What's wrong with risk matrices?

Colorectal cancer risk mapping through Bayesian networks

BACKGROUND AND OBJECTIVE

Only about 14% of eligible EU citizens finally participate in colorectal cancer (CRC) screening programs despite it being the third most common type of cancer worldwide. The development of CRC risk models can enable predictions to be embedded in decision-support tools facilitating CRC screening and treatment recommendations. This paper develops a predictive model that aids in characterizing CRC risk groups and assessing the influence of a variety of risk factors on the population.

METHODS

A CRC Bayesian Network is learnt by aggregating extensive expert knowledge and data from an observational study and making use of structure learning algorithms to model the relations between variables. The network is then parametrised to characterize these relations in terms of local probability distributions at each of the nodes. It is finally used to predict the risks of developing CRC together with the uncertainty around such predictions.

RESULTS

A graphical CRC risk mapping tool is developed from the model and used to segment the population into risk subgroups according to variables of interest. Furthermore, the network provides insights on the predictive influence of modifiable risk factors such as alcohol consumption and smoking, and medical conditions such as diabetes or hypertension linked to lifestyles that potentially have an impact on an increased risk of developing CRC.

CONCLUSION

CRC is most commonly developed in older individuals. However, some modifiable behavioral factors seem to have a strong predictive influence on its potential risk of development. Modeling these effects facilitates identifying risk groups and targeting influential variables which are subsequently helpful in the design of screening and treatment programs.

A navigational risk evaluation of ferry transport: Continuous risk management matrix based on fuzzy Best-Worst Method

Ferry transport has witnessed numerous fatal accidents due to unsafe navigation; thus, it is of paramount importance to mitigate risks and enhance safety measures in ferry navigation. This paper aims to evaluate the navigational risk of ferry transport by a continuous risk management matrix (CRMM) based on the fuzzy Best-Worst Method (BMW). Its originalities include developing CRMM to figure out the risk level of risk factors (RFs) for ferry transport and adopting fuzzy BWM to estimate the probability and severity weights vector of RFs. Empirical results show that twenty RFs for ferry navigation are divided into four zones corresponding to their risk values, including extreme-risk, high-risk, medium-risk, and low-risk areas. Particularly, results identify three extreme-risk RFs: inadequate evacuation and emergency response features, marine traffic congestion, and insufficient training on navigational regulations. The proposed research model can provide a methodological reference to the pertinent studies regarding risk management and multiple-criteria decision analysis (MCDA).

Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship

The arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and the model structure is developed using Bayesian Networks. To this end, an extensive literature survey is conducted, enhanced with the domain knowledge elicited from the experts and improved by the experimental data obtained during representative MASS model trials carried out in an inland river. Conditional Probability Tables are generated using a new function employing expert feedback regarding Interval Type 2 Fuzzy Sets. The developed Bayesian model yields the expected utilities results representing an accident's probability and consequence, with the results visualized on a dedicated diagram. Finally, the developed risk assessment model is validated by conducting three axiom tests, extreme scenarios analysis, and sensitivity analysis. Navigational environment, natural environment, traffic complexity, and shore-ship collaboration performance are critical from the probability and consequence perspective for inland navigational accidents to a remotely controlled MASS. Lastly, important nodes to Shore-Ship collaboration performance include autonomy of target ships, cyber risk, and transition from other remote control centers.

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.

Potential risk assessment: a model for quality evaluation in fluoroscopy-guided interventional procedures

This study presented a model applied for potential risk assessment in an interventional radiology setting. The model of potential risk assessment (MARP) consisted of the creation of a scale of indicators ranging from 0 to 5. The radiation levels were categorized according to gender, kind of procedure, value of kerma air product (Pka), and accumulated radiation dose (mGy). The MARP model was applied in 121 institutions over 8 y. A total of 201 656 patient radiation doses (Dose-area product and accumulated kerma) data were launched into the system over time, with an average of 22 406 doses per year. In the context of the workers (cardiologists, radiographers, and nurses) monitored during the MARP application, 8007 cases (with an average of 890 per year) of occupational radiation doses were recorded. This study showed a strategy for quality evaluation in fluoroscopy using a model with a compulsory information system for monitoring safety.

A framework for risk matrix design: A case of MASS navigation risk

Risk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework for developing a risk matrix based on fuzzy Analytic Hierarchy Process (AHP) is proposed. In this framework, a linear function is defined where the risk index is treated as a response variable, while the probability and consequence indices are explanatory variables, with weights of these two indices representing their importance on given risk level. This significance is assessed by experts and quantified using AHP in interval type 2 fuzzy environment. A continuous risk diagram is then created and converted into a risk matrix that can be improved. To verify the feasibility of the proposed framework, a risk matrix is designed in the context of MASS grounding. The results show that the proposed approach is feasible. Our discussion results can provide new insights for the design of risk matrices and promote the management of MASS navigational risks.

What can Safety Cases offer for patient safety? A multisite case study

BACKGROUND

The Safety Case is a regulatory technique that requires organisations to demonstrate to regulators that they have systematically identified hazards in their systems and reduced risks to being as low as reasonably practicable. It is used in several high-risk sectors, but only in a very limited way in healthcare. We examined the first documented attempt to apply the Safety Case methodology to clinical pathways.

METHODS

Data are drawn from a mixed-methods evaluation of the Safer Clinical Systems programme. The development of a Safety Case for a defined clinical pathway was a centrepiece of the programme. We base our analysis on 143 interviews covering all aspects of the programme and on analysis of 13 Safety Cases produced by clinical teams.

