Outbreaks ofSalmonellaand 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 ofSalmonellafrom 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 toSalmonella. 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 withSalmonellawas 72 [24, 96] (median [p5, p95] across 1000 simulation iterations). The average concentration ofSalmonellawithin 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. faeciumwas the most appropriate surrogate forSalmonellatransfer from surface to milk powder, whileL. innocuawas 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 evaluatingSalmonelladry transfer surrogates for their use in dry cleaning validation and modeling applications.IMPORTANCEThis work demonstrates the utility ofin silicomodeling as a decision support tool that can 1) estimate the cross-contamination ofSalmonellainto milk powder under different processing scenarios, 2) compare the efficacy of different cleaning interventions and 3) help inform surrogate selection for the dry transfer ofSalmonellain modeling and cleaning validation applications. The model presented here contributes to the risk-benefit analysis of tradeoffs associated with dry cleaning in low moisture food environments. For example, the model can be applied to estimate the efficacy of cleaning interventions like product flushing at a lower resource cost than experimental trials in a processing line. The model presented here also provides a more interpretable metric for choosing appropriateSalmonellasurrogates for dry cleaning validation.
