. Pires SM,, Vieira AR,, Perez E,, Lo Fo Wong D,, Hald T . 2012. Attributing human foodborne illness to food sources and water in Latin America and the Caribbean using data from outbreak investigations. Int J Food Microbiol 152 : 129 138.[CrossRef][PubMed]
42. Ravel A,, Greig J,, Tinga C,, Todd E,, Campbell G,, Cassidy M,, Marshall B,, Pollari F . 2009. Exploring historical Canadian foodborne outbreak data sets for human illness attribution. J Food Prot 72 : 1963 1976.[CrossRef][PubMed]
43. King N,, Lake R,, Campbell D . 2011. Source attribution of nontyphoid salmonellosis in New Zealand using outbreak surveillance data. J Food Prot 74 : 438 445.[CrossRef][PubMed]
44. Jones TF,, Kellum ME,, Porter SS,, Bell M,, Schaffner W . 2002. An outbreak of community-acquired foodborne illness caused by methicillin-resistant Staphylococcus aureus. Emerg Infect Dis 8 : 82 84.[CrossRef]
45. Mølbak K,, Baggesen DL,, Aarestrup FM,, Ebbesen JM,, Engberg J,, Frydendahl K,, Gerner-Smidt P,, Petersen AM,, Wegener HC . 1999. An outbreak of multidrug-resistant, quinolone-resistant Salmonella enterica serotype typhimurium DT104. N Engl J Med 341 : 1420 1425.[CrossRef][PubMed]
46. Brown AC,, Grass JE,, Richardson LC,, Nisler AL,, Bicknese AS,, Gould LH . 2017. Antimicrobial resistance in Salmonella that caused foodborne disease outbreaks: United States, 2003–2012. Epidemiol Infect 145 : 766 774.[CrossRef][PubMed]
47. Engberg J . 2006. Contributions to the epidemiology of Campylobacter infections: a review of clinical and microbiological studies. Dan Med Bull 53 : 361 389.[PubMed]
48. Domingues AR,, Pires SM,, Halasa T,, Hald T . 2012. Source attribution of human campylobacteriosis using a meta-analysis of case-control studies of sporadic infections. Epidemiol Infect 140 : 970 981.[CrossRef][PubMed]
49. Pires SM . 2013. Assessing the applicability of currently available methods for attributing foodborne disease to sources, including food and food commodities. Foodborne Pathog Dis 10 : 206 213.[CrossRef][PubMed]
50. Varma JK,, Marcus R,, Stenzel SA,, Hanna SS,, Gettner S,, Anderson BJ,, Hayes T,, Shiferaw B,, Crume TL,, Joyce K,, Fullerton KE,, Voetsch AC,, Angulo FJ . 2006. Highly resistant Salmonella Newport-MDRAmpC transmitted through the domestic US food supply: a FoodNet case-control study of sporadic Salmonella Newport infections, 2002–2003. J Infect Dis 194 : 222 230.[CrossRef][PubMed]
51. Kassenborg HD,, Smith KE,, Vugia DJ,, Rabatsky-Ehr T,, Bates MR,, Carter MA,, Dumas NB,, Cassidy MP,, Marano N,, Tauxe RV,, Angulo FJ, Emerging Infections Program FoodNet Working Group . 2004. Fluoroquinolone-resistant Campylobacter infections: eating poultry outside of the home and foreign travel are risk factors. Clin Infect Dis 38( Suppl 3) : S279 S284.[CrossRef][PubMed]
52. Havelaar AH,, Galindo AV,, Kurowicka D,, Cooke RM . 2008. Attribution of foodborne pathogens using structured expert elicitation. Foodborne Pathog Dis 5 : 649 659.[CrossRef][PubMed]
53. Ravel A,, Davidson VJ,, Ruzante JM,, Fazil A . 2010. Foodborne proportion of gastrointestinal illness: estimates from a Canadian expert elicitation survey. Foodborne Pathog Dis 7 : 1463 1472.[CrossRef][PubMed]
54. Hald T,, Aspinall W,, Devleesschauwer B,, Cooke R,, Corrigan T,, Havelaar AH,, Gibb HJ,, Torgerson PR,, Kirk MD,, Angulo FJ,, Lake RJ,, Speybroeck N,, Hoffmann S . 2016. World Health Organization estimates of the relative contributions of food to the burden of disease due to selected foodborne hazards: a structured expert elicitation. PLoS One 11 : e0145839.[CrossRef][PubMed]
55. Cooke R . 1991. Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press, Oxford, UK.
56. Anonymous . 2017. Annual Report on Zoonoses in Denmark 2016. National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark.