RESULTS

The principles behind a proactive, systematic approach to identifying and controlling risk that could be curated in a single document were broadly welcomed by participants, but was not straightforward to deliver. Compiling Safety Cases helped teams to identify safety hazards in clinical pathways, some of which had been previously occluded. However, the work of compiling Safety Cases was demanding of scarce skill and resource. Not all problems identified through proactive methods were tractable to the efforts of front-line staff. Some persistent hazards, originating from institutional and organisational vulnerabilities, appeared also to be out of the scope of control of even the board level of organisations. A particular dilemma for organisational senior leadership was whether to prioritise fixing the risks proactively identified in Safety Cases over other pressing issues, including those that had already resulted in harm.

CONCLUSIONS

The Safety Case approach was recognised by those involved in the Safer Clinical Systems programme as having potential value. However, it is also fraught with challenge, highlighting the limitations of efforts to transfer safety management practices to healthcare from other sectors.

A critical review of risk matrices used in water safety planning: improving risk matrix construction

Risk matrices are used in water safety planning to prioritize improvements to drinking water systems. While water safety plans (WSPs) are promoted globally, no study has evaluated whether risk matrices are comprehensively constructed to accurately assess risk. We used risk matrix criteria adapted from previous risk matrix research to evaluate risk matrices found in twelve templates across global jurisdictions. WSP templates were found using the WSPortal website and definitions of likelihood and impact were extracted from each template to assist in the evaluation of WSP risk matrices. Application of the criteria developed from a detailed mathematical analysis by revealed that 11 of 12 risk matrices evaluated contravene at least one of the risk matrix criteria. Furthermore, definitions of likelihood and impact varied widely across different jurisdictions, due in part to the system specific nature of the WSP methodology. To improve risk matrix construction, we recommend: setting clearer risk level boundary criteria, aligning specific impact category definitions with water system objectives, and selecting specific impact categories as opposed to defining impact in several ways. Finally, we recommend risk matrix construction be reviewed as part of the WSP process to ensure accurate identification of key risks in a water system.

Assessment of global shipping risk caused by maritime piracy

Due to the frequent occurrence of piracy incidents, normal trade, and transportation activities have been hindered. This paper uses the Piracy and Armed Robbery dataset in the Global Integrated Shipping Information System to analyze the types and evolutionary characteristics of shipping risk caused by piracy and the piracy behavior patterns in different seas. This study found that there are three regions with high incidence of piracy in the world, and their gathering centers change dynamically over time. Piracy incidents can be divided into four categories based on the quantitative assessment of shipping risk caused by piracy. Shipping risk caused by piracy shows different evolution characteristics in different seas, affected by factors such as the evolution of national political situations and anti-piracy measures. Based on the qualitative assessment of the shipping risk caused by piracy, the piracy corpus reflects the diverse patterns of piracy in different seas. In the process of pirate attacks, the diversity is mainly manifested in violence and selectivity. In the consequences of pirate attacks, the targets that pirates pay attention to vary significantly in different seas. This research will help to strengthen the dynamic monitoring of shipping risk caused by piracy, and further contribute to the research on maritime transport safety.

A framework for using data and collaboration to drive prevention through engineering design: Reducing injury and severity in greenhouse and nursery workers

INTRODUCTION

A framework of collaboration between safety professionals and design engineers was proposed that provided direction for utilizing analysis of quantitative and qualitative data to prevent worker injury. This interdisciplinary, context-steeped approach can be utilized across a variety of industries to promote risk reduction by designing equipment and processes to prevent common workplace injuries in the first place. Safety professional expertise in regional worker's compensation claims analysis (including statistical analysis on a quantitative basis and qualitative analysis of trends in written injury descriptions of circumstance) provided the starting point for identifying industries of interest for this approach.

METHOD

Followed by education of design engineers on safety approaches (including hazard identification, the ANSI/ASSP Z590.3 consensus-based standard), tools such as risk assessment matrices and methods for effective on-site work observation and interviews with workers affords transfer of knowledge. Design engineers then utilize safety influenced design problem identification and goal criteria to create and select concepts for eventual detail design and prototype testing on-site. This approach was implemented in a case-study at a Midwest greenhouse industry facility site in summer of 2019. Two problem areas were identified and addressed with two unique engineering designs that were prototyped and utilized at the facility with success.

PRACTICAL APPLICATION

This approach can apply to other industries and collaborative teams in the future to prevent worker injury by design.

A multiple criteria approach for building a pandemic impact assessment composite indicator: The case of COVID-19 in Portugal

The COVID-19 pandemic has caused major damage and disruption to social, economic, and health systems (among others). In addition, it has posed unprecedented challenges to public health and policy/decision-makers who have been responsible for designing and implementing measures to mitigate its strong negative impact. The Portuguese health authorities have used decision analysis techniques to assess the impact of the pandemic and implemented measures for counties, regions, or across the entire country. These decision tools have been subject to some criticism and many stakeholders requested novel approaches. In particular, those which considered the dynamic changes in the pandemic's behaviour due to new virus variants and vaccines. A multidisciplinary team formed by researchers from the COVID-19 Committee of Instituto Superior Técnico at the University of Lisbon (CCIST analyst team) and physicians from the Crisis Office of the Portuguese Medical Association (GCOM expert team) collaborated to create a new tool to help politicians and decision-makers to fight the pandemic. This paper presents the main steps that led to the building of a pandemic impact assessment composite indicator applied to the specific case of COVID-19 in Portugal. A multiple criteria approach based on an additive multi-attribute value theory aggregation model was used to build the pandemic assessment composite indicator. The parameters of the additive model were devised based on an interactive socio-technical and co-constructive process between the CCIST and GCOM team members. The deck of cards method was the adopted technical tool to assist in the assessment the value functions as well as in the assessment of the criteria weights. The final tool was presented at a press conference and had a powerful impact on the Portuguese media and on the main health decision-making stakeholders in the country. In this paper, a completed mathematical and graphical description of this tool is presented.

