Some limitations of qualitative risk rating systems

Reconciling risk as threat and opportunity: The social construction of risk in boardrooms

Board directing is a continuous process of risk analysis and control in response to the duality of risk as threat and opportunity. Judgments are made and remade to simultaneously reduce the potential for damaging threats (e.g., fraud, reputation damage), while exploiting opportunities (e.g., new product development, mergers and acquisitions). Adopting an institutional logics approach, we explore this process of risk analysis and control through the varied subject identities (e.g., directorial roles), risk management practices (the procedures and tools used to identify, assess, and control risk), and risk objects (the product of risk identification, assessment, and control, e.g., a risk matrix or register) of boards. We argue that the contingent interaction between these identities, practices, and objects inform the "risk logic" of a board, which may draw attention to the notion of risk as threat, risk as opportunity, or both threat and opportunity. Using the testimony of 30 executive and nonexecutive directors that represent 62 companies from a range of public, private, and third-sector organizations, we contribute to the literature on the microfoundations of risk analysis in organizations by shining a light on how board directors understand, assess, control, and ultimately govern risk in organizations.

Application of multi-criteria decision analysis techniques and decision support framework for informing select agent designation for agricultural animal pathogens

The United States Department of Agriculture (USDA), Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents and toxins (Select Agent List) that potentially threaten agricultural health and safety, the procedures governing the transfer of those agents, and training requirements for entities working with them. Every 2 years the USDA DASAT reviews the Select Agent List, using subject matter experts (SMEs) to perform an assessment and rank the agents. To assist the USDA DASAT biennial review process, we explored the applicability of multi-criteria decision analysis (MCDA) techniques and a Decision Support Framework (DSF) in a logic tree format to identify pathogens for consideration as select agents, applying the approach broadly to include non-select agents to evaluate its robustness and generality. We conducted a literature review of 41 pathogens against 21 criteria for assessing agricultural threat, economic impact, and bioterrorism risk and documented the findings to support this assessment. The most prominent data gaps were those for aerosol stability and animal infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. The MCDA analysis supported the intuitive sense that select agents should rank high on the relative risk scale when considering agricultural health consequences of a bioterrorism attack. However, comparing select agents with non-select agents indicated that there was not a clean break in scores to suggest thresholds for designating select agents, requiring subject matter expertise collectively to establish which analytical results were in good agreement to support the intended purpose in designating select agents. The DSF utilized a logic tree approach to identify pathogens that are of sufficiently low concern that they can be ruled out from consideration as a select agent. In contrast to the MCDA approach, the DSF rules out a pathogen if it fails to meet even one criteria threshold. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

How People Understand Risk Matrices, and How Matrix Design Can Improve their Use: Findings from Randomized Controlled Studies

Risk matrices are a common way to communicate the likelihood and potential impacts of a variety of risks. Until now, there has been little empirical work on their effectiveness in supporting understanding and decision making, and on how different design choices affect these. In this pair of online experiments (total n = 2699), we show that risk matrices are not always superior to text for the presentation of risk information, and that a nonlinear/geometric labeling scheme helps matrix comprehension (when the likelihood/impact scales are nonlinear). To a lesser degree, results suggested that changing the shape of the matrix so that cells increase in size nonlinearly facilitates comprehension as compared to text alone, and that comprehension might be enhanced by integrating further details about the likelihood and impact onto the axes of the matrix rather than putting them in a separate key. These changes did not affect participants' preference for reducing impact over reducing likelihood when making decisions about risk mitigation. We recommend that designers of risk matrices consider these changes to facilitate better understanding of relationships among risks.

Risk Assessment Matrices for Workplace Hazards: Design for Usability

In occupational safety and health (OSH), the process of assessing risks of identified hazards considers both the (i) foreseeable events and exposures that can cause harm and (ii) the likelihood or probability of occurrence. To account for both, a table format known as a risk assessment matrix uses rows and columns for ordered categories of the foreseeable severity of harm and likelihood/probability of that occurrence. The cells within the table indicate level of risk. Each category has a text description separate from the matrix as well as a word or phrase heading each row and column. Ideally, these header terms will help the risk assessment team distinguish among the categories. A previous project provided recommended sets of header terms for common matrices based on findings from a survey of undergraduate OSH students. This paper provides background on risk assessment matrices, discusses usability issues, and presents findings from a survey of people with OSH-related experience. The aim of the survey was to confirm or improve the prior recommended sets of terms. The prior recommendations for severity, likelihood, and extent of exposure were confirmed with minor modifications. Improvements in the probability terms were recommended.

