Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

A generic causality-informed neural network (CINN) methodology for quantitative risk analytics and decision support

In this paper, we develop a generic framework for systemically encoding causal knowledge manifested in the form of hierarchical causality structure and qualitative (or quantitative) causal relationships into neural networks to facilitate sound risk analytics and decision support via causally-aware intervention reasoning. The proposed methodology for establishing causality-informed neural network (CINN) follows a four-step procedure. In the first step, we explicate how causal knowledge in the form of directed acyclic graph (DAG) can be discovered from observation data or elicited from domain experts. Next, we categorize nodes in the constructed DAG representing causal relationships among observed variables into several groups (e.g., root nodes, intermediate nodes, and leaf nodes), and align the architecture of CINN with causal relationships specified in the DAG while preserving the orientation of each existing causal relationship. In addition to a dedicated architecture design, CINN also gets embodied in the design of loss function, where both intermediate and leaf nodes are treated as target outputs to be predicted by CINN. In the third step, we propose to incorporate domain knowledge on stable causal relationships into CINN, and the injected constraints on causal relationships act as guardrails to prevent unexpected behaviors of CINN. Finally, the trained CINN is exploited to perform intervention reasoning with emphasis on estimating the effect that policies and actions can have on the system behavior, thus facilitating risk-informed decision making through comprehensive "what-if" analysis. Two case studies are used to demonstrate the substantial benefits enabled by CINN in risk analytics and decision support.

Foodborne disease outbreaks in flour and flour-based food products from microbial pathogens in the United States, and their health economic burden

The most comprehensive and inclusive estimates for the economic burden of foodborne illness yield values as high as $97.4 billion USD annually. However, broad incidence and cost estimates have limited use if they cannot be attributed to specific foods, for the purposes of food safety control. In this study, we estimated the economic burden of foodborne illnesses resulting from flour and flour-based food products in the United States from the years 2001 to 2021. The outbreak, illness burden, and health economic data are combined to generate these estimates. Our model combined outbreak data with published Centers for Disease Control and Prevention multipliers to estimate the annual number of illnesses associated with flour-borne pathogens. We then integrated illness severity data with an updated economic model that accounts for costs related to medical care, productivity loss, loss of life, along with the quality of life loss that entails pain and suffering. In total, 752 cases and 223 hospitalizations from flour-related illnesses were reported from 2001 to 2021, with an average of 37.6 cases of reported cases annually. However, the actual number of cases, accounting for underreporting and underdiagnosis, can be as high as 19,440 annually. Pathogens involved in these outbreaks are Salmonella, E. coli O157:H7, and E. coli O121. Our estimates suggest average annual economic losses, including healthy years of life lost, of $108 and $258 million using two alternative models.

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.

Chemophobia and passion: why chemists should desire Marcel Proust

In this article, we introduce a new communication strategy called the "communication success dimension" for the suppression and eradication of chemophobia. We explain, using recent examples, that chemophobia presents a danger not only to the science of chemistry but also to humankind. Based on the latest insights from communication research, we emphasize the need to bring more passion, dedication, and human factors into the communication of chemistry. We demonstrate the application of this new strategy by employing Marcel Proust's In Search of Lost Time to combat chemophobia.

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The Social Amplification of Risk Framework: A Normative Perspective on Trust?

Public trust is being lamented as the central victim of our new, digital information environment, a notion that is depicted in labeling our society as "posttruth" or "posttrust." Within this article, we aim to call this deficit view of public trust into question and kindle a more positive outlook in future research. For this, we utilize the Social Amplification of Risk Framework to discuss trust as an inherent aspect of social interactions and to question the frameworks' normative approach to public trust and risk perception. Utilizing a literature review of prior studies that investigated trust within the structure of SARF and a case study on the impacts of Fukushima on public trust in nuclear energy, we would like to argue that the current normative "trust deficit model" should be overcome and future risk research should increasingly focus on the opportunities of the digital informational environment for risk communication.

Deterrence against Terrorist Attacks in Sports-Mega Events: A Method to Identify the Optimal Portfolio of Defensive Countermeasures

Sports mega-events, such as the Olympic Games or the Super Bowl, are attractive targets for terrorist organizations, due to their visibility, size, and number of people involved. Two characteristics of sports mega-events, however, make them distinctive in comparison with other well-studied target protection problems in counterterrorism analysis (such as transportation hubs or infrastructure facilities). First, defensive measures are often publicly known. Second, their finite horizon means that deterrence against any attack must be prioritized. In this article we thus propose a method that identifies the best portfolio of defensive measures the defense may adopt, given a fixed budget, to minimize the chances of suffering a terrorist attack during a sports mega-event. The method makes some relevant contributions to adversarial risk analysis: (i) it represents attackers that can choose among multiple attack scenarios and the no-attack scenario; (ii) it measures the deterrence effect caused by synergic portfolios of defensive measures; and (iii) it proposes an algorithm that identifies dominated portfolios and may, thus, overcome the scalability problems inherent to this portfolio optimization. We apply this method to a real-world defense problem, revisiting the defensive countermeasure planning for the 2016 Brazilian Olympic Games in Rio de Janeiro, Brazil. In the case study, we find a nonlinear relationship between budget expenditure and deterrence, as well as a decreasing marginal effectiveness use of resources after a given budget threshold, which would support a more efficient allocation of investments in the Games defense.

The Evolving Field of Risk Communication

The 40th Anniversary of the Society for Risk Analysis presents an apt time to step back and review the field of risk communication. In this review, we first evaluate recent debates over the field's current state and future directions. Our takeaway is that efforts to settle on a single, generic version of what constitutes risk communication will be less productive than an open-minded exploration of the multiple forms that comprise today's vibrant interdisciplinary field. We then review a selection of prominent cognitive, cultural, and social risk communication scholarship appearing in the published literature since 2010. Studies on trust in risk communication messengers continued to figure prominently, while new research directions emerged on the opportunities and critical challenges of enhancing transparency and using social media. Research on message attributes explored how conceptual insights particularly relating to framing, affective and emotional responses, and uncertainty might be operationalized to improve message effectiveness. Studies consistently demonstrated the importance of evaluation and how varying single attributes alone is unlikely to achieve desired results. Research on risk communication audiences advanced on risk perception and multiway engagement with notable interest in personal factors such as gender, race, age, and political orientation. We conclude by arguing that the field's interdisciplinary tradition should be further nurtured to drive the next evolutionary phase of risk communication research.