An agent-based model to simulate SARS-CoV-2 contamination of surfaces and meat cuts in processing plants.

At the beginning of the COVID-19 pandemic, several contamination clusters were reported in food-processing plants in France and several countries worldwide. Therefore, a need arose to better understand viral transmission in such occupational environments from multiple perspectives: the protection of workers in hotspots of viral circulation; the prevention of supply disruption due to the closure of plants; and the prevention of cluster expansion due to exports of food products contaminated by the virus to other locations. This paper outlines a simulation-based approach (using agent-based models) to study the effects of measures taken to prevent the contamination of workers, surfaces, and food products. The model includes user-defined parameters to integrate characteristics relating to SARS-CoV-2 (variant of concern to be considered, symptom onset…), food-processing plants (dimensions, ventilation…), and other sociodemographic transmission factors based on laboratory experiments as well as industrial and epidemiological investigations. Simulations were performed for a typical meat-processing plant in different scenarios for illustration purposes. The results suggested that increasing the mask-wearing ratio led to great reductions in the probability of observing clusters of more than 25 infections. In the case of clusters, masks being worn by all workers limited the presence of contamination (defined as levels of at least 5 log10 viral RNA copies) on meat cuts at less than 0.05 % and maintained the production capacity of the plant at optimal levels. Increasing the average distance between two workers from less than 1 m to more than 2 m decreased the cluster-occurrence probability by up to 15 % as well as contamination of food products during cluster situations. The developed approach can open up several perspectives in terms of potential communication-support tools for the agri-food sector and further reuses or adaptations for other hazards and occupational environments.

Dataset of experimental study investigation of airflow and heat transfer in an insulated box equipped with a phase change material.

This article contains a detailed description of the experimental protocol of air velocity (by particle image velocimetry - PIV) and temperature measurement (by T-type thermocouples) in an insulated box equipped with a Phase Change Material (PCM). The study was conducted in an empty box and a loaded box with extruded polystyrene slabs (XPS) and methylcellulose slabs (test product). The measurement was conducted at the middle plane and lateral plane. This article contains a complete dataset along with the illustrated figures of conducted experiment. They lead to more understanding of phenomena inside a closed cavity with a cold source and can be useful for validating numerical models, e.g., the results computed by computational fluid dynamic.

Combining Quantitative Risk Assessment of Human Health, Food Waste, and Energy Consumption: The Next Step in the Development of the Food Cold Chain?

The preservation of perishable food via refrigeration in the supply chain is essential to extend shelf life and provide consumers with safe food. However, electricity consumed in refrigeration processes has an economical and an environmental impact. This study focuses on the cold chain of cooked ham, including transport, cold room in supermarket, display cabinet, transport by consumer, and domestic refrigerator, and aims to predict the risk for human health associated with Listeria monocytogenes, the amount of food wasted due to the growth of spoilage bacteria, and the electrical consumption to maintain product temperature through the cold chain. A set of eight intervention actions were tested to evaluate their impact on the three criteria. Results show that the modification of the thermostat of the domestic refrigerator has a high impact on food safety and food waste and a limited impact on the electrical consumption. Inversely, the modification of the airflow rate in the display cabinet has a high impact on electrical consumption and a limited impact on food safety and food waste. A cost-benefit analysis approach and two multicriteria decision analysis methods were used to rank the intervention actions. These three methodologies show that setting the thermostat of the domestic refrigerator to 4 °C presents the best compromise between the three criteria. The impact of decisionmaker preferences (criteria weight) and limitations of these three approaches are discussed. The approaches proposed by this study may be useful in decision making to evaluate global impact of intervention actions in issues involving conflicting outputs.

Agricultural Practices Influence Salmonella Contamination and Survival in Pre-harvest Tomato Production.