What is wrong with the Mission Dependency Index for US federal infrastructure decisions?

The Mission Dependency Index (MDI) is a risk metric used by US military services and federal agencies for guiding operations, management, and funding decisions for facilities. Despite its broad adoption for guiding the expenditure of billions in federal funds, several studies on MDI suggest it may have flaws that limit its efficacy. We present a detailed technical analysis of MDI to show how its flaws impact infrastructure decisions. We present the MDI used by the US Navy and develop a critique of current methods. We identify six problems with MDI that stem from its interpretation, use, and mathematical formulation, and we provide examples demonstrating how these flaws can bias decisions. We provide recommendations to overcome flaws for infrastructure risk decision making but ultimately recommend the US government develop a new metric less susceptible to bias.

Efficient Risk Mitigation Planning for a Clinical Trial

Each clinical trial faces numerous risks. Neglecting or reacting spontaneously at each materialized risk may delay trial completion, affect trial objectives and even derail the clinical trial. At the same time, pre-allocating excessive contingency resources to eliminate all potential risks, even with a low probability of occurrence and impact, may not be necessary. Therefore, optimal risk planning means finding the "right" balance between contingency resources, risk mitigation strategy, and risk tolerance. Most risk planning publications focus only on risk identification and risk assessment. Risk mitigation strategy planning is often overlooked. A contingency budget is routinely assigned as a percentage of a clinical trial budget, e.g., 10-20%, and is not aligned with the clinical trial risk level. Therefore, to derive an effective clinical trial risk mitigation strategy, a new methodology based on mathematical modeling was developed and validated for a Ph2 clinical trial.

A review of qualitative risk assessment in animal health: Suggestions for best practice

Qualitative risk assessment (QRA) can provide decision support in line with the requirement for an objective, unbiased assessment of disease risk according to the Agreement on the Application of Sanitary and Phytosanitary Measures of the World Trade Organization. However, in order for a QRA to be objective and consistently applied it is necessary to standardize the approach as much as possible. This review considers how QRAs have historically been used for the benefit of animal health, what problems have been encountered during their progression, and considers best practice for their future use. Four main elements were identified as having been the subject of some proposed standard methodology: (i) the description of risk levels, (ii) combining probabilities, (iii) accounting for trade volume and time period, and (iv) uncertainty. These elements were addressed in different ways but were highlighted as being fundamental to improving the robustness in estimating the risk and conveying the results to the risk manager with minimal ambiguity. In line with this, several tools have been developed which attempt to use mathematical reasoning to incorporate uncertainty and improve the objectivity of the qualitative framework. This represents an important advance in animal health QRA. Overall, animal health QRAs have established their usefulness by providing a tool for rapid risk estimation which can be used to identify important chains of events and critical control points along risk pathways and inform risk management programmes as to whether or not the risk exceeds a decision-making threshold above which action should be taken. Ensuring a robust objective methodology is used and that the reasons for differences in results, such as assumptions and uncertainty are clearly described to the customer with minimal ambiguity is essential to maintain confidence in the QRA process. However, further work needs to be done to determine if one objective uniform methodology should be developed and considered best practice. To this end, a set of best practice guidelines presenting the optimal way to conduct a QRA and regulated by bodies such as the World Organization for Animal Health or the European Food Safety Authority would be beneficial.

Spatial Modeling of Maritime Risk Using Machine Learning

Managing navigational safety is a key responsibility of coastal states. Predicting and measuring these risks has a high complexity due to their infrequent occurrence, multitude of causes, and large study areas. As a result, maritime risk models are generally limited in scale to small regions, generalized across diverse environments, or rely on the use of expert judgement. Therefore, such an approach has limited scalability and may incorrectly characterize the risk. Within this article a novel method for undertaking spatial modeling of maritime risk is proposed through machine learning. This enables navigational safety to be characterized while leveraging the significant volumes of relevant data available. The method comprises two key components: aggregation of historical accident data, vessel traffic, and other exploratory features into a spatial grid; and the implementation of several classification algorithms that predicts annual accident occurrence for various vessel types. This approach is applied to characterize the risk of collisions and groundings in the United Kingdom. The results vary between hazard types and vessel types but show remarkable capability at characterizing maritime risk, with accuracies and area under curve scores in excess of 90% in most implementations. Furthermore, the ensemble tree-based algorithms of XGBoost and Random Forest consistently outperformed other machine learning algorithms that were tested. The resultant potential risk maps provide decisionmakers with actionable intelligence in order to target risk mitigation measures in regions with the greatest requirement.

