Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to predict the animal reservoir from which a bacterial strain isolated from a human salmonellosis case originated based on whole-genome sequencing. Machine learning methods recognize patterns in large and complex data sets and use this knowledge to build models. The model learns patterns associated with genetic variations in bacteria isolated from the different animal reservoirs. We selected different machine learning algorithms to predict sources of human salmonellosis cases and trained the model with Danish Salmonella Typhimurium isolates sampled from broilers (n = 34), cattle (n = 2), ducks (n = 11), layers (n = 4), and pigs (n = 159). Using cgMLST as input features, the model yielded an average accuracy of 0.783 (95% CI: 0.77–0.80) in the source prediction for the random forest and 0.933 (95% CI: 0.92–0.94) for the logit boost algorithm. Logit boost algorithm was most accurate (valid accuracy: 92%, CI: 0.8706–0.9579) and predicted the origin of 81% of the domestic sporadic human salmonellosis cases. The most important source was Danish produced pigs (53%) followed by imported pigs (16%), imported broilers (6%), imported ducks (2%), Danish produced layers (2%), Danish produced cattle and imported cattle (<1%) while 18% was not predicted. Machine learning has potential for improving source attribution modeling based on sequence data. Results of such models can inform risk managers to identify and prioritize food safety interventions.     

Safety sans Frontières: An International Safety Culture Model

The management of safety culture in international and culturally diverse organizations is a concern for many high‐risk industries. Yet, research has primarily developed models of safety culture within Western countries, and there is a need to extend investigations of safety culture to global environments. We examined (i) whether safety culture can be reliably measured within a single industry operating across different cultural environments, and (ii) if there is an association between safety culture and national culture. The psychometric properties of a safety culture model developed for the air traffic management (ATM) industry were examined in 17 European countries from four culturally distinct regions of Europe (North, East, South, West). Participants were ATM operational staff (n = 5,176) and management staff (n = 1,230). Through employing multigroup confirmatory factor analysis, good psychometric properties of the model were established. This demonstrates, for the first time, that when safety culture models are tailored to a specific industry, they can operate consistently across national boundaries and occupational groups. Additionally, safety culture scores at both regional and national levels were associated with country‐level data on Hofstede's five national culture dimensions (collectivism, power distance, uncertainty avoidance, masculinity, and long‐term orientation). MANOVAs indicated safety culture to be most positive in Northern Europe, less so in Western and Eastern Europe, and least positive in Southern Europe. This indicates that national cultural traits may influence the development of organizational safety culture, with significant implications for safety culture theory and practice.     

Determining an Optimal Penetration Among Weighted Regions in Two and Three Dimensions

We present efficient algorithms for solving the problem of computing an optimal penetration (a ray or a semi-ray) among weighted regions in 2-D and 3-D spaces. This problem finds applications in several areas, such as radiation therapy, geological exploration, and environmental engineering. Our algorithms are based on a combination of geometric techniques and optimization methods. Our geometric analysis shows that the d-D (d = 2, 3) optimal penetration problem can be reduced to solving O(n ^2(d–1)) instances of certain special types of non-linear optimization problems, where n is the total number of vertices of the regions. We also give implementation results of our 2-D algorithms.     

Job stress,social support and health amongst shrimp fishermen

Abstract

Samples of shrimp fishermen (n = 211) and land-based workers (n = 99) drawn from a US Gulf Coast community are compared with regard to their degree of exposure to occupational stressors, level of social support, and extent of non-clinical depression and somatization. As hypothesized, shrimp fishermen report significantly greater levels of stressor exposure, support, depression and somatization at the zero-order level. At the multivariate level, with several covariates controlled, shrimpers report greater levels of stressor exposure, support and somatization. A model of the stress process which hypothesizes positive effects of stressors, and direct and indirect negative effects of social support on distress, is evaluated for each group. Occupational stressors predict as hypothesized, but social support does not. An explanation is offered which emphasizes the migratory character of shrimping as an occupation.     

A meta-analytic examination of the potential correlates and consequences of workload

Over the last four decades, occupational stress researchers have given considerable attention to the potential correlates and consequences of workload. In the current study, we use meta-analysis (overall k = 336) to quantitatively review the workload literature. In analyses of hypothesized correlates, we found that social support was negatively associated (ρ = ?.20 for supervisor support; ρ = –.11 for co-worker support) and that trait negative affectivity (ρ = .22), role ambiguity (ρ = .28), role conflict (ρ = .44) and work-family conflict (ρ = .44 for work-to-family conflict; ρ = .20 for family-to-work conflict) were each positively associated with workload. Analyses examining hypothesized outcome variables suggest that workload is negatively associated with several indices of psychological and physical well-being (ρs were generally in the –.20s and –.30s), and affective organizational commitment (ρ = –.11), and is positively associated with turnover intention (ρ = .16) and absenteeism (ρ = .07).     