Unveiling Falling Urban Trees before and during Typhoon Higos (2020): Empirical Case Study of Potential Structural Failure Using Tilt Sensor

Urban trees in a densely populated environment may pose risks to the public’s safety in terms of the potential danger of injuries and fatalities, loss of property, impacts on traffic, etc. The biological and mechanical features of urban trees may change over time, thereby affecting the stability of the tree structure. This can be a gradual process but can also be drastic, especially after typhoons or heavy rainstorms. Trees may fall at any time with no discernible signs of failure being exhibited or detected. It is always a challenge in urban tree management to develop a preventive alert system to detect the potential failure of hazardous urban trees and hence be able to have an action plan to handle potential tree tilting or tree collapse. Few studies have considered the comparison of tree morphology to the tilt response relative to uprooting failure in urban cities. New methods involving numerical modeling and sensing technologies provide tools for an effective and deeper understanding of the interaction of root-plate movement and windstorm with the application of the tailor-made sensor. In this study, root-plate tilt variations of 889 trees with sensors installed during Typhoon Higos (2020) are investigated, especially the tilting pattern of the two trees that failed in the event. The correlation of tree response during the typhoon among all trees with tilt measurements was also evaluated. The results from two alarm levels developed in the study, i.e., Increasing Trend Alarm and Sudden Increase Alarm indicated that significant root-plate movement to wind response is species-dependent. These systems could help inform decision making to identify the problematic trees in the early stage. Through the use of smart sensors, the data collected by the alert system provides a very useful analysis of the stability of tree structure and tree health in urban tree management.

Identification and Prioritization of Critical Risk Factors of Commercial and Recreational Complex Building Projects: A Delphi Study Using the TOPSIS Method

Construction development of Commercial and Recreational Complex Building Projects (CRCBPs) is one of the community needs of many developing countries. Since the implementation of these projects is usually very costly, identifying and evaluating their Critical Risk Factors (CRFs) are of significant importance. Therefore, the current study aims to identify and prioritize CRFs of CRCBPs in the Iranian context. A descriptive-survey method was used in this research; the statistical population, selected based on the purposive sampling method, includes 30 construction experts with hands-on experience in CRCBPs. A questionnaire related to the risk identification stage was developed based on a detailed study of the research literature and also using the Delphi survey method; 82 various risks were finally identified. In order to confirm the opinions of experts in identifying the potential risks, Kendall’s coefficient of concordance was used. In the first stage of data analysis, qualitative evaluation was performed by calculating the severity of risk effect and determining the cumulative risk index, based on which 25 CRFs of CRCBPs were identified for more accurate evaluation. At this stage, the identified CRFs were evaluated based on multi-criteria decision-making techniques and using the TOPSIS technique. Results show that the ten CRFs of CRCBPs are external threats from international relations, exchange rate changes, bank interest rate fluctuations, traffic licenses, access to skilled labor, changes in regional regulations, the condition of adjacent buildings, fluctuations and changes in inflation, failure to select a suitable and qualified consultant, and employer’s previous experiences and records. Obviously, the current study’s results and findings can be considered by CRCBPs in both the private and public sectors for proper effective risk identification, evaluation, and mitigation.

Risk Assessment for the Establishment of Vespa mandarinia (Hymenoptera: Vespidae) in the Pacific Northwest, United States

The recent introduction of the Asian giant hornet, Vespa mandarinia Smith, in the United States in late 2019 has raised concerns about its establishment in the Pacific Northwest and its potential deleterious effects on honey bees, Apis spp., and their pollination services in the region. Therefore, we conducted a risk assessment of the establishment of V. mandarinia in Washington, Oregon, Montana, and Idaho on a county-by-county basis. Our highly conservative tier-1 qualitative and semiquantitative risk assessment relied on the biological requirements and ecological relationships of V. mandarinia in the environments of the Pacific Northwest. Our risk characterization was based on climate and habitat suitability estimates for V. mandarinia queens to overwinter and colonize nests, density and distribution of apiaries, and locations of major human-mediated introduction pathways that may increase establishment of the hornet in the counties. Our results suggest that 32 counties in the region could be at low risk, 120 at medium risk, and 23 at high risk of establishment. Many of the western counties in the region were estimated to be at the highest risk of establishment mainly because of their suitable climate for queens to overwinter, dense forest biomass for nest colonization, and proximity to major port and freight hubs in the region. By design, our tier-1 risk assessment most likely overestimates the risk of establishment, but considering its negative effects, these counties should be prioritized in ongoing monitoring and eradication efforts of V. mandarinia.

Developing Bayesian networks in managing the risk of Legionella colonisation of groundwater aeration systems

An Australian water utility has developed a Legionella High Level Risk Assessment (LHLRA) which provides a semi-qualitative assessment of the risk of Legionella proliferation and human exposure in engineered water systems using a combination of empirical observation and expert knowledge. Expanding on this LHLRA, we propose two iterative Bayesian network (BN) models to reduce uncertainty and allow for a probabilistic representation of the mechanistic interaction of the variables, built using data from 25 groundwater treatment plants. The risk of Legionella exposure in groundwater aeration units was quantified as a function of five critical areas including hydraulic conditions, nutrient availability and growth, water quality, system design (and maintenance), and location and access. First, the mechanistic relationship of the variables was conceptually mapped into a fishbone diagram, parameterised deterministically using an expert elicited weighted scoring system and translated into BN. The "sensitivity to findings" analysis of the BN indicated that system design was the most influential variable while elemental accumulation thresholds were the least influential variable for Legionella exposure. The diagnostic inference was used in high and low-risk scenarios to demonstrate the capabilities of the BNs to examine probable causes for diverse conditions. Subsequently, the causal relationship of Legionella growth and human exposure were improved through a conceptual bowtie representation. Finally, an improved model developed the predictors of Legionella growth and the risk of human exposure through the interaction of operational, water quality monitoring, operational parameters, and asset conditions. The use of BNs modelling based on risk estimation and improved functional decision outputs offer a complementary and more transparent alternative approach to quantitative analysis of uncertainties than the current LHLRA.