A Bayesian Framework for the Analysis and Optimal Mitigation of Cyber Threats to Cyber-Physical Systems

Critical infrastructures are increasingly reliant on information and communications technology (ICT) for more efficient operations, which, at the same time, exposes them to cyber threats. As the frequency and severity of cyberattacks are increasing, so are the costs of critical infrastructure security. Efficient allocation of resources is thus a crucial issue for cybersecurity. A common practice in managing cyber threats is to conduct a qualitative analysis of individual attack scenarios through risk matrices, prioritizing the scenarios according to their perceived urgency and addressing them in order until all the resources available for cybersecurity are spent. Apart from methodological caveats, this approach may lead to suboptimal resource allocations, given that potential synergies between different attack scenarios and among available security measures are not taken into consideration. To overcome this shortcoming, we propose a quantitative framework that features: (1) a more holistic picture of the cybersecurity landscape, represented as a Bayesian network (BN) that encompasses multiple attack scenarios and thus allows for a better appreciation of vulnerabilities; and (2) a multiobjective optimization model built on top of the said BN that explicitly represents multiple dimensions of the potential impacts of successful cyberattacks. Our framework adopts a broader perspective than the standard cost-benefit analysis and allows the formulation of more nuanced security objectives. We also propose a computationally efficient algorithm that identifies the set of Pareto-optimal portfolios of security measures that simultaneously minimize various types of expected cyberattack impacts, while satisfying budgetary and other constraints. We illustrate our framework with a case study of electric power grids.

Forty Years of Risk Analysis: A Scientometric Overview

Risk Analysis was first published in 1981, established with a vision to provide a platform for inquiry into fundamental risk-related concepts and theories, and to disseminate new knowledge about methods and approaches for identifying, analyzing, evaluating, managing, and communicating risk. The journal has also contributed significantly to a scientific understanding of specific risks related to human health and safety, engineering, ecological, and social systems. Published on behalf of the Society for Risk Analysis, the journal has become a leading platform over its 40-year history. Complementing recent celebratory overviews and perspectives on the evolution, achievements, and future challenges for Risk Analysis, this article presents a scientometric overview of the journal between 1981 and 2020. The study presents high-level insights in the journal publication trends and structure and trends in the leading countries/regions, institutions, and authors, in relation to their respective collaboration networks. Furthermore, the structure and evolution of research focus issues is analyzed, and highly cited publications are identified. The findings are primarily intended to provide high-level insights, which may be useful for early career academics and risk practitioners to understand the structure and development of the research domain, and its main contributors and topics, and for experienced researchers to reflect on the achievements and future developments.

Applying risk matrices for assessing the risk of psychosocial hazards at work

Although wide-ranging amendments in health and safety regulations at the European and national level oblige employers to conduct psychosocial risk assessment, it is still under debate how psychosocial hazards can be properly evaluated. For psychosocial hazards, an epidemiological, risk-oriented understanding similar to physical hazards is still missing, why most existing approaches for hazard evaluation insufficiently conceive psychosocial risk as a combination of the probability of a hazard and the severity of its consequences (harm), as found in traditional risk matrix approaches (RMA). We aim to contribute to a methodological advancement in psychosocial risk assessment by adapting the RMA from physical onto psychosocial hazards. First, we compare and rate already existing procedures of psychosocial risk evaluation regarding their ability to reliably assess and prioritize risk. Second, we construct a theoretical framework that allows the risk matrix for assessing psychosocial risk. This is done by developing different categories of harm based on psychological theories of healthy work design and classifying hazards through statistical procedures. Taking methodological and theoretical considerations into account, we propose a 3 × 3 risk matrix that scales probability and severity for psychosocial risk assessment. Odds ratios between hazards and harm can be used to statistically assess psychosocial risks. This allows for both risk evaluation and prioritizing to further conduct risk-mitigation. Our contribution advances the RMA as a framework that allows for assessing the relation between psychosocial hazards and harm disregarding which theory of work stress is applied or which tool is used for hazard identification. By this, we also contribute to further possible developments in empirical research regarding how to assess the risk of workplace stress. The risk matrix can help to understand how psychosocial hazards can be evaluated and organizations can use the approach as a guidance to establish a suitable method for psychosocial risk evaluation.

Disaster Risk Planning With Fuzzy Goal Programming

The uncertainty in the timing and severity of disaster events makes the long-term planning of mitigation and recovery actions both critical and extremely difficult. Planners often use expected values for hazard occurrences, leaving communities vulnerable to worse-than-usual and even so-called "black swan" events. This research models disasters in terms of their best-case, most-likely, and worst-case damage estimates. These values are then embedded in a fuzzy goal programming model to provide community planners and stakeholders with the ability to strategize for any range of events from best-case to worst-case by adjusting goal weights. Examples are given illustrating the modeling approach, and an analysis is provided to illustrate how planners might use the model as a planning tool.

Comparing quantitative probability of occurrence to a risk matrix approach: A study of chlorine residual data

Implementation of water safety planning methods globally has focused primarily on developing an evidence base to demonstrate the benefits of the WSP methodology for risk management in water systems. However, little work has been completed to understand the appropriateness of the risk matrix method currently used to capture levels of risk for system-specific hazardous events. This study examines two quantitative risk calculations (probability density functions and event trees) compared to the risk matrix method employed in water safety planning. This analysis was undertaken to understand if the risk matrix provides an accurate estimation of risk in a water system. Two data sets were collected from nine water supply systems, both continuous inline monitoring and grab samples collected in water distribution systems (discrete events) for chlorine residual data. Using quantitative risk calculations, our study found the risk matrix does not accurately estimate risk compared to water quality data from a water system. In thirty-four (77%) of the forty-four possible scenarios investigated, the risk matrix method provided an underestimation or overestimation compared to the probability calculated using water quality data. The probabilities calculated using continuous data and the event tree method provided the closest estimations to the risk matrix, indicating larger data sets with simpler methods may be more likely to match WSP results. The lack of accuracy obtained reveals the need for a re-evaluation of the risk matrix within a water safety plan (WSP), particularly for systems with data available to perform advanced risk analysis. The risk matrix method has been used historically for systems with little data; however, for water systems with advanced water quality monitoring, adding quantitative probability calculations to a water safety plan has the potential to increase accuracy of risk assessment in water safety planning.