On Confidence Intervals for Autoregressive Roots and Predictive Regression

Local to unity limit theory is used in applications to construct confidence intervals (CIs) for autoregressive roots through inversion of a unit root test (Stock (1991)). Such CIs are asymptotically valid when the true model has an autoregressive root that is local to unity (ρ = 1 + c/n), but are shown here to be invalid at the limits of the domain of definition of the localizing coefficient c because of a failure in tightness and the escape of probability mass. Failure at the boundary implies that these CIs have zero asymptotic coverage probability in the stationary case and vicinities of unity that are wider than O(n^−1/3). The inversion methods of Hansen (1999) and Mikusheva (2007) are asymptotically valid in such cases. Implications of these results for predictive regression tests are explored. When the predictive regressor is stationary, the popular Campbell and Yogo (2006) CIs for the regression coefficient have zero coverage probability asymptotically, and their predictive test statistic Q erroneously indicates predictability with probability approaching unity when the null of no predictability holds. These results have obvious cautionary implications for the use of the procedures in empirical practice.     

Assessing and Preventing Serious Incidents with Behavioral Science: Enhancing Heinrich’s Triangle for the 21st Century

ABSTRACT

The rate of occupational injuries has been declining annually, but the rate of decline for fatalities has not kept a similar pace. Behavior-based safety (BBS) contributes to reducing personal injuries, and can be applied to preventing serious incidents. To address serious injuries with greater confidence requires a change in perspective on the causes of fatalities and serious injuries. Heinrich’s safety triangle helps describe the ratio between minor incidents and major incidents, but is not adequate in helping to predict serious incidents. Adding a special subset to the safety triangle can assist safety practitioners in predicting and influencing such events. Extending the triangle to include more foundational root causes, such as leadership shortcomings and system failures, will expand the scope of the behavior analysis, and including greater specificity about the precursors to serious incidents will help the precision of the behavior analysis. The implications of the expanded triangle for amplifying the effectiveness of BBS for reducing serious incidents are discussed.     

Evaluating and improving risk formulas for allocating limited budgets to expensive risk-reduction opportunities

Simple risk formulas, such as risk = probability × impact, or risk = exposure × probability × consequence, or risk = threat × vulnerability × consequence, are built into many commercial risk management software products deployed in public and private organizations. These formulas, which we call risk indices, together with risk matrices, “heat maps,” and other displays based on them, are widely used in applications such as enterprise risk management (ERM), terrorism risk analysis, and occupational safety. But, how well do they serve to guide allocation of limited risk management resources? This article evaluates and compares different risk indices under simplifying conditions favorable to their use (statistically independent, uniformly distributed values of their components; and noninteracting risk‐reduction opportunities). Compared to an optimal (nonindex) approach, simple indices produce inferior resource allocations that for a given cost may reduce risk by as little as 60% of what the optimal decisions would provide, at least in our simple simulations. This article suggests a better risk reduction per unit cost index that achieves 98–100% of the maximum possible risk reduction on these problems for all budget levels except the smallest, which allow very few risks to be addressed. Substantial gains in risk reduction achieved for resources spent can be obtained on our test problems by using this improved index instead of simpler ones that focus only on relative sizes of risk (or of components of risk) in informing risk management priorities and allocating limited risk management resources. This work suggests the need for risk management tools to explicitly consider costs in prioritization activities, particularly in situations where budget restrictions make careful allocation of resources essential for achieving close‐to‐maximum risk‐reduction benefits.     

Classification of Listeria monocytogenes Persistence in Retail Delicatessen Environments Using Expert Elicitation and Machine Learning

Increasing evidence suggests that persistence of Listeria monocytogenes in food processing plants has been the underlying cause of a number of human listeriosis outbreaks. This study extracts criteria used by food safety experts in determining bacterial persistence in the environment, using retail delicatessen operations as a model. Using the Delphi method, we conducted an expert elicitation with 10 food safety experts from academia, industry, and government to classify L. monocytogenes persistence based on environmental sampling results collected over six months for 30 retail delicatessen stores. The results were modeled using variations of random forest, support vector machine, logistic regression, and linear regression; variable importance values of random forest and support vector machine models were consolidated to rank important variables in the experts’ classifications. The duration of subtype isolation ranked most important across all expert categories. Sampling site category also ranked high in importance and validation errors doubled when this covariate was removed. Support vector machine and random forest models successfully classified the data with average validation errors of 3.1% and 2.2% (n = 144), respectively. Our findings indicate that (i) the frequency of isolations over time and sampling site information are critical factors for experts determining subtype persistence, (ii) food safety experts from different sectors may not use the same criteria in determining persistence, and (iii) machine learning models have potential for future use in environmental surveillance and risk management programs. Future work is necessary to validate the accuracy of expert and machine classification against biological measurement of L. monocytogenes persistence.     