Historical trends of the ecotoxicological pesticide risk from the main grain crops in Rolling Pampa (Argentina)

We showed the results of the first long-term analysis (1987-2019) of pesticide (herbicides, fungicides and insecticides) impact in the Rolling Pampa, one of the main agricultural areas of Argentina. Using a clear and meaningful tool, based not only on acute toxicity but also on scaling up the results to total sown area, we identified time trends for both pesticide impact and the ecoefficiency of modal pesticide profiles. By the end of the time series, soybean showed a pesticide impact four times greater than maize crop in the studied area. However, the time trend in the subperiod (2012-2019) showed a sustainable pattern of pesticide use in soybean crop, with an improvement in its ecoefficiency. Oppositely, maize showed a relatively constant ecoefficiency value during most of the time series, suggesting a possible path towards an unsustainable cropping system. Findings from this study suggest that some efforts have to be made to improve the pest management decisions towards a more efficient pesticide profiles in maize crop and to keep improving the ecotoxicity pesticide profile in soybean crops because of its large sown area in the studied area.

Selecting Appropriate Words for Naming the Rows and Columns of Risk Assessment Matrices

The risk management systems used in occupational safety and health typically assess the risk of identified hazards using a tabular format commonly called a risk assessment matrix. Typically, columns are named with words indicating severity, and rows are named with words indicating likelihood or probability. Some risk assessment matrices use words reflecting the extent of exposure to a hazard. This project was undertaken with the aim of helping the designers of risk assessment matrices select appropriate names for the rows and columns. A survey of undergraduate students studying engineering or occupational safety and health obtained ratings of 16 English language words and phrases for each of the three factors. Analyses of 84 completed surveys included comparing average ratings on a 100-point scale. Using the averages, appropriately spaced sets of words and phrases were identified for naming the row and column categories. Based on results, the authors recommend word sets of three, four, and five for severity; three, four, five, and six for likelihood; and two and three for extent of exposure. The study methodology may be useful for future research, and the resulting word sets and numerical ratings may be helpful when creating a new, or reassessing an established, risk assessment matrix.

A Qualitative Risk Assessment of Rabies Reintroduction Into the Rabies Low-Risk Zone of Bhutan

In Bhutan, dog-mediated rabies has been successfully eliminated from most regions of the country but remains endemic in the Southern region and sporadic incursions are also reported in the East. Elimination of rabies from the southern part of Bhutan is challenged by the porous border with the neighboring states of India which facilitates free and unregulated movement of animals. Around 17 outbreaks of rabies are reported annually in dogs and other domestic animals, posing continuous public health risks and economic losses. Furthermore, due to anthropogenic factors, such as increasing human settlements along highways, increased animal transportation, and the complex and changing human-pet relationship, there is potential to reintroduce rabies from rabies high-risk zone to rabies low-risk zone. This study was undertaken to estimate the risk of rabies re-introduction to the rabies low-risk zone by performing a qualitative risk assessment. The assessment was conducted for three risk pathways (stray dog-pathway, pet dog-pathway and cattle-pathway) under two scenarios: (1) no risk mitigation measures in place and (2) current risk mitigation measures in place. The current control measures include Government led programs, such as mass dog vaccination and dog population management, regulation of the movment of animals through pre-travel check-up and health certification, regular awareness education and rabies surveillance in the rabies endemic areas. The probability of an event occurring was assigned using the data from the available literature. Where gaps in knowledge existed, expert opinion, elicited through modified Delphi method, was used. Under the scenario in which no risk mitigation measures were in place, the risk of rabies re-introduction was estimated to be medium for the stray-dog pathway with a low level of uncertainty, low for pet-dog pathway with a low level of uncertainty, and very low for the cattle-pathway with a medium level of uncertainty. When current risk-mitigation measures were included, the risk of rabies reintroduction was estimated to be very low for the stray-dog pathway with a medium level of uncertainty, low for the pet dog-pathway with a low level of uncertainty, and extremely low for the cattle-pathway with a medium level of uncertainty. The risk of rabies re-introduction through all the pathways was greater than negligible. These findings highlight the importance of maintaining and enhancing current risk mitigation measures to prevent re-introduction of rabies into rabies low-risk zone.