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.

Benchmarking ISO Risk Management Systems to Assess Efficacy and Help Identify Hidden Organizational Risk

The overall aim of this article is to contribute to the further development of the area of benchmarking in risk management. The article introduces a two-step benchmarking model to assess the efficacy of ISO risk management systems. It furthermore aims at verifying its usefulness in terms of finding hidden risk issues and improvement opportunities. The existence of all key elements of an ISO 31000-based risk management system is examined at the beginning of this study. Then, the quality in terms of efficacy of important aspects of the risk management system is examined in more detail with special benchmarks. The application of the model to six ISO-certified organizations follows and reinforces the novelty of this study, which is to combine risk science knowledge with benchmarking theory in the application of ISO risk management standards in organizations. The results show that the benchmarking model developed in this study provides rigor when assessing and evaluating the efficacy of an ISO risk management system. By applying the model, risk issues and risk factors can be found that had not previously been identified. The findings are of importance for risk management, the benchmarking science, and for the development of ISO risk management standards.

Prioritization of hazards for risk and resilience management through elicitation of expert judgement

Risk assessment in communities or regions typically relies on the determination of hazard scenarios and an evaluation of their impact on local systems and structures. One of the challenges of risk assessment for infrastructure operators is how to identify the most critical scenarios that are likely to represent unacceptable risks to such assets in a given time frame. This study develops a novel approach for prioritizing hazards for the risk assessment of infrastructure. Central to the proposed methodology is an expert elicitation technique termed paired comparison which is based on a formal mathematical technique for quantifying the range and variance in the judgements of a group of stakeholders. The methodology is applied here to identify and rank natural and operational hazard scenarios that could cause serious disruption or have disastrous effects to the infrastructure in the transnational Øresund region over a period of 5 years. The application highlighted substantial divergences of views among the stakeholders on identifying a single 'most critical' natural or operational hazard scenario. Despite these differences, it was possible to flag up certain cases as critical among the natural hazard scenarios, and others among the operational hazards.

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.

The risk matrix approach: a helpful tool weighing probability and impact when deciding on preventive and diagnostic interventions

Background

Clinical guidelines are developed to lower risks, mostly viewed upon as probability. However, in daily practice, risk is perceived as the combination of probability and the impact of desired and adverse events. This combination of probability and impact can be visualized in a risk matrix. We evaluated the effect of interventions and diagnostic thresholds on modeled risk, by using the risk matrix approach (RMA) in a clinical guideline development process, and investigated which additional factors affected choices.

Methods

To improve care outcomes, we developed new guidelines in which care professionals had to decide upon novel interventions and diagnostic thresholds. A risk matrix showed the probability and impact of an intervention, together with the corresponding risk category. First, professionals’ opinion on required performance characteristics on risk were evaluated by a qualitative online survey. Second, qualitative assessment of possible additional factors affecting final decisions, that followed from group discussion and guideline development were evaluated.

Results

Upfront, professionals opinioned that non-invasive interventions should decrease the general population risk, whereas invasive interventions should decrease the risk in high-risk groups. Nonetheless, when making guidelines, interventions were introduced without reaching the predefined threshold of desired risk reduction. Professionals weighed other aspects besides risk reduction, as financial aspects and practical consequences for daily practice in this guideline-making process.

Conclusion

Professionals are willing to change policies at much lower level of anticipated effectiveness than defined upfront. Although objectively presented data structured group discussions, decisions in guideline development are affected by several other factors than risk reduction alone.

Are Firms Biasing Stakeholder Expectations by Attributing Prior Poor Performance to COVID-19?

Item 503(c) of the United States Securities and Exchange Commission’s (SEC’s) Regulation S-K requires firms to disclose the ‘most significant’ factors that affect them in their Item 1A risk factor disclosures made in their 10-K (annual) or 10-Q (quarterly) SEC filings. Prior to COVID-19, firms discussed risk factors such as liquidity, competition, etc. as part of their Item 1A disclosures. The current pandemic has resulted in the COVID-19 risk factor being widely discussed as part of firms’ Item 1A risk factor disclosures. A ‘firm-specific’ discussion on this transient risk factor is unique in the sense that it can affect the salience of other, already disclosed, less transient but significant risk factors to investors and other stakeholders. Using a sample of 68 firms hard hit by COVID-19 with prior poor performance, I find that market reactions to their Item 1A risk factor disclosures were significantly more positive for firms that disclosed the COVID-19 risk factor in a certain firm-specific manner compared to those that didn’t. These results suggest that stakeholder perceptions of firms’ risk profiles are being biased to some extent as the less transient but other significant risk factors that were already affecting these firms seem to be underweighted by them in evaluating the firms’ risk profiles. I explain this bias further using the meta-theoretical framework of the elaboration likelihood model. I also propose a solution to this problem that involves making these disclosures in the form of risk matrices.

