Optimization of Sampling for Monitoring Chemicals in the Food Supply Chain Using a Risk-Based Approach: The Case of Aflatoxins and Dioxins in the Dutch Dairy Chain

Food safety monitoring faces the challenge of tackling multiple chemicals along the various stages of the food supply chain. Our study developed a methodology for optimizing sampling for monitoring multiple chemicals along the dairy supply chain. We used a mixed integer nonlinear programming approach to maximize the performance of the sampling in terms of reducing the risk of the potential disability adjusted life years (DALYs) in the population. Decision variables are the number of samples collected and analyzed at each stage of the food chain (feed mills, dairy farms, milk trucks, and dairy processing plants) for each chemical, given a predefined budget. The model was applied to the case of monitoring for aflatoxin B₁/M₁(AFB₁/M₁) and dioxins in a hypothetical Dutch dairy supply chain, and results were calculated for various contamination scenarios defined in terms of contamination fraction and concentrations. Considering various monitoring budgets for both chemicals, monitoring for AFB₁/M₁ showed to be more effective than for dioxins in most of the considered scenarios, because AFB₁/M₁ could result into more DALYs than dioxins when both chemicals are in same contamination fraction, and costs for analyzing one AFB₁/M₁ sample are lower than for one dioxins sample. The results suggest that relatively more resources be spent on monitoring AFB₁/M₁ when both chemicals’ contamination fractions are low; when both contamination fractions are higher, relatively more budget should be addressed to monitoring dioxins.     

The Economic Efficiency of Sampling Size: The Case of Beef Trim Revisited

A recent paper by Ferrier and Buzby provides a framework for selecting the sample size when testing a lot of beef trim for Escherichia coli O157:H7 that equates the averted costs of recalls and health damages from contaminated meats sold to consumers with the increased costs of testing while allowing for uncertainty about the underlying prevalence of contamination. Ferrier and Buzby conclude that the optimal sample size is larger than the current sample size. However, Ferrier and Buzby's optimization model has a number of errors, and their simulations failed to consider available evidence about the likelihood of the scenarios explored under the model. After correctly modeling microbial prevalence as dependent on portion size and selecting model inputs based on available evidence, the model suggests that the optimal sample size is zero under most plausible scenarios. It does not follow, however, that sampling beef trim for E. coli O157:H7, or food safety sampling more generally, should be abandoned. Sampling is not generally cost effective as a direct consumer safety control measure due to the extremely large sample sizes required to provide a high degree of confidence of detecting very low acceptable defect levels. Food safety verification sampling creates economic incentives for food producing firms to develop, implement, and maintain effective control measures that limit the probability and degree of noncompliance with regulatory limits or private contract specifications.     

Exposure Assessment for Pesticide Intake from Multiple Food Products: A Bayesian Latent‐Variable Approach

Pesticide risk assessment for food products involves combining information from consumption and concentration data sets to estimate a distribution for the pesticide intake in a human population. Using this distribution one can obtain probabilities of individuals exceeding specified levels of pesticide intake. In this article, we present a probabilistic, Bayesian approach to modeling the daily consumptions of the pesticide Iprodione though multiple food products. Modeling data on food consumption and pesticide concentration poses a variety of problems, such as the large proportions of consumptions and concentrations that are recorded as zero, and correlation between the consumptions of different foods. We consider daily food consumption data from the Netherlands National Food Consumption Survey and concentration data collected by the Netherlands Ministry of Agriculture. We develop a multivariate latent‐Gaussian model for the consumption data that allows for correlated intakes between products. For the concentration data, we propose a univariate latent‐t model. We then combine predicted consumptions and concentrations from these models to obtain a distribution for individual daily Iprodione exposure. The latent‐variable models allow for both skewness and large numbers of zeros in the consumption and concentration data. The use of a probabilistic approach is intended to yield more robust estimates of high percentiles of the exposure distribution than an empirical approach. Bayesian inference is used to facilitate the treatment of data with a complex structure.     

