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Praise for Learning from Catastrophes

‘‘What an extraordinary range of experiences and what an experienced array ofauthors! This book is actually exciting to read, whether or not you are professionallyconcerned with anticipating or coping with catastrophes or their aftermath. But ifthose are your concerns, this book will not only inform you but stimulate your ownthinking.’’

—Thomas Schelling, Emeritus Distinguished University Professorat the School of Public Policy of the University of Maryland,and recipient of the 2005 Nobel Prize in Economic Science

‘‘Learning from Catastrophes brings together the expertise of two distinguishedacademics, Howard Kunreuther and Michael Useem, and other prominent thoughtleaders to shed light on a provocative topic of our times—risk. Kunreuther is a leading expert on the economic impact of large scale catastrophes and brings a well-honed perspective to the risk sciences. Useem is a driving force in studying leadership attributes, incorporating leadership studies into business curriculum andapplying them in business. Together, the two professors of The Wharton School, University of Pennsylvania have presented a thoughtful analysis of extreme eventsand recommendations for mitigating their impacts. Spawned by discussions at the2009 World Economic Forum, this book is a must read for those whose careers touchon the prediction of and response to catastrophes.’’

—Jay Fishman, Chairman and Chief Executive Officer, The Travelers Companies, Inc.

‘‘The first decade of this century has seen natural disasters, acts of mass violence, anda severe financial crisis; but also increasing global integration and growing prosperityin many areas. Learning from Catastrophes is a most timely look at how we can usethe latter to be better prepared for the former. The richness of ideas in this bookreflects the diversity and expertise of the contributors. There is, however, a singlethread that runs through it—that the answer lies in communication and collaborationand that we have a shared global responsibility to harness technology, intellectualresources, and financial capital to prevent recurrence of these events and mitigatetheir impact.’’

—K. V. Kamath, Chairman, ICICI Bank, and former President, Confederation of Indian Industry

‘‘In this volume, Howard Kunreuther and Michael Useem have gathered together acast of brilliant thinkers to impart lifesaving knowledge for successfully navigatingthe hazards of the twenty-first century. This deeply optimistic book not only equipsthe reader with the intellectual tools for confronting our worst fears head-on, butteaches us that we can become a better, more compassionate, and prosperous globalsociety in the process.’’

—Stephen E. Flynn, Senior Fellow for Counterterrorism and National Security Studies, Council on Foreign Relations

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Learning from Catastrophes


Learning from Catastrophes

Strategies for React ion andResponse

Edited by Howard Kunreuther and Michael UseemAlan BergerCase BrownSéan ClearyArnold HowittBridget M. HutterMichel JarraudCarolyn KouskyHerman “Dutch” LeonardGeoff LoveThomas Lovejoy

Michele McNabbErwann Michel-KerjanSuzanne Nora JohnsonKristine PearsonHarvey RubinJiah-Shin TehDetlof von WinterfeldtLan Xue Richard ZeckhauserKaibin Zhong

In Collaboration with the World Economic Forum Global Agenda Council on

the Mitigation of Natural Disasters

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Library of Congress Cataloging-in-Publication Data

Kunreuther, Howard.

Learning from catastrophes : strategies for reaction and response / Howard Kunreuther,Michael Useem.

p. cm.

Includes bibliographical references and index.

ISBN-13: 978-0-13-704485-6 (hardcover : alk. paper)

ISBN-10: 0-13-704485-2

1. Risk management. 2. Emergency management. I. Useem, Michael. II. Title.

HD61.K86 2010

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2009032585

Editor: Steve Kobrin

Publishing as Prentice Hall

Prentice Hall offers excellent discounts on this book when ordered in quantity

Contents

Foreword by Klaus Schwab . . . . . . . . . . . .xiii

Preface by Howard Kunreuther and Michael Useem . . . . . . . . . . . . . . . . . . .xv

Part I: Setting the StageChapter 1: Principles and Challenges for Reducing Risks

from Disasters . . . . . . . . . . . . . . . . . . . . . . . .1Howard Kunreuther and Michael UseemOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Framework for Analysis . . . . . . . . . . . . . . . . . . . . . 2Risk Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Risk Perception and Choice . . . . . . . . . . . . . . . . . . 6Risk-Management Strategies . . . . . . . . . . . . . . . . . 8Guiding Principles. . . . . . . . . . . . . . . . . . . . . . . . . 13

