Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats

Aven, Terje; Zio, Enrico

doi:10.1016/j.ress.2020.107270

Cited by 49 publications

(27 citation statements)

References 31 publications

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“…Such an ethics could consider the seven principles of ethics for disasters proposed by the philosopher Naomi Zack [18]: general moral obligations to plan for and respond to disaster; adequacy (i.e., proportionality to benefit and inverse proportionality to risk) and fairness, with the rule of Fairly Save All Who Can Be Saved with the Best Preparation; individual responsibility; social contract obligations, i.e., governments are obligated to assist individuals in disaster-preparation and -response planning and implementation; safety and security, with a clear distinction regarding the treatment of public safety and public security; dignity, i.e., the human dignity of all disaster victims should be preserved as a primary oral value; and needs, i.e., the needs of all victims must be addressed. The ethics of resilience could also account for Jonas's collective imperative of responsibility for the distant future [9], as well as the englobing view of the interdependences between the various dynamics of a disaster, the various sources and natures of risk, and the spatial worldwide distribution of causes and effects [19,20]. Clearly, an enormous amount of work is waiting for the discipline of Disaster Risk Reduction.…”

Section: Discussionmentioning

confidence: 99%

Risk Perception Biases and the Resilience of Ethics for Complying with COVID-19-Pandemic-Related Safety Measures

Rajaonah¹,

Zio²

2021

JRACR

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After 1 year and a half of the COVID-19 pandemic, almost four million deaths, 1 and considerable socioeconomic damage worldwide, we extend a prior short communication 2 to more thoroughly explore the relationships between risk judgment and the decisionmaking that risk judgment informs. Our goal is to raise the debate about risk communication, starting from the influences on risk perceptions and risk decisions of cognitive, affective and social factors -with an emphasis on mental models and trust -and ending with the concept of the ethics of resilience. INFLUENCES OF RISK JUDGMENTS AND RISK DECISIONSWe choose the work of Breakwell [1] to summarize the determinants of risk judgments and decisions regarding individual protective behavior (i.e., mask wearing, physical distance keeping, contact tracing app usage, vaccination, movement restriction, and lockdown acceptance) (Table 1). Note that even though these influences are categorized here in terms of cognitive, personality, affective, and social factors for their readability, they interact with each other and provide different levels of explanation from the individual level to the institutional level.In brief, risk judgments, and correlatively, risk decisions, are influenced by (i) heuristics; (ii) affective factors (e.g., feelings of confidence); (iii) mental models of risk including knowledge (e.g., virus transmissibility) and beliefs (e.g., self-efficacy), social and cultural norms (e.g., attitude toward mask wearing) and moral values (e.g., altruism); and (iv) trust as an engagement in action (e.g., intention to get vaccinated).We decided to focus on mental models of risk and trust because the goal of risk communication is to (i) fill the gaps in the mental model with regard to risk understanding, reinforce correct beliefs, and correct misconceptions [2] and (ii) correct noncalibrated trust. However, let us begin with their common thread, the resilience of ethics. RESILIENT ETHICS AND RISK COMMUNICATIONResilience is defined by the United Nations Office for Disaster Risk Reduction as the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform and recover from the effects of a hazard in a timely and efficient manner […]. Resilience relies not only on groups and communities but also on their members as individual responsible moral entities who are distinct from each other but influence each other within a given group or community. The challenge of COVID-19-related risk communication is not only to change individuals' attitudes until the pandemic is mastered but also to make people aware that there

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Section: Discussionmentioning

confidence: 99%

Risk Perception Biases and the Resilience of Ethics for Complying with COVID-19-Pandemic-Related Safety Measures

Rajaonah¹,

Zio²

2021

JRACR

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“…The occurrence of inherent uncertainties in risk assessment and decision-making is well known in the general fields of risk science and resilience, e.g., in Flage et al (2014) and Aven and Zio (2021). In this context, especially the role of these uncertainties is discussed when considering decision-making for risk-reducing measures (Aven and Zio 2011;Yoe 2019).…”