JEL Classifications: G38, M10, M40, M41, M48

An Approach to Risk Assessment and Threat Prediction for Complex Object Security Based on a Predicative Self-Configuring Neural System

We identified a set of methods for solving risk assessment problems by forecasting an incident of complex object security based on incident monitoring. The solving problem approach includes the following steps: building and training a classification model using the C4.5 algorithm, a decision tree creation, risk assessment system development, and incident prediction. The last system is a predicative self-configuring neural system that includes a SCNN (self-configuring neural network), an RNN (recurrent neural network), and a predicative model that allows for determining the risk and forecasting the probability of an incident for an object. We proposed and developed: a mathematical model of a neural system; a SCNN architecture, where, for the first time, the fundamental problem of teaching a perceptron SCNN was solved without a teacher by adapting thresholds of activation functions of RNN neurons and a special learning algorithm; and a predicative model that includes a fuzzy output system with a membership function of current incidents of the considered object, which belongs to three fuzzy sets, namely “low risk”, “medium risk”, and “high risk”. For the first time, we gave the definition of the base class of an object’s prediction and SCNN, and the fundamental problem of teaching a perceptron SCNN was solved without a teacher. We propose an approach to neural system implementation for multiple incidents of complex object security. The results of experimental studies of the forecasting error at the level of 2.41% were obtained.

Plutonium Disposition: Using and Explaining Complex Risk-Related Methods

Applying risk assessment and management tools to plutonium disposition is a long-standing challenge for the U.S. government. The science is complicated, which has helped push risk assessment and management tools in new creative directions. Yet, communicating effectively about increasingly complicated risk-science issues like plutonium disposition requires careful planning and speakers who can address why specific tools are selected, the past record of applying these tools, why assumptions sometimes are applied instead of reliable data, and how uncertainty is characterized. Speakers addressing risk issues must also overcome obstacles in communication arising from expert-audience differences in knowledge and legal restrictions on disclosing information. This perspective seeks to highlight and illustrate five key risk questions, about probabilistic risk assessment (PRA) and performance assessment (PA) in the context of managing plutonium defense nuclear waste: objectives, experience, gaps, transparency, and difficulty of applying and communicating using each tool. While the general public needs to be involved, some issues require a level of expertise that is typically beyond local communities and therefore an expert panel should support community access.

Fusing strategic risk and futures methods to inform long-term strategic planning: case of water utilities

Risks and futures methods have complementary strengths as tools for managing strategic decisions under uncertainty. When combined, these tools increase organisational competency to evaluate and manage long-term risks, improving the flexibility and agility of the organisation to deal with gross uncertainties. Here, we set out a framework to guide the assessment of strategic risks for long-term business planning, based on its application at Portugal’s largest water utility, Empresa Portuguesa das Águas Livres. Our approach extends strategic risk assessment by incorporating scenario planning—a futures approach used to help the utility move beyond single point forecast of risks to focus on critical dimensions of uncertainty that are fundamental to the resilience of corporate objectives and their vulnerability to external pressures. We demonstrate how we combine two complementary approaches—risk and futures—and use them to assess (i) how a set of baseline strategic risks for a water utility evolves under alternative futures, (ii) the aggregate corporate-level risk exposure, and (iii) the process and responses needed to manage multiple, interdependent strategic risks. The framework offers a corporate approach to evolving strategic risks and improves a utility’s (i) knowledge of uncertainties, (ii) ability to assess the impacts of external developments over long time horizons and the consequences of actions and (iii) degree of flexibility to adapt to possible future challenges. The framework supports risk managers in their long-term strategic planning, through the appraisal and management of multiple, interdependent long-term strategic risks and can be replicated in other organisational contexts to bridge operational and corporate perspectives of enterprise risk.

Risk Management in the Ambulatory Care Process in a Mutual Benefit Association Covering Work-Related Accidents and Diseases: Applying Modified Failure Mode and Effect Analysis (FMEA) Methodology

AIM

To assess the impact of different forms of use of failure mode and effect analysis methodology for risk prioritization in the ambulatory care process in a mutual benefit association covering work-related accidents and diseases.

METHODS

The study is based on a previously drafted and individually prioritized risk map by a multidisciplinary team made up of patient safety committee members from health care centers and clinics in a mutual benefit association covering work-related accidents and diseases. The professionals mainly carry out their work in the field of management (individual manager group (IMG)). A group formed by clinicians subsequently completed 2 prioritizations: one based on the individual opinions of each of the members (individual clinical group (ICG)) and another in a consensual way (consensual clinical group (CCG)) as recommended by failure mode and effect analysis methodology. The risk prioritization was compared in the 3 groups (IMG, ICG, and CCG).

RESULTS

The risk prioritization by the IMG defines 7 extreme risks (risk prioritization ≥ 275). When the clinical group prioritizes them in an individual way (ICG), there is no extreme risk, whereas when it does so in a consensual way (CCG), there are 21 extreme risks. With respect to the coincidences of existing causes between the 3 groups, it is noted that the "risk of falls" is rated by both the clinical and the manager group but prioritized differently. On the other hand, the ICG and CCG coincide in that pressure on health care services can contribute to carrying out incomplete anamnesis. They also both consider that internal and external waiting lists and holiday periods can cause a delay in the starting of rehabilitation. The IMG and the CCG show similarity in the risk assessment of overprescribing medication and that multiple computer sessions are initiated. Finally, the IMG and the ICG coincide in the "lack of delivery of the medication leaflet".

CONCLUSIONS

The point of view of the clinicians is important in the risk prioritization of the ambulatory health care process. The difference in the risk prioritization between the clinical group at individual level and after consensus is remarkable.