Between 2000 and 2010 the Eastern Shore of Virginia was implicated in four Salmonella outbreaks associated with tomato. Therefore, a multi-year study (2012-2015) was performed to investigate presumptive factors associated with the contamination of Salmonella within tomato fields at Virginia Tech's Eastern Shore Agricultural Research and Extension Center. Factors including irrigation water sources (pond and well), type of soil amendment: fresh poultry litter (PL), PL ash, and a conventional fertilizer (triple superphosphate - TSP), and production practices: staked with plastic mulch (SP), staked without plastic mulch (SW), and non-staked without plastic mulch (NW), were evaluated by split-plot or complete-block design. All field experiments relied on naturally occurring Salmonella contamination, except one follow up experiment (worst-case scenario) which examined the potential for contamination in tomato fruits when Salmonella was applied through drip irrigation. Samples were collected from pond and well water; PL, PL ash, and TSP; and the rhizosphere, leaves, and fruits of tomato plants. Salmonella was quantified using a most probable number method and contamination ratios were calculated for each treatment. Salmonella serovar was determined by molecular serotyping. Salmonella populations varied significantly by year; however, similar trends were evident each year. Findings showed use of untreated pond water and raw PL amendment increased the likelihood of Salmonella detection in tomato plots. Salmonella Newport and Typhimurium were the most frequently detected serovars in pond water and PL amendment samples, respectively. Interestingly, while these factors increased the likelihood of Salmonella detection in tomato plots (rhizosphere and leaves), all tomato fruits sampled (n = 4800) from these plots were Salmonella negative. Contamination of tomato fruits was extremely low (< 1%) even when tomato plots were artificially inoculated with an attenuated Salmonella Newport strain (104 CFU/mL). Furthermore, Salmonella was not detected in tomato plots irrigated using well water and amended with PL ash or TSP. Production practices also influenced the likelihood of Salmonella detection in tomato plots. Salmonella detection was higher in tomato leaf samples for NW plots, compared to SP and SW plots. This study provides evidence that attention to agricultural inputs and production practices may help reduce the likelihood of Salmonella contamination in tomato fields.

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing.

We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0-5-log10 reduction in Salmonella) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400-248,000) cases/year. Risk reduction (by 5- to 7-fold) predicted from a 1-log10 seed treatment alone was comparable to SIW testing alone, and each additional 1-log10 seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3-log10 or a 5-log10 seed treatment reduced the predicted cases/year to 139 (95% CI 33-448) or 1.4 (95% CI <1-4.5), respectively. Combined with SIW testing, a 3-log10 or 5-log10 seed treatment reduced the cases/year to 45 (95% CI 10-146) or <1 (95% CI <1-1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3-log10 seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22-298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.

Quantitative Risk Assessment of Norovirus Transmission in Food Establishments: Evaluating the Impact of Intervention Strategies and Food Employee Behavior on the Risk Associated with Norovirus in Foods.

We developed a quantitative risk assessment model using a discrete event framework to quantify and study the risk associated with norovirus transmission to consumers through food contaminated by infected food employees in a retail food setting. This study focused on the impact of ill food workers experiencing symptoms of diarrhea and vomiting and potential control measures for the transmission of norovirus to foods. The model examined the behavior of food employees regarding exclusion from work while ill and after symptom resolution and preventive measures limiting food contamination during preparation. The mean numbers of infected customers estimated for 21 scenarios were compared to the estimate for a baseline scenario representing current practices. Results show that prevention strategies examined could not prevent norovirus transmission to food when a symptomatic employee was present in the food establishment. Compliance with exclusion from work of symptomatic food employees is thus critical, with an estimated range of 75-226% of the baseline mean for full to no compliance, respectively. Results also suggest that efficient handwashing, handwashing frequency associated with gloving compliance, and elimination of contact between hands, faucets, and door handles in restrooms reduced the mean number of infected customers to 58%, 62%, and 75% of the baseline, respectively. This study provides quantitative data to evaluate the relative efficacy of policy and practices at retail to reduce norovirus illnesses and provides new insights into the interactions and interplay of prevention strategies and compliance in reducing transmission of foodborne norovirus.

Identification of the significant factors in food safety using global sensitivity analysis and the accept-and-reject algorithm: application to the cold chain of ham.

Deterministic models describing heat transfer and microbial growth in the cold chain are widely studied. However, it is difficult to apply them in practice because of several variable parameters in the logistic supply chain (e.g., ambient temperature varying due to season and product residence time in refrigeration equipment), the product's characteristics (e.g., pH and water activity) and the microbial characteristics (e.g., initial microbial load and lag time). This variability can lead to different bacterial growth rates in food products and has to be considered to properly predict the consumer's exposure and identify the key parameters of the cold chain. This study proposes a new approach that combines deterministic (heat transfer) and stochastic (Monte Carlo) modeling to account for the variability in the logistic supply chain and the product's characteristics. The model generates a realistic time-temperature product history , contrary to existing modeling whose describe time-temperature profile Contrary to existing approaches that use directly a time-temperature profile, the proposed model predicts product temperature evolution from the thermostat setting and the ambient temperature. The developed methodology was applied to the cold chain of cooked ham including, the display cabinet, transport by the consumer and the domestic refrigerator, to predict the evolution of state variables, such as the temperature and the growth of Listeria monocytogenes. The impacts of the input factors were calculated and ranked. It was found that the product's time-temperature history and the initial contamination level are the main causes of consumers' exposure. Then, a refined analysis was applied, revealing the importance of consumer behaviors on Listeria monocytogenes exposure.