Chapter 2: Acting in Time Against Disasters: AComprehensive Risk-ManagementFramework . . . . . . . . . . . . . . . . . . . . . . . . . .18Herman B. “Dutch” Leonard and Arnold M. HowittOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Managing Large-Scale Social Hazards . . . . . . . . . 19Points of Intervention: When and Where Can We Invest Most Effectively? . . . . . . . . . . . . . . . . . 23The Level and Balance of the Current Portfolio of Risk-Management Efforts . . . . . . . . . . . . . . . . 29The More General Problem of Acting in Time . . 37Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Part II: Linking Risk Assessment, Risk Perception, and Risk ManagementChapter 3: Forecasting and Communicating the Risk of

Extreme Weather Events . . . . . . . . . . . . . .41Geoff Love and Michel JarraudOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42Assessing Risk and Characterizing Uncertainty onClimate Timescales . . . . . . . . . . . . . . . . . . . . . . . . 45Assessing Risk and Characterizing Uncertainty forExtreme Weather Events . . . . . . . . . . . . . . . . . . . 52Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Chapter 4: Cognitive Constraints and Behavioral Biases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Séan ClearyOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Thinking About Complex Systems . . . . . . . . . . . . 66How Do We Cope? . . . . . . . . . . . . . . . . . . . . . . . . 69How Can We Improve Our Performance? . . . . . 78

Chapter 5: The Five Neglects: Risks Gone Amiss . . . .83Alan Berger, Case Brown, Carolyn Kousky, andRichard ZeckhauserOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83The Five Neglects . . . . . . . . . . . . . . . . . . . . . . . . . 86Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Chapter 6: Can Poor Countries Afford to Prepare forLow-Probability Risks? . . . . . . . . . . . . . . .100Michele McNabb and Kristine PearsonOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

viii LEARNING FROM CATASTROPHES

Can Poor Countries Afford to Prepare for Low-Probability Risks? . . . . . . . . . . . . . . . . . . . . 101State of Early Warning in Developing Countries:High-Probability Events . . . . . . . . . . . . . . . . . . . 103State of Early Warning in Developing Countries:Low-Probability Events . . . . . . . . . . . . . . . . . . . 105High or Low Probability: How Climate Change Is Changing the Nature of Risk . . . . . . . . . . . . . 106Who Should Pay for Early Warning? . . . . . . . . . 107Options for Early Warning for Devastating Low-Probability Events in Poor Countries . . . . 114Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

Chapter 7: The Role of Risk Regulation in MitigatingNatural Disasters . . . . . . . . . . . . . . . . . . . .121Bridget M. HutterOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Regulating Risk . . . . . . . . . . . . . . . . . . . . . . . . . . 123The Importance of Information . . . . . . . . . . . . . 125Important Considerations and Constraints . . . . 133Discussion: Lessons and Recommendations . . . 135

Chapter 8: Hedging Against Tomorrow’s Catastrophes:Sustainable Financial Solutions to HelpProtect Against Extreme Events . . . . . . . .139Erwann O. Michel-KerjanOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140How Much Are You Willing to Lose When the Next Catastrophe Strikes?. . . . . . . . . . . . . . . . . . 142How Alternative Risk-Transfer Instruments Provide Financial Protection Against ExtremeEvents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145How Financial Instruments Can Help the Developing World . . . . . . . . . . . . . . . . . . . . . . . . 152Further Expanding Alternative Risk-Transfer Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

CONTENTS ix

Part III: Applications to Catastrophic RisksChapter 9: A Financial Malignancy . . . . . . . . . . . . . . .156

Suzanne Nora JohnsonOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156Coordination and Cooperation . . . . . . . . . . . . . . 158Clarity of Communication . . . . . . . . . . . . . . . . . 163Control of Toxins . . . . . . . . . . . . . . . . . . . . . . . . . 164Capital and Cushion . . . . . . . . . . . . . . . . . . . . . . 165Co-Investment. . . . . . . . . . . . . . . . . . . . . . . . . . . 166Courage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Chapter 10: Climate Change: Nature and Action . . . .170Thomas E. LovejoyOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170The Earth as a Biophysical System. . . . . . . . . . . 170

Chapter 11: Lessons from Risk Analysis: Terrorism,Natural Disasters, and TechnologicalAccidents . . . . . . . . . . . . . . . . . . . . . . . . . .177Detlof Von WinterfeldtOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177A Brief History of Risk Analysis . . . . . . . . . . . . . 178What Can Terrorism Risk Analysts Learn from Risk Analyses of Natural and Technological Disasters?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181What Can Natural and Technological Disaster Risk Analysts Learn from Terrorism Risk Analysis? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