A framework to support risk assessment in hospitals

Quality problem or issue

A number of challenges have been identified with current risk assessment practice in hospitals, including: a lack of consultation with a sufficiently wide group of stakeholders; a lack of consistency and transparency; and insufficient risk assessment guidance. Consequently, risk assessment may not be fully effective as a means to ensure safety.

Initial assessment

We used a V system developmental model, in conjunction with mixed methods, including interviews and document analysis to identify user needs and requirements.

Choice of solution

One way to address current challenges is through providing good guidance on the fundamental aspects of risk assessment. We designed a risk assessment framework, comprising: a risk assessment model that depicts the main risk assessment steps; risk assessment explanation cards that provide prompts to help apply each step; and a risk assessment form that helps to systematize the risk assessment and document the findings.

Implementation

We conducted multiple group discussions to pilot the framework through the use of a representative scenario and used our findings for the user evaluation.

Evaluation

User evaluation was conducted with 10 participants through interviews and showed promising results.

Lessons learned

While the framework was recommended for use in practice, it was also proposed that it be adopted as a training tool. With its use in risk assessment, we anticipate that risk assessments would lead to more effective decisions being made and more appropriate actions being taken to minimize risks. Consequently, the quality and safety of care delivered could be improved.

Understanding BRCA Mutation Carriers' Preferences for Communication of Genetic Modifiers of Breast Cancer Risk

Refined estimates of risk based on genetic risk modifiers could assist BRCA mutation carriers in understanding their risk, but it is not clear whether carriers are interested in receiving these estimates or how they might benefit from them. Using qualitative interviews, we investigated female BRCA1 and BRCA2 mutation carriers' (N = 20) reactions to numerical and verbal presentations of breast cancer risk based on risk modifiers and assessed women's preferences regarding visual formats for communicating risk. Our results show carriers are interested in receiving refined risk estimates and suggest the estimates may influence decision-making regarding cancer prevention, depending on the nature of the risk assessment. Although accurate and precise estimates of breast cancer risk are most important to women, they preferred quantitative risk estimates expressed as a proportion with or without a population comparison; however, women noted that comparisons to other BRCA mutation carriers were less useful given their high risk. Participants also preferred communication of a risk as a specific percentage versus a range of risk, but a clear preference regarding visual displays was not expressed. Results support many existing recommendations for genetic risk communication and provide guidance for the development of tools incorporating genetic risk modifiers.

A Review of Risk Matrices Used in Acute Hospitals in England

In healthcare, patient safety has received substantial attention and, in turn, a number of approaches to managing safety have been adopted from other high-risk industries. One of these has been risk assessment, predominantly through the use of risk matrices. However, while other industries have criticized the design and use of these risk matrices, the applicability of such criticism has not been investigated formally in healthcare. This study examines risk matrices as used in acute hospitals in England and the guidance provided for their use. It investigates the applicability of criticisms of risk matrices from outside healthcare through a document analysis of the risk assessment policies, procedures, and strategies used in English hospitals. The findings reveal that there is a large variety of risk matrices used, where the design of some might increase the chance of risk misprioritization. Additionally, findings show that hospitals may provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms of risk matrices. Consequently, this is likely to lead to variation in the quality of risk assessment and in the subsequent deployment of resources to manage the assessed risk. Finally, the article outlines ways in which hospitals could use risk matrices more effectively.

Injury Risk (Burden), Risk Matrices and Risk Contours in Team Sports: A Review of Principles, Practices and Problems

The aim of this review was to provide insights into and a critical assessment of injury burden, risk matrices and risk contours in the context of team sports. Injury burden is the product of injury incidence and mean severity, and is normally reported as days' absence/1000 player-hours. An important feature of injury burden is that equal values can reflect quite different numerical combinations of injury incidence and severity. The timeframe over which injury burden affects a team depends on the incidence and severity values of the injuries sustained. Injury burden is evaluated through the use of risk matrices and risk contours. The main benefits of using risk matrices, and the reasons for their widespread acceptance, are the minimal data inputs required, the ease of understanding the visual data presentation, the transparent nature of the evaluation criteria and the simplicity with which the conclusions can be communicated to stakeholders. Injury burden is most often used for the identification of injuries that cause the greatest loss of time for players, ranking the importance of injury risk factors and prioritising injury prevention plans. Although risk matrices are commonly used for evaluating risks during the risk assessment process, there is little evidence to demonstrate that they improve decision-making, as they have a number of limitations, including potential inconsistencies and discrepancies when evaluating and ranking risks. These limitations suggest that physicians, physiotherapists and sports scientists should only use injury burden, risk matrices and risk contours when they fully understand their strengths and weaknesses.

Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors

Part of the ecological risk assessment process involves examining the potential for environmental stressors and ecological receptors to co-occur across a landscape. In this study, we introduce a Bayesian joint modeling framework for use in evaluating and mapping the co-occurrence of stressors and receptors using empirical data, open-source statistical software, and Geographic Information Systems tools and data. To illustrate the approach, we apply the framework to bioassessment data on stream fishes and nutrients collected from a watershed in southwestern Ohio. The results highlighted the joint model's ability to parse and exploit statistical dependencies in order to provide empirical insight into the potential environmental and ecotoxicological interactions influencing co-occurrence. We also demonstrate how probabilistic predictions can be generated and mapped to visualize spatial patterns in co-occurrences. For practitioners, we believe that this data-driven approach to modeling and mapping co-occurrence can lead to more quantitatively transparent and robust assessments of ecological risk.

