Models of Antimicrobial Resistance and Foodborne Illness: Examining Assumptions and Practical Applications

Abstract

Antimicrobial resistance is an issue of increasing global concern. Several investigators have suggested that antibiotic use in food-producing animals is a major contributor to the increasing incidence of antimicrobial-resistant organisms causing illness in humans (F. J. Angulo, K. R. Johnson, R. V. Tauxe, and M. L. Cohen, Microb. Drug Res. 6:77–83, 2000; P. D. Fey, T. J. Safranek, M. E. Rupp, E. F. Dunne, R. Efrain, P. C. Iwen, P. A. Bradford, F. J. Angulo, and S. H. Hinrichs, N. Engl. J. Med. 342:1242–1249, 2000; S. A. McEwen and P. J. Fedorka-Cray, Commun. Infect. Dis. 34(Suppl. 3):S93–S106, 2002; D. L. Smith, A. D. Harris, J. A. Johnson, E. K. Silbergeld, and J. G. Morris, Jr., Proc. Natl. Acad. Sci. USA 99:6434–6439, 2002; D. G. White, S. Zhao, R. Sudler, S. Ayers, S. Friedman, S. Chen, P. F. McDermott, D. D. Wagner, and J. Meng, N. Engl. J. Med. 345:1147–1154, 2001; W. Witte, Science 279:996, 1998). In this paper, we discuss this and other assumptions relevant to a quantitative risk assessment model for salmonellosis in humans. We also discuss other important aspects of modeling food safety and food-associated antimicrobial resistance risk to humans. We suggest that the role of food-producing animals in the origin and transmission of antimicrobial resistance and “foodborne” pathogens has been overestimated and overemphasized in the scientific literature; consequently, nonfoodborne transmission, including pet-associated human cases, has been underemphasized. Much evidence exists for the potential contribution to infectious disease that may be of human or pet origin (that may contact humans through food but not be of a food origin). Risk analyses that do not acknowledge the potential for these sources of cross-contamination will understate the contribution that origin has in the realm of foodborne and food-associated diseases (e.g., Salmonella) and the resulting uncertainty levels in the food system, thus leading to biased inferences. We emphasize the importance of evaluating both the foodborne and nonfoodborne transmission risk for salmonellosis and outline the basics of an analytical modeling approach in food safety with examples to illustrate strengths and limitations in the modeling. Examples illustrate, on a simplistic level, how varying assumptions and other inputs can influence the output of food-associated quantitative risk models.