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.     

Development of an urban intensity index to facilitate urban ecosystem studies in Trinidad and Tobago

Urban ecosystems, considered centres of economic, social and cultural development, face a multitude of environmental and socio-economic challenges, which impact on quality of life. Effective management of the urbanization process is believed critical to improving quality of life and realizing sustainable development. The ecosystem perspective provides a holistic approach, needed to address the complexly interconnected issues, which arise from urban development. Central to the mapping and characterization of urban ecosystems is the delineation of their boundaries, which are made less transparent by growing urbanization. This exposes the limitations of a dichotomous approach. An urban intensity index is a critical tool which supports urban ecosystem studies by facilitating analysis of effects along the urban–rural gradient. In this study, Urban Intensity is estimated and ranked from most to least intense for communities across Trinidad and Tobago, using multivariate statistical analysis of physical data from the built environment. This statistically validated index, designed for Trinidad and Tobago, should have wider applicability to other disciplines and countries.     

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid-Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross-validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.     

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.     

Are Subsidies to be Blamed? A Reexamination of U.S. Countervailing Duty on Hog Imports From Canada

A dramatic increase in U.S. hog imports from Canada triggered a successful countervail action against Canada in 1985, and resulted in an import tariff. This paper finds Canadian subsidies were not a major factor explaining increased hog exports, rather, the depreciation of the Canadian dollar played a larger role. More importantly, we find that hog imports from Canada did not “injure” the U.S. industry. These results imply the U.S. hog countervail duty was the outcome of rent-seeking activities rather than due to economic factors.     

Building Career PATHS (Postschool Achievement Through Higher Skills) for Young Women With Disabilities

The PATHS (Postschool Achievement Through Higher Skills) curriculum is designed to address the career development needs of young women with disabilities and other barriers. Participants (N = 110) in a pilot test of the curriculum showed increases in vocational self‐efficacy, social efficacy, and awareness of disability/gender issues related to career planning, whereas those in the comparison group did not make similar gains. Qualitative findings from focus groups (N = 68) revealed that PATHS participants improved in self‐confidence, self‐awareness, ability to identify strengths, knowledge of multiple career options, and the capacity to set goals and plan for future careers.     

Effects of Partnership Quality,Talent Management,and Global Mindset on Performance of Offshore IT Service Providers in India

This paper investigates the effects of partnership quality, talent management and global mindset on the performance of offshore service providers (OSPs) in the information technology sector in India. The findings show that partnership quality has partial and strong mediation effects on the impact of talent management and global mindset on performance of OSPs. We also find that talent management strongly mediates the effects of global mindset on partnership quality. Overall, the results confirm that global mindset, by itself, has limited direct influence on the performance of OSPs and that the full benefits of global mindset can only be enjoyed by OSPs which have well developed talent management and high quality partnerships with their clients. The implications and limitations of the study are also discussed.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.