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Cross-contamination and undercooking are major factors responsible for campylobacteriosis and as such should be incorporated in microbiological risk assessment. A previous paper by van Asselt et al.((1)) quantified cross-contamination routes from chicken breast fillet via hand, cutting board, and knife ending up in a prepared chicken-curry salad in the domestic kitchen. The aim of the current article was to validate the obtained transfer rates with consumer data obtained by video observations and microbial analyses of a home prepared chicken-curry salad. Results showed a wide range of microbial contamination levels in the final salad, caused by various cross-contamination practices and heating times varying from 2'44'' to 41'30''. Model predictions indicated that cooking times should be at least 8 minutes and cutting boards need to be changed after cutting raw chicken in order to obtain safe bacterial levels in the final salad. The model predicted around 75% of the variance in cross-contamination behavior. Accuracy of the model can further be improved by including other cross-contamination routes besides hands, cutting boards, and knives. The model proved to be fail-safe, which implies it can be used as a worst-case estimate to assess the importance of cross-contamination in the home.

The improvement of food safety in the domestic environment requires a transdisciplinary approach, involving interaction between both the social and natural sciences. This approach is applied in a study on risks associated with Campylobacter on broiler meat. First, some web-based information interventions were designed and tested on participant motivation and intentions to cook more safely. Based on these self-reported measures, the intervention supported by the emotion "disgust" was selected as the most promising information intervention. Its effect on microbial cross-contamination was tested by recruiting a set of participants who prepared a salad with chicken breast fillet carrying a known amount of tracer bacteria. The amount of tracer that could be recovered from the salad revealed the transfer and survival of Campylobacter and was used as a measure of hygiene. This was introduced into an existing risk model on Campylobacter in the Netherlands to assess the effect of the information intervention both at the level of exposure and the level of human disease risk. We showed that the information intervention supported by the emotion "disgust" alone had no measurable effect on the health risk. However, when a behavioral cue was embedded within the instruction for the salad preparation, the risk decreased sharply. It is shown that a transdisciplinary approach, involving research on risk perception, microbiology, and risk assessment, is successful in evaluating the efficacy of an information intervention in terms of human health risks. The approach offers a novel tool for science-based risk management in the area of food safety.

It has been established that, to a considerable extent, the domestic hygiene practices adopted by consumers can result in a greater or lesser microbial load in prepared meals. In the research presented here, an interdisciplinary study is reported in which interviews, observations of consumers preparing a recipe, and microbial contamination of the finished meals were compared. The results suggest that, while most consumers are knowledgeable about the importance of cross-contamination and heating in preventing the occurrence of foodborne illness, this knowledge is not necessarily translated into behavior. The adoption of habitual cooking practices may also be important. Potentially risky behaviors were, indeed, observed in the domestic food preparation environment. Eighteen of the participants made errors in food preparation that could potentially result in cross-contamination, and seven participants allowed raw meat juices to come in contact with the final meal. Using a tracer microorganism the log reduction as a result of consumer preparation was estimated at an average of log 4.1 cfu/salad. When combining these findings, it was found that cross-contamination errors were a good predictor for log reduction. Procedural food safety knowledge (i.e., knowledge proffered after general open questions) was a better predictor of efficacious bacterial reduction than declarative food safety knowledge (i.e., knowledge proffered after formal questioning). This suggests that motivation to prepare safe food was a better indicator of actual behavior than knowledge about food safety per se.

Microbial food safety has been the focus of research across various disciplines within the risk analysis community. Natural scientists involved in food microbiology and related disciplines work on the identification of health hazards, and the detection of pathogenic microorganisms. To perform risk assessment, research activities are increasingly focused on the quantification of microbial contamination of food products at various stages in the food chain, and modeling the impact of this contamination on human health. Social scientists conduct research into how consumers perceive food risks, and how best to develop effective risk communication with consumers in order to improve public health through improved food handling practices. The two approaches converge at the end of the food chain, where the activities regarding food preparation and food consumption are considered. Both natural and social sciences may benefit from input and expertise from the perspective of the alternative discipline, although, to date, the integration of social and natural sciences has been somewhat limited. This article therefore explores the potential of a transdisciplinary approach to food risk analysis in terms of delivering additional improvements to public health. Developing knowledge arising from research in both the natural and social sciences, we present a novel framework involving the integration of the two approaches that might provide the most effective way to improve the consumer health associated with food-borne illness.

Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth rate model based on interpretable parameters was used to predict growth during linear cooling of pea soup. Second, a temperature model for cooling pea soup was constructed by fitting the model to experimental data published earlier. This cooling model was used to estimate the effect of various cooling environments on average cooling times, taking into account the effect of stirring and product volume. The growth model systematically overestimated growth of C. perfringens during cooling in air, but this effect was limited to less than 0.5 log N/ml and this was considered to be acceptable for practical purposes. It was demonstrated that the growth model for C. perfringens combined with the cooling model for pea soup could be used to sufficiently predict growth of C. perfringens in different volume sizes of pea soup during cooling in air as well as the effect of stirring, different cooling temperatures, and various cooling environments on the growth of C. perfringens in pea soup. Although fine-tuning may be needed to eliminate inaccuracies, it was concluded that the combined model could be a useful tool for designing good manufacturing practices (GMP) procedures.