Online patient feedback as a safety valve: An automated language analysis of unnoticed and unresolved safety incidents

Safety reporting systems are widely used in healthcare to identify risks to patient safety. But, their effectiveness is undermined if staff do not notice or report incidents. Patients, however, might observe and report these overlooked incidents because they experience the consequences, are highly motivated, and independent of the organization. Online patient feedback may be especially valuable because it is a channel of reporting that allows patients to report without fear of consequence (e.g., anonymously). Harnessing this potential is challenging because online feedback is unstructured and lacks demonstrable validity and added value. Accordingly, we developed an automated language analysis method for measuring the likelihood of patient-reported safety incidents in online patient feedback. Feedback from patients and families (n = 146,685, words = 22,191,427, years = 2013–2019) about acute NHS trusts (hospital conglomerates; n = 134) in England were analyzed. The automated measure had good precision (0.69) and excellent recall (0.98) in identifying incidents; was independent of staff-reported incidents (r = −0.04 to 0.19); and was associated with hospital-level mortality rates (z = 3.87; p < 0.001). The identified safety incidents were often reported as unnoticed (89%) or unresolved (21%), suggesting that patients use online platforms to give visibility to safety concerns they believe have been missed or ignored. Online stakeholder feedback is akin to a safety valve; being independent and unconstrained it provides an outlet for reporting safety issues that may have been unnoticed or unresolved within formal channels.     

The nature,extent and determinants of violence against psychiatric personnel

Violence against psychiatric staff seems to be on the increase. Such abuse can lead to mental health consequences for the staff and a reluctance to be closely involved with patients. Few Swedish investigations have examined violence against mental nurses and psychiatrists, or undertaken comparative studies between them. In this study we examined the extent, nature and determinants (i.e. risk factors) of violence against psychiatric nurses (n = 731) and psychiatrists (n = 320) working in the eight health care districts of Stockholm. These caregivers were assessed cross-sectionally by means of a questionnaire covering various areas (e.g. violence and work environment). The majority of the participants (85%) reported having been exposed to violence during their careers, with 57% being victimized in the past 12 months. Physical violence was common, and factors such as negative attitudes to work and diminished sense of autonomy were associated with an increased vulnerability to violence. Nurses and psychiatrists did not differ in violence variables. In spite of the weaknesses of the design (cross-sectional self-selecting sample), this study corroborates previous findings and identifies personal factors associated with violence that have received little attention in the literature (e.g. lack of respect for the organization of care).     

Minimizing the mean squared deviation from a common due date: unconstrained and constrained cases

The problem of minimizing the mean squared deviation (MSD) of completion times from a common due date in both unconstrained and constrained cases is addressed. It is shown that the unconstrained MDS function is unimodal for n ≤ 6, where n is the number of jobs. The constrained case is shown to be unimodular for n ≤ 3, The unconstrained case is shown, by counterexample, not to be unimodular for n = 8. The constrained case is shown not to be unimodular for n = 5. For the unimodular cases, a proposed search routine can find the optimum solution in less than three CPU seconds for n = 100. It provides an excellent heuristic solution otherwise. Computational results are shown in both cases.     

The Potential Effects of Recall Bias and Selection Bias on the Epidemiological Evidence for the Carcinogenicity of Glyphosate

Glyphosate is a widely used herbicide worldwide. The International Agency for Research on Cancer in 2015 declared that glyphosate is probably carcinogenic to humans, noting a positive association for non-Hodgkin lymphoma (NHL). The principal human data on glyphosate and NHL come from five case–control studies and two cohort studies. The case–control studies are at risk of recall bias resulting from information on exposure to pesticides being collected from cases and controls based on their memories. In addition, two of the case–control studies are additionally at risk of a form of selection bias that can exacerbate the effect of recall bias. Both biases are in the direction of making glyphosate appear carcinogenic. If odds ratios (ORs) are not biased and a pesticide plays no role in causing NHL, the probability that an OR for that pesticide is greater than 1.0 is approximately 0.5. The fractions of ORs for pesticides other than glyphosate that are greater than 1.0 in the case–control studies are 0.90 (n = 92), 0.90 (n = 152), 0.93 (n = 59), 0.76 (n = 140), and 0.53 (n = 54), the first two from studies that are at risk for both types of bias. In the two cohort studies, which are not subject to these biases, the comparable fractions for relative risks for all cancers are 0.51 (n = 70) and 0.48 (n = 158). These results comply closely with what would be expected if evidence for carcinogenicity of glyphosate in these studies results from statistical bias in the case–control studies.     

Simple Finite Horizon Bubbles Robust to Higher Order Knowledge

An asymmetric information model of a finite horizon “nth order” rational asset price bubble is presented, where (all agents know that)ⁿ the asset is worthless. Also, the model has only two agents, so the first order version of the bubble is simpler than other first order bubbles in the literature.     

