Risk Analysis of Complex and Uncertain Systems

• 1 INTRODUCTION TO RISK ANALYSIS.- Quantitative Risk Assessment Goals and Challenges.- to Engineering Risk Analysis.- to Health Risk Analysis.- 2 AVOIDING BAD RISK ANALYSIS.- Limitations of Risk Assessment Using Risk Matrices.- Limitations of Quantitative Risk Assessment Using Aggregate Exposure and Risk Models.- 3 PRINCIPLES FOR DOING BETTER.- Identifying Nonlinear Causal Relations in Large Data Sets.- Overcoming Preconceptions and Confirmation Biases Using Data Mining.- Estimating the Fraction of Disease Caused by One Component of a Complex Mixture: Bounds for Lung Cancer.- Bounding Resistance Risks for Penicillin.- Confronting Uncertain Causal Mechanisms – Portfolios of Possibilities.- Determining What Can Be Predicted: Identifiability.- 4 APPLICATIONS AND EXTENSIONS.- Predicting the Effects of Changes: Could Removing Arsenic from Tobacco Smoke Significantly Reduce Smoker Risks of Lung Cancer?.- Simplifying Complex Dynamic Networks: A Model of Protease Imbalance and COPD Dynamic Dose-Response.- Value of Information (VOI) in Risk Management Policies for Tracking and Testing Imported Cattle for BSE.- Improving Antiterrorism Risk Analysis.- Designing Resilient Telecommunications Networks.

From the reviews: "The new results of this book include many real life applications especially in health management. ... More applications to the specialists are given throughout the book. The book is written for practitioners but I think it is quite useful for anyone interested in risk analysis and assessment. ... Concluding, this is one of the best books on quantitative risk assessment. I strongly recommended it to anyone interested in reducing risk in this highly volatile world." (E. Ahmed, Zentralblatt MATH, Vol. 1168, 2009) "The book is devoted to the development of quantitative risk assessment (QRA) for complex and uncertain biological, engineering, and social systems. ... This book is written for practitioners using rational quantitative risk analysis in various areas. The methods and strategies included are good enough to help one make effective risk management decisions." (Krzysztof Szajowski, Mathematical Reviews, Issue 2012 c)