Dietary and Inhalation Intake of Lead and Estimation of Blood Lead Levels in Adults and Children in Kanpur, India

This research was initiated to study lead levels in various food items in the city of Kanpur, India, to assess the dietary intake of lead and to estimate blood lead (PbB) levels, a biomarker of lead toxicity. For this purpose, sampling of food products, laboratory analysis, and computational exercises were undertaken. Specifically, six food groups (leafy vegetables, nonleafy vegetables, fruits, pulses, cereals, and milk), drinking water, and lead air concentration were considered for estimating lead intake. Results indicated highest lead content in leafy vegetables followed by pulses. Fruits showed low lead content and drinking water lead levels were always within tolerable limits. It was estimated that average daily lead intake through diet was about 114 microg/day for adults and 50 microg/day in children; tolerable limit is 250 microg/day for adults and 90 microg/day for children. The estimated lead intakes were translated into the resultant PbB concentrations for children and adults using a physiologically-based pharmacokinetic (PBPK) model. Monte Carlo simulation of PbB level variations for adults showed that probability of exceeding the tolerable limit of PbB (i.e.,10 microg/dL) was 0.062 for the pre-unleaded and 0.000328 for the post-unleaded gasoline period. The probability of exceeding tolerable limits in PbB level was reduced by a factor of 189 in the post-unleaded scenario. The study also suggested that in spite of the introduction of unleaded gasoline, children continue to be at a high risk (probability of exceeding 10 microg/dL = 0.39) because of a high intake of lead per unit body weight.     

考虑追溯水平的食品厂商竞争决策研究

本文综合考虑食品市场竞争环境,消费者食品安全风险规避程度及食品追溯水平等因素建立了食品厂商的双寡头竞争博弈模型,探讨了食品的追溯水平与消费者风险规避程度对食品厂商价格、安全努力水平以及利润的影响。研究发现：食品厂商的最优价格和食品的安全努力水平随其食品追溯水平的提高而增加,随竞争厂商的食品追溯水平的提高而降低;厂商食品追溯水平较高时,其安全努力水平随消费者风险规避程度的增大而提高,其最优价格随高风险规避型消费者比例的增大而增加;而厂商食品追溯水平较低时,其安全努力水平随消费者风险规避程度的增大先增加而后下降,其最优价格随高风险规避型消费者比例的增大总是下降;随高风险规避型消费者比例的增大,各厂商的食品追溯水平对其决策的影响产生不同的变化。     

Meta-Analysis of Food Safety Information Based on a Combination of a Relational Database and a Predictive Modeling Tool

The management of microbial risk in food products requires the ability to predict growth kinetics of pathogenic microorganisms in the event of contamination and growth initiation. Useful data for assessing these issues may be found in the literature or from experimental results. However, the large number and variety of data make further development difficult. Statistical techniques, such as meta-analysis, are then useful to realize synthesis of a set of distinct but similar experiences. Moreover, predictive modeling tools can be employed to complete the analysis and help the food safety manager to interpret the data. In this article, a protocol to perform a meta-analysis of the outcome of a relational database, associated with quantitative microbiology models, is presented. The methodology is illustrated with the effect of temperature on pathogenic Escherichia coli and Listeria monocytogenes, growing in culture medium, beef meat, and milk products. Using a database and predictive models, simulations of growth in a given product subjected to various temperature scenarios can be produced. It is then possible to compare food products for a given microorganism, according to its growth ability in these products, and to compare the behavior of bacteria in a given foodstuff. These results can assist decisions for a variety of questions on food safety.     