Perfect Circular Arc Coloring

The circular arc coloring problem is to find a minimum coloring of a set of arcs of a circle so that no two overlapping arcs share a color. This NP-hard problem arises in a rich variety of applications and has been studied extensively. In this paper we present an O(n² m) combinatorial algorithm for optimally coloring any set of arcs that corresponds to a perfect graph, and propose a new approach to the general circular arc coloring problem.Partially supported by Project 02139 of Education Ministry of China.Supported in part by the Research Grants Council of Hong Kong (Project No. HKU7054/03P) and a seed funding for basic research of HKU.     

Bioaccessibility and Risk of Exposure to Metals and SVOCs in Artificial Turf Field Fill Materials and Fibers

To reduce maintenance costs, municipalities and schools are starting to replace natural grass fields with a new generation synthetic turf. Unlike Astro‐Turf, which was first introduced in the 1960s, synthetic field turf provides more cushioning to athletes. Part of this cushioning comes from materials like crumb rubber infill, which is manufactured from recycled tires and may contain a variety of chemicals. The goal of this study was to evaluate potential exposures from playing on artificial turf fields and associated risks to trace metals, semi‐volatile organic compounds (SVOCs), and polycyclic aromatic hydrocarbons (PAHs) by examining typical artificial turf fibers (n = 8), different types of infill (n = 8), and samples from actual fields (n = 7). Three artificial biofluids were prepared, which included: lung, sweat, and digestive fluids. Artificial biofluids were hypothesized to yield a more representative estimation of dose than the levels obtained from total extraction methods. PAHs were routinely below the limit of detection across all three biofluids, precluding completion of a meaningful risk assessment. No SVOCs were identified at quantifiable levels in any extracts based on a match of their mass spectrum to compounds that are regulated in soil. The metals were measurable but at concentrations for which human health risk was estimated to be low. The study demonstrated that for the products and fields we tested, exposure to infill and artificial turf was generally considered de minimus, with the possible exception of lead for some fields and materials.     

Job Strain,Effort-Reward Imbalance and Mental Distress: A study of occupations in general medical practice

There is increasing evidence to support the predictive power of social epidemiological models such as Effort-Reward Imbalance (Siegrist, 1996) and the Job-Strain Model (Karasek, and Theorell, 1990) for explaining occupational stress, although it has been suggested that the models may have distinctive contributions towards explaining work stress in specific work settings. Alternatively, it has been suggested that the explanatory power of the different models might be enhanced if they were combined. The aim of this paper is to explore these questions by examining the power of the two different models both separately and in combination for explaining job satisfaction and mental distress in general medical practice. This analysis was based on data collected from a postal survey of the members of staff (N=1089, response rate = 70%) of 81 practices, which were randomly selected from all general practices in the National Health Service Executive South East region. The results show that while both models were predictors of mental distress and job satisfaction the models that combined different dimensions were the strongest predictors.     

Organizational-level interventions to reduce occupational stressors

Abstract

Occupational stress research continues to grow, and is increasingly being used to inform national policy on worker health and well-being. Most models of occupational stress emphasize notions of person-environment fit. Two approaches for intervention to minimize adverse consequences of occupational stress follow from such models. One emphasizes the strengthening and enhancement of indwiduals and their resources, the other emphasizes the reduction ofcommon workplace-based sources ofoccupational stress. This paper reviews 10 organizational-level interventions to reduce stress at work which have been examined in various field studies. These interventions were generally found to have positive effects, and, given the limited success of individual-level interventions in addressing occupational sources of stress, should be encouraged.     

Patterns of conflict and enrichment in work-family balance: A three-dimensional typology

Abstract

A four-dimensional typology of work-family balance (WFB) that has previously been reported was tested in four samples: Finnish nurses (n=662), Slovenian nurses (n=667), Finnish health and social care workers (n=1493) and Finnish service sector employees (n=827). Latent profile analyses identified three rather than four types of WFB in each sample. In line with the four-dimensional typology, a Beneficial type (56% to 70% of the participants), experiencing high work-to-family and family-to-work enrichment (WFE and FWE) and low work-to-family and family-to-work conflict (WFC and FWC), and an Active type (15% to 20%), experiencing high WFC, FWC, WFE and FWE, emerged; however, the Harmful and Passive types were not identified. Instead, a Contradictory type (16% to 53%), experiencing high WFC and low WFE in combination with low FWC and high FWE, was found. The Beneficial type showed higher subjective well-being than the Contradictory and Active types, the latter showing higher vigour at work but also higher psychological strain and lower life satisfaction than the Contradictory type. These findings support the view that WFB is not a single state or continuum, but manifests itself in diverse combinations of WFC, FWC, WFE and FWE.