Maximum entropy modeling risk of anthrax in the Republic of Kazakhstan

The objective of this study was to zone the territory of the Republic of Kazakhstan (RK) into risk categories according to the probability of anthrax emergence in farm animals as stipulated by the re-activation of preserved natural foci. We used historical data on anthrax morbidity in farm animals during the period 1933 - 2014, collected by the veterinary service of the RK. The database covers the entire territory of the RK and contains 4058 anthrax outbreaks tied to 1798 unique locations. Considering the strongly pronounced natural focality of anthrax, we employed environmental niche modeling (Maxent) to reveal patterns in the outbreaks' linkages to specific combinations of environmental factors. The set of bioclimatic factors BIOCLIM, derived from remote sensing data, the altitude above sea level, the land cover type, the maximum green vegetation fraction (MGVF) and the soil type were examined as explanatory variables. The model demonstrated good predictive ability, while the MGVF, the bioclimatic variables reflecting precipitation level and humidity, and the soil type were found to contribute most significantly to the model. A continuous probability surface was obtained that reflects the suitability of the study area for the emergence of anthrax outbreaks. The surface was turned into a categorical risk map by averaging the probabilities within the administrative divisions at the 2nd level and putting them into four categories of risk, namely: low, medium, high and very high risk zones, where very high risk refers to more than 50% suitability to the disease re-emergence and low risk refers to less than 10% suitability. The map indicated increased risk of anthrax re-emergence in the districts along the northern, eastern and south-eastern borders of the country. It was recommended that the national veterinary service uses the risk map for the development of contra-epizootic measures aimed at the prevention of anthrax re-emergence in historically affected regions of the RK. The map can also be considered when developing large-scale construction projects in the areas comprising preserved soil foci of anthrax.

Long-term trends in the intensity and relative toxicity of herbicide use

Herbicide use is among the most criticized aspects of modern farming, especially as it relates to genetically engineered (GE) crops. Many previous analyses have used flawed metrics to evaluate herbicide intensity and toxicity trends. Here, I show that herbicide use intensity increased over the last 25 years in maize, cotton, rice and wheat. Although GE crops have been previously implicated in increasing herbicide use, herbicide increases were more rapid in non-GE crops. Even as herbicide use increased, chronic toxicity associated with herbicide use decreased in two out of six crops, while acute toxicity decreased in four out of six crops. In the final year for which data were available (2014 or 2015), glyphosate accounted for 26% of maize, 43% of soybean and 45% of cotton herbicide applications. However, due to relatively low chronic toxicity, glyphosate contributed only 0.1, 0.3 and 3.5% of the chronic toxicity hazard in those crops, respectively.

A preliminary spatial assessment of risk: Marine birds and chronic oil pollution on Canada's Pacific coast

Chronic oil pollution poses substantial risks to marine birds and other marine wildlife worldwide. On Canada's Pacific coast, the negative ecological consequences to marine birds and marine ecosystems in general remain poorly understood. Using information relating to oil spill probability of occurrence, areas of overall importance to marine birds, and the at-sea distribution and density of 12 marine bird species and seven bird groups, including multiple Species at Risk, we undertook a spatial assessment of risk. Our results identify two main areas important to marine birds potentially at higher risk of exposure to oil. For individual bird species or species groups, those predicted to have elevated bird densities near the mainland and the northeast coast of Vancouver Island were identified as being at higher potential risk of exposure. Our results, however, should be considered preliminary. As with other anthropogenic stressors, in order to better understand and subsequently mitigate the consequences of chronic oil pollution on marine birds, improved information relating to marine birds and the occurrence of oil spills on Canada's Pacific coast is needed.

Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides

Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically considered an improvement over simply comparing the amount of herbicides applied by weight. Herbicides are treated differently compared to other pesticide groups when calculating the EIQ, and therefore, it is important to understand how different risk factors affect the EIQ for herbicides. The purpose of this work was to evaluate the suitability of the EIQ as an environmental indicator for herbicides. Simulation analysis was conducted to quantify relative sensitivity of the EIQ to changes in risk factors, and actual herbicide EIQ values were used to quantify the impact of herbicide application rate on the EIQ Field Use Rating. Herbicide use rate was highly correlated with the EIQ Field Use Rating (Spearman's rho >0.96, P-value <0.001) for two herbicide datasets. Two important risk factors for herbicides, leaching and surface runoff potential, are included in the EIQ calculation but explain less than 1% of total variation in the EIQ. Plant surface half-life was the risk factor with the greatest relative influence on herbicide EIQ, explaining 26 to 28% of the total variation in EIQ for actual and simulated EIQ values, respectively. For herbicides, the plant surface half-life risk factor is assigned values without any supporting quantitative data, and can result in EIQ estimates that are contrary to quantitative risk estimates for some herbicides. In its current form, the EIQ is a poor measure of herbicide environmental impact.