Toward Improving Food Safety in the Domestic Environment: A Multi-Item Rasch Scale for the Measurement of the Safety Efficacy of Domestic Food-Handling Practices

To reduce consumer health risks from foodborne diseases that result from improper domestic food handling, consumers need to know how to safely handle food. To realize improvements in public health, it is necessary to develop interventions that match the needs of individual consumers. Successful intervention strategies are therefore contingent on identifying not only the practices that are important for consumer protection, but also barriers that prevent consumers from responding to these interventions. A measure of food safety behavior is needed to assess the effectiveness of different intervention strategies across different groups of consumers. A nationally representative survey was conducted in the Netherlands to determine which practices are likely conducted by which consumers. Participants reported their behaviors with respect to 55 different food-handling practices. The Rasch modeling technique was used to determine a general measure for the likelihood of an average consumer performing each food-handling behavior. Simultaneously, an average performance measure was estimated for each consumer. These two measures can be combined to predict the likelihood that an individual consumer engages in a specific food-handling behavior. A single "food safety" dimension was shown to underlie all items. Some potentially safe practices (e.g., use of meat thermometers) were reported as very difficult, while other safe practices were conducted by respondents more frequently (e.g., washing of fresh fruit and vegetables). A cluster analysis was applied to the resulting data set, and five segments of consumers were identified. Different behaviors may have different effects on microbial growth in food, and thus have different consequences for human health. Once the microbial relevance of the different consumer behaviors has been confirmed by experiments and modeling, the scale developed in the research reported here can be used to develop risk communication targeted to the needs of different consumer groups, as well as to measure the efficacy of different interventions.     

Sensitivity Analysis for Critical Control Points Determination and Uncertainty Analysis to Link FSO and Process Criteria: Application to Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

Microbiological food safety is an important economic and health issue in the context of globalization and presents food business operators with new challenges in providing safe foods. The hazard analysis and critical control point approach involve identifying the main steps in food processing and the physical and chemical parameters that have an impact on the safety of foods. In the risk‐based approach, as defined in the Codex Alimentarius, controlling these parameters in such a way that the final products meet a food safety objective (FSO), fixed by the competent authorities, is a big challenge and of great interest to the food business operators. Process risk models, issued from the quantitative microbiological risk assessment framework, provide useful tools in this respect. We propose a methodology, called multivariate factor mapping (MFM), for establishing a link between process parameters and compliance with a FSO. For a stochastic and dynamic process risk model of in soft cheese made from pasteurized milk with many uncertain inputs, multivariate sensitivity analysis and MFM are combined to (i) identify the critical control points (CCPs) for throughout the food chain and (ii) compute the critical limits of the most influential process parameters, located at the CCPs, with regard to the specific process implemented in the model. Due to certain forms of interaction among parameters, the results show some new possibilities for the management of microbiological hazards when a FSO is specified.     

Optimal Security Investments and Extreme Risk

In the aftermath of 9/11, concern over security increased dramatically in both the public and the private sector. Yet, no clear algorithm exists to inform firms on the amount and the timing of security investments to mitigate the impact of catastrophic risks. The goal of this article is to devise an optimum investment strategy for firms to mitigate exposure to catastrophic risks, focusing on how much to invest and when to invest. The latter question addresses the issue of whether postponing a risk mitigating decision is an optimal strategy or not. Accordingly, we develop and estimate both a one‐period model and a multiperiod model within the framework of extreme value theory (EVT). We calibrate these models using probability measures for catastrophic terrorism risks associated with attacks on the food sector. We then compare our findings with the purchase of catastrophic risk insurance.     

同质时鲜产品捆绑销售的最优策略

由于时鲜产品具有十分显著的时效性,为了更快地将时鲜产品销售出去,很多零售商采用了捆绑销售的方式.研究了同质时鲜产品捆绑销售的最优策略问题,对同质时鲜产品捆绑销售的最优价格、最优临界时间以及最优数量决策问题进行了描述,并利用随机效用理论建立了MNL模型.获得了同质时鲜产品捆绑销售单变量决策的最优价格、最优临界时间和最优数量,以及相应的最大利润.进而研究了同质时鲜产品捆绑销售的双变量组合决策问题,并给出了最优双变量组合决策和条件.最后,给出了一个算例,并分析了捆绑销售中价格、数量与时间之间的关系.     

