title: A quantitative risk assessment model for Salmonella and whole chickens.
abstract: Existing data and predictive models were used to define the input settings of a previously developed but modified quantitative risk assessment model (QRAM) for Salmonella and whole chickens. The QRAM was constructed in an Excel spreadsheet and was simulated using @Risk. The retail-to-table pathway was modeled as a series of unit operations and associated pathogen events that included initial contamination at retail, growth during consumer transport, thermal inactivation during cooking, cross-contamination during serving, and dose response after consumption. Published data as well as predictive models for growth and thermal inactivation of Salmonella were used to establish input settings. Noncontaminated chickens were simulated so that the QRAM could predict changes in the incidence of Salmonella contamination. The incidence of Salmonella contamination changed from 30% at retail to 0.16% after cooking to 4% at consumption. Salmonella growth on chickens during consumer transport was the only pathogen event that did not impact the risk of salmonellosis. For the scenario simulated, the QRAM predicted 0.44 cases of salmonellosis per 100,000 consumers, which was consistent with recent epidemiological data that indicate a rate of 0.66-0.88 cases of salmonellosis per 100,000 consumers of chicken. Although the QRAM was in agreement with the epidemiological data, surrogate data and models were used, assumptions were made, and potentially important unit operations and pathogen events were not included because of data gaps and thus, further refinement of the QRAM is needed.
authors.affiliation: Microbial Food Safety Research Unit, Agricultural Research Service, United States Department of Agriculture, University of Maryland Eastern Shore, 1124 Trigg Hall, Princess Anne, MD 21853, USA. toscar@umes.edu
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Oscar
mesh_terms: D000818:Animals; D002645:Chickens / Q000382:microbiology*; D003257:Consumer Product Safety; D005506:Food Contamination / Q000032:analysis*; D005516:Food Microbiology; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D018570:Risk Assessment; D012475:Salmonella / Q000302:isolation & purification*; D012478:Salmonella Food Poisoning / Q000209:etiology / Q000382:microbiology