Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.

A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

Everyday we face decisions that carry an element of risk and uncertainty. The ability to analyse, communicate and control the level of risk entailed by these decisions remains one of the most pressing challenges to the analyst, scientist and manager. This book presents the foundational issues in risk analysis ? expressing risk, understanding what risk means, building risk models, addressing uncertainty, and applying probability models to real problems. The principal aim of the book is to give the reader the knowledge and basic thinking they require to approach risk and uncertainty to support decision making. Presents a statistical framework for dealing with risk and uncertainty. Includes detailed coverage of building and applying risk models and methods. Offers new perspectives on risk, risk assessment and the use of parametric probability models. Highlights a number of applications from business and industry. Adopts a conceptual approach based on elementary probability calculus and statistical theory. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.

Risk Analysis: Foundations, Models, and Methods fully addresses the questions of "What is health risk analysis?" and "How can its potentialities be developed to be most valuable to public health decision-makers and other health risk managers?" Risk analysis provides methods and principles for answering these questions. It is divided into methods for assessing, communicating, and managing health risks. Risk assessment quantitatively estimates the health risks to individuals and to groups from hazardous exposures and from the decisions or activities that create them. It applies specialized models and methods to quantify likely exposures and their resulting health risks. Its goal is to produce information to improve decisions. It does this by relating alternative decisions to their probable consequences and by identifying those decisions that make preferred outcomes more likely. Health risk assessment draws on explicit engineering, biomathematical, and statistical consequence models to describe or simulate the causal relations between actions and their probable effects on health. Risk communication characterizes and presents information about health risks and uncertainties to decision-makers and stakeholders. Risk management applies principles for choosing among alternative decision alternatives or actions that affect exposure, health risks, or their consequences.

This book provides a comprehensive demonstration of risk analysis as a distinct science covering risk understanding, assessment, perception, communication, management, governance and policy. It presents and discusses the key pillars of this science, and provides guidance on how to conduct high-quality risk analysis. The Science of Risk Analysis seeks to strengthen risk analysis as a field and science by summarizing and extending current work on the topic. It presents the foundation for a distinct risk field and science based on recent research, and explains the difference between applied risk analysis (to provide risk knowledge and tackle risk problems in relation to for example medicine, engineering, business or climate change) and generic risk analysis (on concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterise, communicate, manage and govern risk). The book clarifies and describes key risk science concepts, and builds on recent foundational work conducted by the Society for Risk Analysis in order to provide new perspectives on science and risk analysis. The topics covered are accompanied by cases and examples relating to current issues throughout. This book is essential reading for risk analysis professionals, scientists, students and practitioners, and will also be of interest to scientists and practitioners from other fields who apply risk analysis in their work.

Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p

Risk science is becoming increasingly important as businesses, policymakers and public sector leaders are tasked with decision-making and investment using varying levels of knowledge and information. Risk Science: An Introduction explores the theory and practice of risk science, providing concepts and tools for understanding and acting under conditions of uncertainty. The chapters in this work cover the fundamental concepts, principles, approaches, methods and models for how to understand, assess, communicate, manage and govern risk. These topics are presented and examined in a way which details how they relate, for example, how to characterize and communicate risk with particular emphasis on reflecting uncertainties; how to distinguish risk perception and professional risk judgments; how to assess risk and guide decision-makers, especially for cases involving large uncertainties and value differences; and how to integrate risk assessment with resilience-based strategies. The text provides a variety of examples and case studies that relate to highly visible and relevant issues facing risk academics, practitioners and non-risk leaders who must make risk-related decisions. Presenting both the foundational and most recent advancements in the subject matter, this work particularly suits students of risk science courses at college and university level. The book also provides broader key reading for students and scholars in other domains, including business, engineering and public health.

This book is the seventh in a series of titles from the National Research Council that addresses the effects of exposure to low dose LET (Linear Energy Transfer) ionizing radiation and human health. Updating information previously presented in the 1990 publication, Health Effects of Exposure to Low Levels of Ionizing Radiation: BEIR V, this book draws upon new data in both epidemiologic and experimental research. Ionizing radiation arises from both natural and man-made sources and at very high doses can produce damaging effects in human tissue that can be evident within days after exposure. However, it is the low-dose exposures that are the focus of this book. So-called “late” effects, such as cancer, are produced many years after the initial exposure. This book is among the first of its kind to include detailed risk estimates for cancer incidence in addition to cancer mortality. BEIR VII offers a full review of the available biological, biophysical, and epidemiological literature since the last BEIR report on the subject and develops the most up-to-date and comprehensive risk estimates for cancer and other health effects from exposure to low-level ionizing radiation.

Improving Risk Analysis shows how to better assess and manage uncertain risks when the consequences of alternative actions are in doubt. The constructive methods of causal analysis and risk modeling presented in this monograph will enable to better understand uncertain risks and decide how to manage them. The book is divided into three parts. Parts 1 shows how high-quality risk analysis can improve the clarity and effectiveness of individual, community, and enterprise decisions when the consequences of different choices are uncertain. Part 2 discusses social decisions. Part 3 illustrates these methods and models, showing how to apply them to health effects of particulate air pollution. "Tony Cox’s new book addresses what risk analysts and policy makers most need to know: How to find out what causes what, and how to quantify the practical differences that changes in risk management practices would make. The constructive methods in Improving Risk Analysis will be invaluable in helping practitioners to deliver more useful insights to inform high-stakes decisions and policy,in areas ranging from disaster planning to counter-terrorism investments to enterprise risk management to air pollution abatement policies. Better risk management is possible and practicable; Improving Risk Analysis explains how." Elisabeth Pate-Cornell, Stanford University "Improving Risk Analysis offers crucial advice for moving policy-relevant risk analyses towards more defensible, causally-based methods. Tony Cox draws on his extensive experience to offer sound advice and insights that will be invaluable to both policy makers and analysts in strengthening the foundations for important risk analyses. This much-needed book should be required reading for policy makers and policy analysts confronting uncertain risks and seeking more trustworthy risk analyses." Seth Guikema, Johns Hopkins University "Tony Cox has been a trail blazer in quantitative risk analysis, and his new book gives readers the knowledge and tools needed to cut through the complexity and advocacy inherent in risk analysis. Cox’s careful exposition is detailed and thorough, yet accessible to non-technical readers interested in understanding uncertain risks and the outcomes associated with different mitigation actions. Improving Risk Analysis should be required reading for public officials responsible for making policy decisions about how best to protect public health and safety in an uncertain world." Susan E. Dudley, George Washington University