Consumer Confidence in the Safety of Food and Newspaper Coverage of Food Safety Issues: A Longitudinal Perspective

This study develops a longitudinal perspective on consumer confidence in the safety of food to explore if, how, and why consumer confidence changes over time. In the first study, a theory-based monitoring instrument for consumer confidence in the safety of food was developed and validated. The monitoring instrument assesses consumer confidence together with its determinants. Model and measurement invariance were validated rigorously before developments in consumer confidence in the safety of food and its determinants were investigated over time. The results from the longitudinal analysis show that across four waves of annual data collection (2003–2006), the framework was stable and that the relative importance of the determinants of confidence was, generally, constant over time. Some changes were observed regarding the mean ratings on the latent constructs. The second study explored how newspaper coverage of food safety related issues affects consumer confidence in the safety of food through subjective consumer recall of food safety incidents. The results show that the newspaper coverage on food safety issues is positively associated with consumer recall of food safety incidents, both in terms of intensity and recency of media coverage.     

On the Use of Hierarchical Probabilistic Models for Characterizing and Managing Uncertainty in Risk/Safety Assessment

A general probabilistically-based approach is proposed for both cancer and noncancer risk/safety assessments. The familiar framework of the original ADI/RfD formulation is used, substituting in the numerator a benchmark dose derived from a hierarchical pharmacokinetic/pharmacodynamic model and in the denominator a unitary uncertainty factor derived from a hierarchical animal/average human/sensitive human model. The empirical probability distributions of the numerator and denominator can be combined to produce an empirical human-equivalent distribution for an animal-derived benchmark dose in external-exposure units.     

Foot-and-Mouth Disease Entrance Assessment Model Through Air Passenger Violations

This article aims to construct a risk model for the prediction of foot-and-mouth disease (FMD) entrance caused by passengers who illegally carry meat products of cloven-hoofed animals through international airports into a country. The risk that meat contaminated with the FMD virus is formulated as the probabilities of FMD factor events (the prevalence of FMD), the commodity factor event (the transportation, storage, and distribution (TSD) factor event), and the passenger event. Data used for analysis were records of illegal meat product carriers from areas A and B intercepted at an international airport in Taiwan. A risk model was proposed to simulate the probability distributions in disease prevalence, probability of FMD virus existing in the meat products after meat processing, and estimation of survival of virus and time period for TSD. The probability of the passenger event was hypothesized with the odds of intercepted passengers and estimated via logistic regression. The results showed that the odds of passengers being intercepted by beagles were higher than those intercepted by Customs. By conducting Monte Carlo simulations, the probability of FMD virus risk caused by FMD factors from area A was 149 times lower than that from area B. The probability of FMD virus risk caused by the passenger event from area A was four times lower than the corresponding probability from area B. The model provides a contribution to FMD prevention and can be a reference for developing models of other diseases.     

Re-distributed manufacturing and the food-water-energy nexus: opportunities and challenges

Abstract

Addressing the intersection of two important emerging research areas, re-distributed manufacturing (RDM) and the food-energy-water (FEW) nexus, this work combines insights from engineering, business and policy perspectives and explores opportunities and challenges towards a more localized and sustainable food system. Analysis centred on two specific food products, namely bread and tomato paste reveals that the feasibility and potential of RDM vary with the type of food product and the supply chain (SC) components. Physically, energy efficiency, water consumption and reduction of waste and carbon footprint may be affected by scale and location of production activities and potentials of industrial symbiosis. From the business perspective, novel products, new markets and new business models are expected in order for food RDM to penetrate within the established food industry. Studies on policies, through the lens of public procurement, call for solid evidence of envisioned environmental, social and economic benefits of a more localized food system. An initial integrated framework is proposed for understanding and assessing food RDM and the FEW nexus.     