57. Kim H,, Kim YA,, Park YS,, Choi MH,, Lee GI,, Lee K . 2017. Risk factors and molecular features of sequence type (ST) 131 extended-spectrum β-lactamase-producing Escherichia coli in community-onset bacteremia. Sci Rep 7 : 14640.[CrossRef][PubMed]
58. Vos T,, Barber RM,, Bell B,, Bertozzi-Villa A,, Biryukov S,, Bolliger I,, Charlson F,, Davis A,, Degenhardt L,, Dicker D,, Duan L,, Erskine H,, Feigin VL,, Ferrari AJ,, Fitzmaurice C,, Fleming T,, Graetz N,, Guinovart C,, Haagsma J,, Hansen GM,, Hanson SW,, Heuton KR,, Higashi H,, Kassebaum N,, Kyu H,, Laurie E,, Liang X,, Lofgren K,, Lozano R,, MacIntyre MF,, Moradi-Lakeh M,, Naghavi M,, Nguyen G,, Odell S,, Ortblad K,, Roberts DA,, Roth GA,, Sandar L,, Serina PT,, Stanaway JD,, Steiner C,, Thomas B,, Vollset SE,, Whiteford H,, Wolock TM,, Ye P,, Zhou M,, Ãvila MA,, Aasvang GM,, Abbafati C, , et al . 2015. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386 : 743 800.[PubMed]
59. Harb A,, O’Dea M,, Hanan ZK,, Abraham S,, Habib I . 2017. Prevalence, risk factors and antimicrobial resistance of Salmonella diarrhoeal infection among children in Thi-Qar Governorate, Iraq. Epidemiol Infect 145 : 3486 3496.[CrossRef][PubMed]
60. Loman NJ,, Constantinidou C,, Christner M,, Rohde H,, Chan JZ-M,, Quick J,, Weir JC,, Quince C,, Smith GP,, Betley JR,, Aepfelbacher M,, Pallen MJ . 2013. A culture-independent sequence-based metagenomics approach to the investigation of an outbreak of Shiga-toxigenic Escherichia coli O104:H4. JAMA 309 : 1502 1510.[CrossRef][PubMed]
61. Aarestrup FM,, Seyfarth AM,, Emborg HD,, Pedersen K,, Hendriksen RS,, Bager F . 2001. Effect of abolishment of the use of antimicrobial agents for growth promotion on occurrence of antimicrobial resistance in fecal enterococci from food animals in Denmark. Antimicrob Agents Chemother 45 : 2054 2059.[CrossRef][PubMed]
62. Jensen VF,, de Knegt LV,, Andersen VDWA,, Wingstrand A . 2014. Temporal relationship between decrease in antimicrobial prescription for Danish pigs and the “Yellow Card” legal intervention directed at reduction of antimicrobial use. Prev Vet Med 117 : 554 564.[CrossRef][PubMed]
63. Agersø Y,, Aarestrup FM . 2013. Voluntary ban on cephalosporin use in Danish pig production has effectively reduced extended-spectrum cephalosporinase-producing Escherichia coli in slaughter pigs. J Antimicrob Chemother 68 : 569 572.[CrossRef][PubMed]
64. Alban L,, Olsen AM,, Nielsen B,, Sørensen R,, Jessen B, OIE . 2002. Qualitative and quantitative risk assessment for human salmonellosis due to multi-resistant Salmonella Typhimurium DT104 from consumption of Danish dry-cured pork sausages. Prev Vet Med 52 : 251 265.[CrossRef]
65. Claycamp HG,, Hooberman BH . 2004. Antimicrobial resistance risk assessment in food safety. J Food Prot 67 : 2063 2071.[CrossRef][PubMed]
66. Snary EL,, Kelly LA,, Davison HC,, Teale CJ,, Wooldridge M . 2004. Antimicrobial resistance: a microbial risk assessment perspective. J Antimicrob Chemother 53 : 906 917.[CrossRef][PubMed]
67. Salisbury JG,, Nicholls TJ,, Lammerding AM,, Turnidge J,, Nunn MJ . 2002. A risk analysis framework for the long-term management of antibiotic resistance in food-producing animals. Int J Antimicrob Agents 20 : 153 164.[PubMed]
68. Manaia CM . 2017. Assessing the risk of antibiotic resistance transmission from the environment to humans: non-direct proportionality between abundance and risk. Trends Microbiol 25 : 173 181.[CrossRef][PubMed]
69. Bezoen A,, Van Haren W,, Hanekamp JC . 1999. Emergence of a Debate: AGPs and Public Health. HAN, Amsterdam, The Netherlands.