A Failure Modes and Effects Analysis Framework for Assessing Geotechnical Risks of Tailings Dam Closure

Tailings dams remain on site following mine closures and must be designed and reclaimed to meet long-term goals, which may include walk-away closure or long-term care and maintenance. The underperformance of these structures can result in significant risks to public and environmental safety, as well as impacts on the future land use and economic activities near the structure. In Alberta, Canada, the expectation is for a tailings dam to be reclaimed and closed so that it can undergo deregistration. To aid in assessing the risks of underperformance during and after closure, a Generalized Failure Modes and Effects Analysis (G-FMEA) framework was developed to assess the long-term geotechnical risks for tailings dams in Alberta, with the goal of assessing the potential success of a tailings dam closure strategy. The G-FMEA is part of an initiative to enhance closure evaluations in Alberta in a collaborative effort between industry, the regulator, and academia. The G-FMEA incorporates the element of time to account for the evolution of the system, which should be applied at the planning stage and updated continually throughout the life of the facility. This paper presents the developed G-FMEA framework for tailings dams in Alberta, including the developed risk matrix framework.

Assessing the introduction risk of vector-borne animal diseases for the Netherlands using MINTRISK: A Model for INTegrated RISK assessment

To evaluate and compare the risk of emerging vector-borne diseases (VBDs), a Model for INTegrated RISK assessment, MINTRISK, was developed to assess the introduction risk of VBDs for new regions in an objective, transparent and repeatable manner. MINTRISK is a web-based calculation tool, that provides semi-quantitative risk scores that can be used for prioritization purposes. Input into MINTRISK is entered by answering questions regarding entry, transmission, establishment, spread, persistence and impact of a selected VBD. Answers can be chosen from qualitative answer categories with accompanying quantitative explanation to ensure consistent answering. The quantitative information is subsequently used as input for the model calculations to estimate the risk for each individual step in the model and for the summarizing output values (rate of introduction; epidemic size; overall risk). The risk assessor can indicate his uncertainty on each answer, and this is accounted for by Monte Carlo simulation. MINTRISK was used to assess the risk of four VBDs (African horse sickness, epizootic haemorrhagic disease, Rift Valley fever, and West Nile fever) for the Netherlands with the aim to prioritise these diseases for preparedness. Results indicated that the overall risk estimate was very high for all evaluated diseases but epizootic haemorrhagic disease. Uncertainty intervals were, however, wide limiting the options for ranking of the diseases. Risk profiles of the VBDs differed. Whereas all diseases were estimated to have a very high economic impact once introduced, the estimated introduction rates differed from low for Rift Valley fever and epizootic haemorrhagic disease to moderate for African horse sickness and very high for West Nile fever. Entry of infected mosquitoes on board of aircraft was deemed the most likely route of introduction for West Nile fever into the Netherlands, followed by entry of infected migratory birds.

Using Risk–Benefit Analysis to Control Salmonella in Chicken Meat

We have created a risk–benefit analysis (RBA) model to assist in food safety decision-making by analyzing Salmonella control in Brazilian chicken meat. First, we described the issues in a risk profile and used a 5×5 matrix to rank the risks associated with Salmonella. We then classified the magnitude of benefits and costs of control measures using another matrix. Finally, we verified the beneficial effects of recommended control measures using Quantitative Microbiological Risk Assessment (QMRA). The RBA classified Salmonella contamination as risk 6, indicating that control measures should be taken in the short and medium terms. It also recommended the adoption of biosecurity measures on farms to reduce the prevalence of Salmonella in birds, better control of carcass washings and chiller tank management, and information placement on packages and campaigns to raise the awareness of the population about the need to control Salmonella contamination before consumption. On the other hand, it did not recommend better controls at scalding and defeathering. QMRA confirmed the beneficial effects of the recommended control measures. For example, as Salmonella prevalence in poultry increased from 4.04 per cent to 50 per cent, the risk of infection per serving also increased from 0.0080 to 0.071. Although better controls in washings and chiller tank management did not affect the risk of infection, it reduced Salmonella counts on carcasses. We assume that the presence of Salmonella on carcasses was due to improper thermal processing or cross-contamination, which increased the risk from 0.0080 to 0.015962. The RBA demonstrated the logic involved in the adoption of control measures, and this can be helpful in the risk management of food safety issues.

Application of QMRA to prioritise water supplies for Cryptosporidium risk in New South Wales, Australia

A Quantitative Microbial Risk Assessment (QMRA) framework was applied to assess 312 drinking water supply systems across regional New South Wales (NSW). The framework was needed to support the implementation of a recommendation in the Australian Drinking Water Guidelines (ADWG) for appropriate treatment barriers to be operating in systems 'at risk' for Cryptosporidium. The objective was to prioritise systems so that those with the highest risk could be identified and addressed first. The framework was developed in a pilot study of 30 systems, selected to represent the range of water supplies across regional NSW. From these, source water categories were defined to represent local conditions with reference to the literature and Cryptosporidium risk factors. Values for Cryptosporidium oocyst concentration were assigned to the categories to allow quantification of the health risk from those water sources. The framework was then used to assess the risks in all 312 regional drinking water supply systems. Combining the disciplined approach of QMRA with simple catchment and treatment information and categorical risk outputs provided a useful and transparent method for prioritising systems for further investigation and potential risk management intervention. The risk rankings for drinking water supplies from this QMRA process have been used to set priorities for a large State Government funding program.

Risk Analysis in Healthcare Organizations: Methodological Framework and Critical Variables

Purpose

A risk assessment matrix is a widely used tool for analyzing, assessing and setting priorities in risk management in many fields. This paper overviews critical variables, advantages, disadvantages, strengths and weaknesses of this tool, according to the ISO 31000 risk management framework.

Results

Risk assessment is one of the key stages in the Risk Management Process and involves specific steps: identifying hazards, analyzing and evaluating all possible risks. Several methods are developed to assess risks in the literature. A risk matrix method, also called “decision matrix risk assessment (DMRA) technique”, is a systematic approach used to determine the risk level and to compare different risks and define which threats need to be controlled first. The actors involved in risk assessment are called on to manage different issues related to the choice of the most appropriate methodological approach, the assessment of the adequacy of the existing control measures, the articulation of risk consequence domains, the definition of the impact-consequences, the explanation of risk likelihood scales and the development of a risk matrix.

