A SIMULATION MODEL TO QUANTIFY THE EFFICACY OF DRY CLEANING INTERVENTIONS ON A CONTAMINATED MILK POWDER LINE

Abstract

Outbreaks of Salmonella and other pathogens associated with low moisture foods have been caused by cross-contamination from the processing environment into product. We used Monte Carlo simulations to model the impact of hypothetical cross-contamination scenarios of Salmonella from production equipment into milk powder. Model outputs include the quantity and extent of contaminated product from a production line, which can be useful for comparing the efficacy of different cleaning interventions. We also modeled the cross-contamination of potential dry cleaning surrogates to see how they responded to cleaning interventions in comparison to Salmonella. Input parameters for the model included log reductions from wiping an inoculated surface with a dry towel and transfer coefficients from an inoculated surface into milk powder that were measured experimentally and fitted to probability distributions. After a 2 log CFU contamination breach, the number of consumer size milk powder units (300 g) contaminated with Salmonella was 72 [24, 96] (median [p5, p95] across 1000 simulation iterations). The average concentration of Salmonella within contaminated units was -2.33 log CFU/g [-2.46, -1.86]. Wiping with a dry towel reduced the number of contaminated units to 26 [12, 64]. After product flushing with 150 kg of milk powder, the number of contaminated units dropped to 0 [0, 41]. E. faecium was the most appropriate surrogate for Salmonella transfer from surface to milk powder, while L. innocua was a more appropriate surrogate for the dry towel wiping intervention. These results suggest that product flushing, and to a lesser degree dry wiping, may be effective interventions in reducing contaminated milk powder product after a contamination breach. Further, simulation modeling is a useful tool for evaluating Salmonella dry transfer surrogates for their use in dry cleaning validation and modeling applications.