Process risk model for Salmonella and ground chicken

AIMS: To develop a process risk model (PRM) for evaluating the safety of individual lots of ground chicken (GC) contaminated with Salmonella (Salm). METHODS AND RESULTS: Data for prevalence, number and serotype of Salm were collected with 25 g samples of GC using a combination of methods (whole sample enrichment, quantitative polymerase chain reaction, cultural isolation and serotyping). These data were used to develop a predictive model for Salm contamination of GC as a function of serving size from 25 to 300 g. This model was combined with a model for thermal inactivation of Salm in GC and a dose–response model for Salm to develop a PRM in Excel that was simulated with NeuralTools and @Risk. Of 100, 25 g samples of GC examined, 19 tested positive for Salm. Three serotypes were isolated: Infantis (n = 13), Enteritidis (n = 5) and Typhimurium (n = 1). The number of Salm ranged from 0 to 2·56 log with a median of 0·93 log per 25 g of GC. The PRM predicted that Salm prevalence would increase (P < 0·05) from 19 to 57% to 82 to 93% as serving size increased from 25 to 100 g to 200 to 300 g. However, the total number of Salm in a 100‐kg lot of GC and total severity of illness (TSI) were not affected (P> 0·05) by serving size. The PRM was also used to evaluate effects of serving size distribution, cooking, food consumption behaviour, consumer demographics and Salmonella virulence on TSI. CONCLUSIONS: How a lot of GC is partitioned and consumed does not affect TSI. Scenario analysis demonstrated that the PRM can integrate prevalence, number and serotype data for Salm with consumer handling, consumption and demographics data to identify safe and unsafe lots of GC for improved food safety and public health. SIGNIFICANCE AND IMPACT OF THE STUDY: Process‐risk models like the one developed in this study represent a new, holistic approach to food safety that holds great promise for improving public health and reducing food recalls.