The Assessment of African Swine Fever Virus Risk to Belgium Early 2014, using the Quick and Semiquantitative Pandora Screening Protocol

A risk assessment was organized during the early EU ASF outbreaks of early 2014 (February-April) and performed in cooperation with 15 Belgian and European experts on ASFV and its epidemiology in pigs/wild boar. African swine fever (ASF) is considered as one of the most dangerous infectious pig diseases, causing many outbreaks. Since the end of 2013 - early 2014, several outbreaks within the European Union (Lithuania, Poland, Estonia and Latvia) were reported to OIE, which prompted several risk assessments by (inter)national bodies and scientists. In this study, the open source, semiquantitative Pandora risk assessment tool was used for a quick overall screening of the risk posed by ASF to Belgium early 2014. A set of integrated risk scores was calculated within the Pandora framework. Experts scored the questions and uncertainty levels in the Pandora modules individually, after which the calculations were performed and averaged scores were used within pre-defined risk scales to define and visualize the ASF risk to Belgium. Emergence risk was considered low (Pandora score 0.29), while disease consequences were deemed high (0.93); the resulting multiplicative overall risk of ASFV for Belgium was low (0.27). The Belgian experts tended to give lower risk scores than the European experts, especially for entry risk and trade/public opinion consequences. These risk scores are further interpreted with a due consideration of the qualitative data in the expert remarks and of other ASF risk assessments. The results are similar to more extensive and elaborate risk assessment models/procedures which may require more time and resources. The Pandora tool allows sequential updates to monitor (rates of) increasing risk and provides information for risk managers to organize targeted control.

A quantitative approach for integrating multiple lines of evidence for the evaluation of environmental health risks

Decision analysis often considers multiple lines of evidence during the decision making process. Researchers and government agencies have advocated for quantitative weight-of-evidence approaches in which multiple lines of evidence can be considered when estimating risk. Therefore, we utilized Bayesian Markov Chain Monte Carlo to integrate several human-health risk assessment, biomonitoring, and epidemiology studies that have been conducted for two common insecticides (malathion and permethrin) used for adult mosquito management to generate an overall estimate of risk quotient (RQ). The utility of the Bayesian inference for risk management is that the estimated risk represents a probability distribution from which the probability of exceeding a threshold can be estimated. The mean RQs after all studies were incorporated were 0.4386, with a variance of 0.0163 for malathion and 0.3281 with a variance of 0.0083 for permethrin. After taking into account all of the evidence available on the risks of ULV insecticides, the probability that malathion or permethrin would exceed a level of concern was less than 0.0001. Bayesian estimates can substantially improve decisions by allowing decision makers to estimate the probability that a risk will exceed a level of concern by considering seemingly disparate lines of evidence.

A probabilistic analysis reveals fundamental limitations with the environmental impact quotient and similar systems for rating pesticide risks

Comparing risks among pesticides has substantial utility for decision makers. However, if rating schemes to compare risks are to be used, they must be conceptually and mathematically sound. We address limitations with pesticide risk rating schemes by examining in particular the Environmental Impact Quotient (EIQ) using, for the first time, a probabilistic analytic technique. To demonstrate the consequences of mapping discrete risk ratings to probabilities, adjusted EIQs were calculated for a group of 20 insecticides in four chemical classes. Using Monte Carlo simulation, adjusted EIQs were determined under different hypothetical scenarios by incorporating probability ranges. The analysis revealed that pesticides that have different EIQs, and therefore different putative environmental effects, actually may be no different when incorporating uncertainty. The EIQ equation cannot take into account uncertainty the way that it is structured and provide reliable quotients of pesticide impact. The EIQ also is inconsistent with the accepted notion of risk as a joint probability of toxicity and exposure. Therefore, our results suggest that the EIQ and other similar schemes be discontinued in favor of conceptually sound schemes to estimate risk that rely on proper integration of toxicity and exposure information.

Selective breeding in fish and conservation of genetic resources for aquaculture

To satisfy increasing demands for fish as food, progress must occur towards greater aquaculture productivity whilst retaining the wild and farmed genetic resources that underpin global fish production. We review the main selection methods that have been developed for genetic improvement in aquaculture, and discuss their virtues and shortcomings. Examples of the application of mass, cohort, within family, and combined between-family and within-family selection are given. In addition, we review the manner in which fish genetic resources can be lost at the intra-specific, species and ecosystem levels and discuss options to best prevent this. We illustrate that fundamental principles of genetic management are common in the implementation of both selective breeding and conservation programmes, and should be emphasized in capacity development efforts. We highlight the value of applied genetics approaches for increasing aquaculture productivity and the conservation of fish genetic resources.