Chapter 12: Turning Danger ( ) to Opportunities ( ):Reconstructing China’s National System forEmergency Management After 2003 . . . .190Lan Xue and Kaibin ZhongOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191Weaknesses in the Traditional Model: Lessons from SARS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

x LEARNING FROM CATASTROPHES

Restructuring a New National System for Emergency Management: Chinese NSEM 2.0 After SARS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197New Challenges and the Way Forward . . . . . . . 205Moving into NSEM 3.0: Major Issues to Resolve. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208

Chapter 13: Dealing with Pandemics: Global Security, Risk Analysis, and Science Policy . . . . . . .211Jiah-Shin Teh and Harvey RubinOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212Infectious Diseases: An Enduring Threat . . . . . 216Antibiotic Resistance. . . . . . . . . . . . . . . . . . . . . . 217Agricultural Practices . . . . . . . . . . . . . . . . . . . . . 220Dual-Use Research of Concern . . . . . . . . . . . . . 221Emerging and Re-emerging Infectious Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224Preparedness Against Biological Events . . . . . . 226An International Compact for Infectious Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

Part IV: Innovation and Leadership Chapter 14: Long-Term Contracts for Reducing Losses

from Future Catastrophes . . . . . . . . . . . . .235Howard KunreutherOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235Two Illustrative Examples. . . . . . . . . . . . . . . . . . 236Behavioral Biases. . . . . . . . . . . . . . . . . . . . . . . . . 238Reducing Losses and Fatalities from Natural Disasters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239Dealing with Interdependencies in Organizations. . . . . . . . . . . . . . . . . . . . . . . . . . . . 245Future Research Needs . . . . . . . . . . . . . . . . . . . 248

CONTENTS xi

Chapter 15: Developing Leadership to Avert and MitigateDisasters . . . . . . . . . . . . . . . . . . . . . . . . . . .249Michael UseemOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249Experience-Anchored Leadership Precepts . . . 251Merck & Co., Inc. . . . . . . . . . . . . . . . . . . . . . . . . 259Preparing Leadership for a Firefighting Crisis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263The Enduring Importance of Leadership in the Face of Extreme Risk . . . . . . . . . . . . . . . . . . . . . 267

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . .269

About the Authors . . . . . . . . . . . . . . . . . . .307

World Economic Forum Global AgendaCouncil on the Mitigation of Natural Disasters . . . . . . . . . . . . . . . . . . . . . . . . . . .313

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . .317

xii LEARNING FROM CATASTROPHES

Foreword

In late autumn 2008, more than 700 experts gathered in Dubaifor the inaugural meeting of the World Economic Forum’s GlobalAgenda Councils. Initiated less than 12 months earlier, the ideabehind the Councils was to bring together some of the best mindsfrom business, academia, and government to focus on the most press-ing questions of our times. From that gathering emerged fresh think-ing, sometimes provocative, sometimes pragmatic, as to how tomobilize the combined forces of the public, private, and nongovern-mental sectors around issues ranging from global economic imbal-ances to ecosystems and biodiversity. One of these councils, theCouncil on the Mitigation of Natural Disasters, under the chairman-ship of Howard Kunreuther and Michael Useem, left Dubai with aneven stronger vision of the need for a holistic approach to this issue, avision they explore in this book.

The initial focus of the council members was on natural catastro-phes, which wreak havoc on lives, communities, and economies.These events occur across countries, climates, and economic sectors,and only mitigating strategies, preparedness, and response readinesscan make a difference. What emerged from the council’s thinking washow much the principles and operational elements relevant for natu-ral catastrophe mitigation and management can be applied to otherincident-driven risks. In their discussions with experts and practition-ers from fields as diverse as terrorism prevention, pandemic pre-paredness, and technical or even nuclear accident avoidance, thecouncil’s principles were unanimously deemed applicable.

Thus, the focus of Learning from Catastrophes is on improvingour ability to identify and manage events that are perceived to behighly unlikely, but which, if they do occur, can have catastrophicimpact at both the national and global levels. Left to our own devices,we tend to underappreciate such low-probability, high-consequenceevents. Our minds often turn them into “no likelihood”—althoughsometimes into the opposite and equally pernicious prescription of

“near certainty.” As a result, those who are responsible for leadingmajor institutions have a special and specific calling to recognize andguard against these human shortcomings.

