The Science of Resilience: Complexity, Risk Modeling and Systems, Wiley, 2025
Ted G. Lewis
ISBN: 978-1-394-35493-1

This book offers strategies for improving resilience, incorporating complexity theory, risk analysis and systems thinking with rigorous mathematical treatment.

The Science of Resilience is a compilation of more than 20 years of study of system collapses and catastrophes – a journey that began in 2002 when author Ted G. Lewis co-founded the Center For Homeland Defence and Security at the Naval Postgraduate School in California, and continued after his retirement in 2013.

Lewis is a computer scientist with expertise in applied complexity theory, homeland security, infrastructure systems, and early-stage start-up strategies. He has served in government, industry and academia over an extensive career.

“It has been a slowly evolving investigation of a theory and practice based on a rigorous understanding of system faults, fault propagation and collapse,” Lewis writes. “Why do some systems under stress fail while others do not?” His motivating factor was a belief that a large number of catastrophic events are built into the system; that is, the system itself is partially responsible for the disaster – a radical idea that Lewis says is slowly being accepted by practitioners and academics. “It is not an easy idea to accept because if the system is partly responsible for its own collapse, then it can be improved. Moreover, new systems can be constructed that are more resilient. More resilience implies less risk and fewer casualties.”

In seeking to find out how, Lewis focuses on three ideas that recur throughout the book: self‐organisation inherent in all systems; phase transition or the culmination of stress that reaches a critical tipping point beyond which consequences increase exponentially; and the realisation that structure matters – connectivity and the topology of a system that largely determines its response to stress.

This is a book that approaches resilience as a systems problem, examined through models, analogies and worked examples drawn from physics, ecology, engineering, finance and cyber security. The opening chapter sets the tone with the sandpile metaphor, using self-organised criticality to explain how minor shocks can trigger disproportionate losses. From there, the author moves into formal tools such as exceedance probability, fault trees and network theory.

Case material anchors his theories. The California Wildfires illustrate phase change and percolation, the Covid-19 pandemic is framed as a biological avalanche, while the 2008 financial crisis illustrates what happens when systems become too connected to fail.

Throughout the book, Lewis returns to recurring mechanisms: clustering, bottlenecks, spectral radius, competitive exclusion and the Braess paradox. Each chapter adds another layer, showing how optimisation can erode slack, how redundancy reshapes kill chains, and how blocking critical nodes can dampen cascades.

By using mathematical models and real-world examples, the book provides practical tools and strategies for designing resilient systems that can adapt and thrive in the face of uncertainty.

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