The rise and fall of a regulator: adventure sports in the United kingdom

Following a tragic accident in 1993 involving the deaths of teenagers while kayaking a new regulatory regime was imposed upon some adventure sports providers in the United Kingdom. In particular, a new regulatory body, the Adventure Activities Licensing Authority (AALA), was established to oversee the sector. Yet in 2010, a government-sponsored review recommended that AALA be abolished and this recommendation has been quickly accepted by government. This article explores the background to these developments through documentation, interviews with those affected by the AALA regime, and court cases. Evidence reported here, perhaps surprising, is that AALA itself is seen in a very positive light by many, even those it regulates. What may have happened is that AALA became caught up in a wider debate about the place and management of risk in life beyond the workplace, which has been simmering in the United Kingdom for a decade or more, and of which it fell foul. It may also be that adventure sports, because they entail voluntary engagement with high consequence hazards, starkly expose serious questions about the application of conventional, factory-originated risk assessment approaches to life in general.

Qualitative risk assessment of the acquisition of Meticillin-resistant staphylococcus aureus in pet dogs

This article presents a qualitative risk assessment of the acquisition of meticillin-resistant Staphylococcus aureus (MRSA) in pet dogs, representing an important first step in the exploration of risk of bidirectional MRSA transfer between dogs and humans. A conceptual model of the seven potential pathways for MRSA acquisition in a dog in any given 24-hour period was developed and the data available to populate that model were considered qualitatively. Humans were found to represent the most important source of MRSA for dogs in both community and veterinary hospital settings. The environment was found to be secondary to humans in terms of importance and other dogs less still. This study highlights some important methodological limitations of a technique that is heavily relied upon for qualitative risk assessments and applies a novel process, the use of relative risk ranking, to enable the generation of a defensible output using a matrix combination approach. Given the limitations of the prescribed methods as applied to the problem under consideration, further validation, or repudiation, of the findings contained herein is called for using a subsequent quantitative assessment.

Assessing potential human health hazards and benefits from subtherapeutic antibiotics in the United States: tetracyclines as a case study

Many scientists, activists, regulators, and politicians have expressed urgent concern that using antibiotics in food animals selects for resistant strains of bacteria that harm human health and bring nearer a "postantibiotic era" of multidrug resistant "super-bugs." Proposed political solutions, such as the Preservation of Antibiotics for Medical Treatment Act (PAMTA), would ban entire classes of subtherapeutic antibiotics (STAs) now used for disease prevention and growth promotion in food animals. The proposed bans are not driven by formal quantitative risk assessment (QRA), but by a perceived need for immediate action to prevent potential catastrophe. Similar fears led to STA phase-outs in Europe a decade ago. However, QRA and empirical data indicate that continued use of STAs in the United States has not harmed human health, and bans in Europe have not helped human health. The fears motivating PAMTA contrast with QRA estimates of vanishingly small risks. As a case study, examining specific tetracycline uses and resistance patterns suggests that there is no significant human health hazard from continued use of tetracycline in food animals. Simple hypothetical calculations suggest an unobservably small risk (between 0 and 1.75E-11 excess lifetime risk of a tetracycline-resistant infection), based on the long history of tetracycline use in the United States without resistance-related treatment failures. QRAs for other STA uses in food animals also find that human health risks are vanishingly small. Whether such QRA calculations will guide risk management policy for animal antibiotics in the United States remains to be seen.

Evidence-based semiquantitative methodology for prioritization of foodborne zoonoses

OBJECTIVES

To prioritize an extended list of food- and water-borne zoonoses to allow food safety authorities to focus on the most relevant hazards in the food chain.

METHODS

An evidence-based semiquantitative methodology was developed. Scores were given by 35 scientific experts in the field of animal and public health, food, and clinical microbiology and epidemiology to 51 zoonotic agents according to five criteria related to public health (severity and occurrence in humans), animal health (severity of disease coupled with economic consequences and occurrence in animals), and food (occurrence in food). The scoring procedure was standardized and evidence-based as experts were provided, for each zoonotic agent, a same set of up-to-date help information data related to the five criteria. Independently, the relative importance of the five criteria was weighted by seven food chain risk managers. The zoonotic agents were ranked based on overall weighted scores and were grouped in four statistically different levels of importance.

RESULTS

The following foodborne zoonotic pathogens were classified as "most important": Salmonella spp., Campylobacter spp., Listeria monocytogenes, and verocytotoxigenic Escherichia coli. A second group of "significant importance" included Toxoplasma gondii, the agent of bovine spongiform encephalopathy, Clostridium botulinum, Staphylococcus aureus, Cryptosporidium parvum, Mycobacterium bovis, Echinococcus granulosus, Streptococcus spp., Echinococcus multilocularis, Yersinia enterocolitica, Mycobacterium avium, Fasciola hepatica, Giardia intestinalis, and Rotavirus.

CONCLUSIONS

This methodology allowed to rank 51 zoonotic agents with objectivity and taking account of a combined input from risk assessors and risk managers.

APPLICATIONS

These results support food safety policy makers to establish the multiannual monitoring program of foodborne zoonoses. They also enable to identify knowledge gaps on specific zoonotic agents and to formulate key research questions. Principally, this method of prioritization is of general interest as it can be applied for any other ranking exercise and in any country.