Section: Introductionmentioning

confidence: 99%

Representing Uncertainty in Physical Security Risk Assessment

et al. 2021

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The importance of (physical) security is increasingly acknowledged by society and the scientific community. In light of increasing terrorist threat levels, numerous security assessments of critical infrastructures are conducted in practice and researchers propose new approaches continuously. While practical security risk assessments (SRA) use mostly qualitative methods, most of the lately proposed approaches are based on quantitative metrics. Due to little evidence of actual attacks, both qualitative and quantitative approaches suffer from the fundamental problem of inherent uncertainties regarding threats and capabilities of security measures as a result from vague data or the usage of expert knowledge. In quantitative analysis, such uncertainties may be represented by, e.g., probability distributions to reflect the knowledge on security measure performance available. This paper focuses on the impact of these uncertainties in security assessment and their consideration in system design. We show this influence by comparing the results of a scalar evaluation that does not take into account uncertainties and another evaluation based on distributed input values. In addition, we show that the influence is concentrated on certain barriers of the security system. Specifically, we discuss the robustness of the system by conducting quantitative vulnerability assessment as part of the SRA process of an airport structure example. Based on these results, we propose the concept of a security margin. This concept accounts for the uncertain knowledge of the input parameters in the design of the security system and minimizes the influence of these uncertainties on the actual system performance. We show how this approach can be used for vulnerability assessment by applying it to the initially assessed configuration of the airport structure. The results of this case study support our assumptions that the security margin can help in targeted uncertainty consideration leading to reduced system vulnerability.

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“…All of these factors in any part of the healthcare system must be taken into account and considered under the analysis of the conception of healthcare safety [5]. The coronavirus pandemic has exacerbated many problems regarding health and safety [10,11]. Timely analysis and evaluation of healthcare safety can help avoid complications for patients [12].…”

Section: Introductionmentioning

confidence: 99%

“…These two specifics (complexity of the investigated system and uncertainty of the initial data) are the principal factors that cause the development of new methods for reliability analysis in healthcare safety. The studies of healthcare safety in time of the coronavirus pandemic are restricted by uncertainties and weak knowledge even more [10,11,24]. Therefore, the methods for reliability analysis that allow analysis and evaluation based on uncertain data should be considered as the first.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we propose a new method for the structure function construction for the mathematical representation of a system based on incompletely specified and uncertain data, which can be used for different types of systems in healthcare. For example, uncertainty and incompleteness are typical for data related to coronavirus disease problems [10,11,37,38]. The important aspect of the proposed method is interpretation of the structure function as classifier, which divides all possible system states into several predefined classes (for example, fault states and working states) [25,33].…”

Section: Introductionmentioning

confidence: 99%

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Reliability Evaluation of the Factors That Influenced COVID-19 Patients’ Condition

2021

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Health and safety is a problem that is intensively discussed nowadays. The failures in healthcare are called medical errors: if the patient’s condition worsens or he/she contracts an illness, then the actions that led to this are interpreted as medical errors. Medical errors can be the result of new procedures, extremes of age, complex or urgent care, improper documentation, illegible hand-writing, or patient actions. One of the ways to reduce medical error is an evaluation of its possibility, and then using the result of this evaluation to improve the medical organization units and processes in patient diagnosis, treatment, and care. This evaluation is possible based on methods of reliability engineering. The reliability engineering methods allow evaluating of different systems’ reliability and the influence of external and internal factors on system reliability. These methods’ application needs the system to be investigated or objective interpretation in terms of reliability engineering. Therefore, such a system in healthcare, for the diagnosis of disease, a patient’s treatment, the influence of different factors on a patient’s condition, and others, should be presented according to the rules and demands of reliability engineering. The first step is development of the mathematical representation of the investigated system or object according to the demands of the reliability analysis. One of the often-used mathematical representations in the reliability analysis of a system is the structure function. However, this mathematical representation needs completely specified initial data. The initial data from the healthcare domain for medical error analysis is uncertain and incompletely specified. Therefore, the development of this mathematical representation needs special methods. In this paper, a new method for the mathematical representation of system development based on uncertain and incompletely specified data is proposed. The system evaluation based on the structure function allows computing of many reliability indices and measures used in reliability engineering. The approbation of this method is considered based on an example of COVID-19 patients.

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Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats

Cited by 49 publications

References 31 publications

Risk Perception Biases and the Resilience of Ethics for Complying with COVID-19-Pandemic-Related Safety Measures

Risk Perception Biases and the Resilience of Ethics for Complying with COVID-19-Pandemic-Related Safety Measures

Representing Uncertainty in Physical Security Risk Assessment

Reliability Evaluation of the Factors That Influenced COVID-19 Patients’ Condition

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