70. WHO . 2016. Critically Important Antimicrobials for Human Medicine, 5th revision. WHO, Geneva, Switzerland.
71. Collineau L,, Carmo LP,, Endimiani A,, Magouras I,, Müntener C,, Schüpbach-Regula G,, Stärk KDC . 2017. Risk ranking of antimicrobial-resistant hazards found in meat in Switzerland. Risk Anal.[CrossRef][PubMed]
72. Bartholomew MJ,, Vose DJ,, Tollefson LR,, Travis CC . 2005. A linear model for managing the risk of antimicrobial resistance originating in food animals. Risk Anal 25 : 99 108.[CrossRef][PubMed]
73. CVMP . 2013. Guideline on the assessment of the risk to public health from antimicrobial resistance due to the use of an antimicrobial VMPs in food-producing animals. Available at http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2015/03/WC500183774.pdf.
74. Martínez JL,, Coque TM,, Baquero F . 2015. What is a resistance gene? Ranking risk in resistomes. Nat Rev Microbiol 13 : 116 123.[CrossRef][PubMed]
75. Buchanan RL,, Smith JL,, Long W . 2000. Microbial risk assessment: dose-response relations and risk characterization. Int J Food Microbiol 58 : 159 172.[CrossRef][PubMed]
76. Lammerding AM,, Fazil A . 2000. Hazard identification and exposure assessment for microbial food safety risk assessment. Int J Food Microbiol 58 : 147 157.[CrossRef][PubMed]
77. Nauta MJ, . 2008. The modular process risk model (MPRM): a structured approach to food chain exposure assessment, p 99 136. In Schaffner DW (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC.
78. Waltner-Toews D,, McEwen SA . 1994. Residues of antibacterial and antiparasitic drugs in foods of animal origin: a risk assessment. Prev Vet Med 20 : 219 234.[CrossRef]
79. Anonymous . 2014. MRSA risk assessment. Prepared by the MRSA expert group. Available at https://www.foedevarestyrelsen.dk/english/SiteCollectionDocuments/Dyresundhed/Rapport_fra_MRSA-ekspertgruppe%20EN.pdf.
80. Alban L,, Ellis-Iversen J,, Andreasen M,, Dahl J,, Sönksen UW . 2017. Assessment of the risk to public health due to use of antimicrobials in pigs: an example of pleuromutilins in Denmark. Front Vet Sci 4 : 74.[CrossRef][PubMed]
81. Alban L,, Nielsen EO,, Dahl J . 2008. A human health risk assessment for macrolide-resistant Campylobacter associated with the use of macrolides in Danish pig production. Prev Vet Med 83 : 115 129.[CrossRef][PubMed]
82. FDA . 2000. Human health impact of fluoroquinolone resistant campylobacter attributed to the consumption of chicken. Food and Drug Administration Center for Veterinary Medicine, Rockville, MD.
83. Nelson JM,, Chiller TM,, Powers JH,, Angulo FJ . 2007. Fluoroquinolone-resistant Campylobacter species and the withdrawal of fluoroquinolones from use in poultry: a public health success story. Clin Infect Dis 44 : 977 980.[CrossRef][PubMed]
84. Anderson SA,, Woo RWY,, Crawford LM . 2001. Risk assessment of the impact on human health of resistant Campylobacter jejuni from fluoroquinolone use in beef cattle. Food Control 12 : 13 25.