Conclusion

We highlighted a number of recommendations in order to address these issues, especially useful when healthcare organizations provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms on their use.

Risk Management of Bored Piling Construction on Sandy Soils with Real-Time Cost Control

In a global society, in which geotechnical projects are increasingly designed in a country other than the one where construction takes place, geotechnical risk management must be extended to cover infrastructure works, which are smaller than dams and tunnels, for example, since there is a significant impact on works budget imponderables. Therefore, a risk management methodology based on the likelihood of the occurrence of certain events and their economic consequences is proposed, which is applicable to bored piles (Kelly drilled) in coarse soils, easy to use, and simple to implement since the initial stage of construction. Of 12 case studies of construction works involving bored piles (Kelly drilled) carried out in Luanda (Angola), two selected examples involving the proposed risk methodology on sandy soil layers with interbedded clays are discussed. Subsequently, whether the overall foundation contract budget is affected by assessed risk is determined, and what influence it has on the budget in the light of mitigating factors and associated real costs. This method intended to encourage the adaptation of sustainable risk management in bored piles construction by the site project managers, involving risk analysis concurrently with budgetary review. Though the level of assessed technical risk may be acceptable, overall costs associated with the contract in question may not be acceptable.

Prioritizing facilities linked to corporate strategic objectives using a fuzzy model

Purpose

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

Design/methodology/approach

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Findings

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

Originality/value

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

Risk and Safety Management in Physical Education: A Study of Teachers' Practice Perspectives

The aim of this article is to explore and understand teachers' risk and safety management (RSM) practices in physical education (PE) programs in Norway. A survey questionnaire and semistructured interviews were therefore used to generate quantitative data on trends from a larger sample of teachers (n = 698) and rich in-depth qualitative data concerning teachers' (n = 17) practices. By providing the teachers' perspectives, a better understanding of the complexity of RSM in PE may be possible. The results from both the survey and interviews suggest that teachers employ multiple strategies: from safety procedures, complying to compulsory risk measures, to the use of common sense in their RSM practices. The interviewees, on the other hand, initially claim that their RSM practice is quite scarce and, in some respects, not appropriate for PE. They emphasize measures that cater to the students' needs and modification to physical activities in their teaching. However, the interview data suggest that teachers do not primarily conceptualize this part of their practice as RSM but as measures of other pedagogical concerns. Combined, the results from both the survey and the interviews may characterize a RSM practice that relies on teaching experience and the use of discretion. The results in this article both converge and diverge and emphasize the importance of multiple data sources in investigating teachers' RSM practices.

The Pebble Remains in the Master's Hand: Two Careers Spent Learning (Still) from John Evans

In this article, we discuss four vexing problems in risk-based decision making that John Evans has addressed over the last nearly 40 years and has perennially challenged the two of us and others to think about. We tackle the role in decision making of potential thresholds in dose-response functions, how the lack of health reference values for many chemicals may distort risk management, the challenge of model uncertainty for risk characterization, and the yet-untapped potential for value-of-information analysis to enhance public health decision making. Our theme is that work remains to be done on each of these, but that some of that work would merely involve listening to ideas that John has already offered.

How Perceptions of Trust, Risk, Tap Water Quality, and Salience Characterize Drinking Water Choices

Provision of safe drinking water by water utilities is challenged by disturbances to water quality that have become increasingly frequent due to global changes and anthropogenic impacts. Many water utilities are turning to adaptable and flexible strategies to allow for resilient management of drinking water supplies. The success of resilience-based management depends on, and is enabled by, positive relationships with the public. To understand how relationships between managers and communities spill over to in-home drinking water behavior, we examined the role of trust, risk perceptions, salience of drinking water, and water quality evaluations in the choice of in-home drinking water sources for a population in Roanoke Virginia. Using survey data, our study characterized patterns of in-home drinking water behavior and explored related perceptions to determine if residents’ perceptions of their water and the municipal water utility could be intuited from this behavior. We characterized drinking water behavior using a hierarchical cluster analysis and highlighted the importance of studying a range of drinking water patterns. Through analyses of variance, we found that people who drink more tap water have higher trust in their water managers, evaluate water quality more favorably, have lower risk perceptions, and pay less attention to changes in their tap water. Utility managers may gauge information about aspects of their relationships with communities by examining drinking water behavior, which can be used to inform their future interactions with the public, with the goal of increasing resilience and adaptability to external water supply threats.

Using a participatory qualitative risk assessment to estimate the risk of introduction and spread of transboundary animal diseases in scarce-data environments: A Spatial Qualitative Risk Analysis applied to foot-and-mouth disease in Tunisia 2014-2019

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Rasines D. An Adversarial Risk Analysis Framework for Cybersecurity

Risk analysis is an essential methodology for cybersecurity as it allows organizations to deal with cyber threats potentially affecting them, prioritize the defense of their assets, and decide what security controls should be implemented. Many risk analysis methods are present in cybersecurity models, compliance frameworks, and international standards. However, most of them employ risk matrices, which suffer shortcomings that may lead to suboptimal resource allocations. We propose a comprehensive framework for cybersecurity risk analysis, covering the presence of both intentional and nonintentional threats and the use of insurance as part of the security portfolio. A simplified case study illustrates the proposed framework, serving as template for more complex problems.