Ranking the risks from multiple hazards in a small community

Natural hazards, human-induced accidents, and malicious acts have caused great losses and disruptions to society. After September 11, 2001, critical infrastructure protection has become a national focus in the United States and is likely to remain one for the foreseeable future. Damage to the infrastructures and assets could be mitigated through predisaster planning and actions. A systematic methodology was developed to assess and rank the risks from these multiple hazards in a community of 20,000 people. It is an interdisciplinary study that includes probabilistic risk assessment (PRA), decision analysis, and expert judgment. Scenarios are constructed to show how the initiating events evolve into undesirable consequences. A value tree, based on multi-attribute utility theory (MAUT), is used to capture the decisionmaker's preferences about the impacts on the infrastructures and other assets. The risks from random failures are ranked according to their expected performance index (PI), which is the product of frequency, probabilities, and consequences of a scenario. Risks from malicious acts are ranked according to their PI as the frequency of attack is not available. A deliberative process is used to capture the factors that could not be addressed in the analysis and to scrutinize the results. This methodology provides a framework for the development of a risk-informed decision strategy. Although this study uses the Massachusetts Institute of Technology campus as a case study of a real project, it is a general methodology that could be used by other similar communities and municipalities.

A qualitative assessment of Toxoplasma gondii risk in ready-to-eat smallgoods processing

Toxoplasma gondii is one of the most common parasitic infections of humans and other warm-blooded animals. In most adults, it does not cause serious illness, but severe disease may result from infection in fetuses and immunocompromised people. Consumption of raw or undercooked meats has consistently been identified as an important source of exposure to T. gondii. Several studies indicate the potential failure to inactivate T. gondii in the processes of cured meat products, This article presents a qualitative risk-based assessment of the processing of ready-to-eat smallgoods, which include cooked or uncooked fermented meat, pâté, dried meat, slow cured meat, luncheon meat, and cooked muscle meat including ham and roast beef. The raw meat ingredients are rated with respect to their likelihood of containing T. gondii cysts and an adjustment is made based on whether all the meat from a particular source is frozen. Next, the effectiveness of common processing steps to inactivate T. gondii cysts is assessed, including addition of spices, nitrates, nitrites and salt, use of fermentation, smoking and heat treatment, and the time and temperature during maturation. It is concluded that processing steps that may be effective in the inactivation of T. gondii cysts include freezing, heat treatment, and cooking, and the interaction between salt concentration, maturation time, and temperature. The assessment is illustrated using a Microsoft Excel-based software tool that was developed to facilitate the easy assessment of four hypothetical smallgoods products.

What's wrong with risk matrices?

Risk matrices-tables mapping "frequency" and "severity" ratings to corresponding risk priority levels-are popular in applications as diverse as terrorism risk analysis, highway construction project management, office building risk analysis, climate change risk management, and enterprise risk management (ERM). National and international standards (e.g., Military Standard 882C and AS/NZS 4360:1999) have stimulated adoption of risk matrices by many organizations and risk consultants. However, little research rigorously validates their performance in actually improving risk management decisions. This article examines some mathematical properties of risk matrices and shows that they have the following limitations. (a) Poor Resolution. Typical risk matrices can correctly and unambiguously compare only a small fraction (e.g., less than 10%) of randomly selected pairs of hazards. They can assign identical ratings to quantitatively very different risks ("range compression"). (b) Errors. Risk matrices can mistakenly assign higher qualitative ratings to quantitatively smaller risks. For risks with negatively correlated frequencies and severities, they can be "worse than useless," leading to worse-than-random decisions. (c) Suboptimal Resource Allocation. Effective allocation of resources to risk-reducing countermeasures cannot be based on the categories provided by risk matrices. (d) Ambiguous Inputs and Outputs. Categorizations of severity cannot be made objectively for uncertain consequences. Inputs to risk matrices (e.g., frequency and severity categorizations) and resulting outputs (i.e., risk ratings) require subjective interpretation, and different users may obtain opposite ratings of the same quantitative risks. These limitations suggest that risk matrices should be used with caution, and only with careful explanations of embedded judgments.

Critical asset and portfolio risk analysis: an all-hazards framework

This article develops a quantitative all-hazards framework for critical asset and portfolio risk analysis (CAPRA) that considers both natural and human-caused hazards. Following a discussion on the nature of security threats, the need for actionable risk assessments, and the distinction between asset and portfolio-level analysis, a general formula for all-hazards risk analysis is obtained that resembles the traditional model based on the notional product of consequence, vulnerability, and threat, though with clear meanings assigned to each parameter. Furthermore, a simple portfolio consequence model is presented that yields first-order estimates of interdependency effects following a successful attack on an asset. Moreover, depending on the needs of the decisions being made and available analytical resources, values for the parameters in this model can be obtained at a high level or through detailed systems analysis. Several illustrative examples of the CAPRA methodology are provided.