85. FDA . 2003. Guidance for industry #152: evaluating the safety of antimicrobial new animal drugs with regard to their microbiological effects on bacteria of human health concern. Food and Drug Administration Center for Veterinary Medicine, Rockville, MD.
86. Hurd HS,, Doores S,, Hayes D,, Mathew A,, Maurer J,, Silley P,, Singer RS,, Jones RN . 2004. Public health consequences of macrolide use in food animals: a deterministic risk assessment. J Food Prot 67 : 980 992.[CrossRef][PubMed]
87. Hurd HS,, Vaughn MB,, Holtkamp D,, Dickson J,, Warnick L . 2010. Quantitative risk from fluoroquinolone-resistant Salmonella and Campylobacter due to treatment of dairy heifers with enrofloxacin for bovine respiratory disease. Foodborne Pathog Dis 7 : 1305 1322.[PubMed]
88. Rico A,, Jacobs R,, Van den Brink PJ,, Tello A . 2017. A probabilistic approach to assess antibiotic resistance development risks in environmental compartments and its application to an intensive aquaculture production scenario. Environ Pollut 231 : 918 928.[CrossRef][PubMed]
89. Chaillou S,, Chaulot-Talmon A,, Caekebeke H,, Cardinal M,, Christieans S,, Denis C,, Desmonts MH,, Dousset X,, Feurer C,, Hamon E,, Joffraud J-J,, La Carbona S,, Leroi F,, Leroy S,, Lorre S,, Macé S,, Pilet M-F,, Prévost H,, Rivollier M,, Roux D,, Talon R,, Zagorec M,, Champomier-Vergès M-C . 2015. Origin and ecological selection of core and food-specific bacterial communities associated with meat and seafood spoilage. ISME J 9 : 1105 1118.[CrossRef][PubMed]
90. De Filippis F,, La Storia A,, Villani F,, Ercolini D . 2013. Exploring the sources of bacterial spoilers in beefsteaks by culture-independent high-throughput sequencing. PLoS One 8 : e70222.[CrossRef][PubMed]
91. Brul S,, Bassettb J,, Cookc P . 2012. “Omics” technologies in quantitative microbial risk assessment. Trends Food Sci Technol 27 : 12 24.[CrossRef]
92. McEwen SA,, Singer RS . 2006. Stakeholder position paper: the need for antimicrobial use data for risk assessment. Prev Vet Med 73 : 169 176.[CrossRef][PubMed]
93. Madsen AM,, Hodge SE,, Ottman R . 2011. Causal models for investigating complex disease. I. A primer. Hum Hered 72 : 54 62.[CrossRef][PubMed]
94. den Besten HMW,, Amézquita A,, Bover-Cid S,, Dagnas S,, Ellouze M,, Guillou S,, Nychas G,, O’Mahony C,, Pérez-Rodriguez F,, Membré J-M . 2017. Next generation of microbiological risk assessment: potential of omics data for exposure assessment. Int J Food Microbiol. [Epub ahead of print.][CrossRef][PubMed]
95. Nadon C,, Van Walle I,, Gerner-Smidt P,, Campos J,, Chinen I,, Concepcion-Acevedo J,, Gilpin B,, Smith AM,, Man Kam K,, Perez E,, Trees E,, Kubota K,, Takkinen J,, Nielsen EM,, Carleton H, FWD-NEXT Expert Panel . 2017. PulseNet International: vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance. Euro Surveill 22 : 30544.[CrossRef][PubMed]


Generic image for table
Table 1

Definition, overview of methods and main challenges of source attribution and microbial risk assessment approaches

Citation: Pires S, Duarte A, Hald T. 2018. Source Attribution and Risk Assessment of Antimicrobial Resistance, p 619-635. In Schwarz S, Cavaco L, Shen J (ed), Antimicrobial Resistance in Bacteria from Livestock and Companion Animals. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.ARBA-0027-2017

This is a required field
Please enter a valid email address
Please check the format of the address you have entered.
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error