This book is motivated by the following convictions:
1) Quantitative risk assessment (QRA) can be a powerful discipline for improving
risk management decisions and policies.
2) Poorly conducted QRAs can produce results and recommendations that are
worse than useless.
3) Sound risk assessment methods provide the benefits of QRA modeling – being
able to predict and compare the probable consequences of alternative actions,
interventions, or policies and being able to identify those that make preferred
consequences more probable – while avoiding the pitfalls.
This book develops and illustrates QRA methods for complex and uncertain bio-
logical, engineering, and social systems. These systems have behaviors that are too
complex or uncertain to be modeled accurately in detail with high confidence. Prac-
tical applications include assessing and managing risks from chemical carcinogens,
antibiotic resistance, mad cow disease, terrorist attacks, and accidental or deliberate
failures in telecommunications network infrastructure.
For Whom Is It Meant?
This book is intended primarily for practitioners who want to use rational quanti-
tative risk analysis to support and improve risk management decisions in important
health, safety, environmental, reliability, and security applications, but who have
been frustrated in trying to apply traditional quantitative modeling methods by the
high uncertainty and/or complexity of the systems involved. We emphasize methods
and strategies for modeling causal relations in complex and uncertain systems well
enough to make effective risk management decisions. The book is written for practi-
tioners from multiple disciplines – decision and risk analysts, operations researchers
and management scientists, quantitative policy analysts, economists, health and
safety risk assessors, engineers, and modelers – who need practical ways to predict
and manage risks in complex and uncertain systems.