Understanding Consumer Confidence in the Safety of Food: Its Two-Dimensional Structure and Determinants

Understanding of the determinants of consumer confidence in the safety of food is important if effective risk management and communication are to be developed. In the research reported here, we attempt to understand the roles of consumer trust in actors in the food chain and regulators, consumer recall of food safety incidents, consumer perceptions regarding the safety of particular product groups, personality characteristics, and sociodemographics, as potential determinants of consumer confidence in the safety of food. Consumer confidence in the safety of food was conceptualized as consisting of two distinct dimensions, namely, "optimism" and "pessimism." On the basis of a representative sample of 657 Dutch consumers, structural equation modeling was applied to simultaneously estimate the effect of the determinants on both "optimism" and "pessimism." The results indicated that, to a considerable extent, both optimism and pessimism about the safety of food arise from consumer trust in regulators and actors in the food chain and the perceived safety of meat and fish rather than other product categories. In addition, support was found for the notion that optimism and pessimism are conceptually distinct, as these dimensions of confidence were partly influenced by different determinants. The results of this study imply that consumer confidence in the safety of food could be enhanced by improving both consumer trust in societal actors, and consumer safety perceptions of particular product groups.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.     

Risk-Based Design of Aseptic Processing of Heterogeneous Food Products

A risk assessment was performed to incorporate uncertainty in food processing conditions to develop a risk-based sterilization process design. The focus of this analysis was uncertainty associated with heterogeneous food products. Quartered button mushrooms were the chosen food product because it represents the most typical type. A model for sterilization of spherical particles was utilized, and each parameter's uncertainty was characterized for use under Monte Carlo simulation. Various particle distributions and fluid types were compared. The output of the model was the required sterilization time to achieve the target sterilization conditions with 95% probability. This value was then used to determine the mean fluid velocity for a given tube length. Finally, the output from the model was analyzed to determine the confidence in output based on uncertainty in the input parameters. The model was more sensitive to variation in particle size distribution than fluid type for power-law fluids. The 90% confidence interval included a holding time range of 1 min. With a 95% confidence level that only 8% of the data will be below the target sterilization conditions, a maximum of 9% of the data were expected to achieve double the target level. The results of such an analysis would be useful for management decisions concerning the design of aseptic food processing operations.     

供应链的利润博弈与均衡定价

供应链涉及多个利益主体,优化供应链的全局效益需要成员企业的协调来实现。效率评估的非参数法应用广泛,但是单纯的效率优化未考虑资源的可替代性和再分配,忽视了投入(产出)结构调整释放的优化空间。对于效率分解,取折衷或单边最优的方案不完全符合企业追求各自利益最大化的目标。本文针对两级供应链的利润优化问题建立一般化的分析框架,同时考虑了技术进步和资源可替代性的影响,对成员企业的利润博弈展开讨论,探讨了合作博弈如何促成供应链实现集权模式下的最优。通过建立议价模型得出了纳什均衡基础上的成员企业最优利润组合,并给出了实现最优分配方案的中间产品均衡定价。     

A Model of Hygiene Practices and Consumption Patterns in the Consumer Phase

A mathematical model is presented, which addresses individual hygiene practices during food preparation and consumption patterns in private homes. Further, the model links food preparers and consumers based on their relationship to household types. For different age and gender groups, the model estimates (i) the probability of ingesting a meal where precautions have not been taken to avoid the transfer of microorganisms from raw food to final meal (a risk meal), exemplified by the event that the cutting board was not washed during food preparation, and (ii) the probability of ingesting a risk meal in a private home, where chicken was the prepared food item (a chicken risk meal). Chicken was included in the model, as chickens are believed to be the major source of human exposure to the foodborne pathogen Campylobacter. Monte Carlo simulations showed that the probability of ingesting a risk meal was highest for young males (aged 18-29 years) and lowest for the elderly above 60 years of age. Children aged 0-4 years had a higher probability of ingesting a risk meal than children aged 5-17 years. This difference between age and gender groups was ascribed to the variations in the hygiene levels of food preparers. By including the probability of ingesting a chicken meal at home, simulations revealed that all age groups, except the group above 60 years of age, had approximately the same probability of ingesting a chicken risk meal, the probability of females being slightly higher than that of males. The simulated results show that the probability of ingesting a chicken risk meal at home does not only depend on the hygiene practices of the persons preparing the food, but also on the consumption patterns of consumers, and the relationship between people preparing and ingesting food. This finding supports the need of including information on consumer behavior and preparation hygiene in the consumer phase of exposure assessments.