The empirical evidence presented in this book points to the valueof building an effective forecasting capacity and persuasively commu-nicating information on high-consequence risks to everybody poten-tially affected. The authors also recommend drawing upon economicand other incentives to encourage individuals, firms, and public agen-cies to work together in undertaking protective measures for reduc-ing losses from disasters and in building a culture of resilience andsustainability.

To avoid and mitigate both natural and unnatural calamities inthe future, you will want to incorporate this book’s directives intoyour strategic and operational planning processes and leadership pro-grams. Leaders from business and the public and nonprofit leaderscould do a lot to protect their organizations and communities by put-ting the principles highlighted in Learning from Catastrophes intopractice. This book provides a useful set of principles for guidingdecision making and leadership so essential for averting and over-coming those future risks that are sure to threaten yet again ourglobal prosperity.

—Klaus SchwabFounder and Executive ChairmanWorld Economic Forum

xiv LEARNING FROM CATASTROPHES

Preface

According to the 2008 World Disasters Report, natural calamitiesin 2007 affected more than 200 million people. Their direct cost in2007 totaled more than $60 billion; the financial impact of theSichuan earthquake in 2008 alone has been estimated to exceed $70billion. The cost of the 2008–09 global financial crisis reached hun-dreds of billions of dollars in many countries. A widespread outbreakof swine flu could wreak havoc on a comparable scale.

This book offers critical lessons for those who are most responsi-ble for avoiding the worst, whether natural calamities or unnaturalcatastrophes ranging from financial crises to terrorist attacks.

All are low-probability but high-consequence events. By examin-ing what worked and what did not in prior disasters, we can be betterequipped to prevent and mitigate future disasters. One cannot fullylearn to effectively manage extreme risk without looking to the les-sons from both natural and unnatural disasters.

If New Orleans had well-maintained levees and evacuationplans, land-use management programs, and well-enforced buildingcodes, and if insurers could charge premiums that reflected risk andcould reward with price reductions those who adopted loss-reduc-tion measures, the devastation from Hurricane Katrina would havebeen far less. But in fact, short-term savings trumped long-termsafeguards.

If federal regulators had required transparency in credit-defaultswaps, if bank CEOs had insisted that quarterly windfalls be balancedagainst future earnings, and if loan officers had to live with the sub-prime risks they were foisting on others, we would be talking aboutmarket correction, not credit calamity. But in fact, private greedtrumped collective good.

If we know that we will predictably underpredict—and thusunderanticipate the next catastrophe—we can do something about itin advance. Now is the time for all of us to appreciate the importanceof recognizing risks and preparing for them before they result in

another Katrina washout or credit tsunami. Above all, leaders need toremember that a low risk is not no risk.

Drawing on the knowledge of a select set of leading experts onnatural disasters and other extreme events, this book takes stock ofwhat we know about decision making, risk reduction, and strategiesfor encouraging preventive actions. Learning from Catastrophes pro-vides a framework and a core set of principles for designing strategiesfor managing risks that have a relatively small chance of occurring—but could create severe consequences if they do.

Learning from Catastrophes is intended for readers with a gen-eral or professional interest in understanding behavior and develop-ing more effective strategies for reducing losses from low-probability,high-consequence events. These events include large-scale naturaldisasters, financial crises, industrial accidents, rogue trading, corpo-rate bankruptcies, pandemics, and terrorist attacks. The book shouldbe of interest to policy makers, risk managers, and business leaders;those directly engaged in preparation for, mitigation of, and recoveryfrom catastrophes; and decision makers in organizations ranging frominsurance firms and financial companies to emergency preparednessagencies and other governmental organizations concerned with therisks from disasters.

We owe a great debt of gratitude to World Economic ForumExecutive Chairman Klaus Schwab for his leadership in creating andsupporting the Global Agenda Councils. We are extremely grateful aswell for the assistance of Matthias Caton, Martina Gmür, StéphaneOertel, Fiona Paua, and Sheana Tambourgi of the World EconomicForum in supporting our Global Agenda Council on the Mitigation ofNatural Disasters. It was through a number of wide-ranging discus-sions with members of this council and a meeting of all the councils inDubai in November 2008 that this book took shape.

We also want to thank Carol Heller of the Wharton Risk Manage-ment and Decision Processes Center, for her careful and comprehen-sive guidance of this project from its inception to the completion ofthis book. Jeanne Glasser, Russ Hall, Steven Kobrin, Timothy C.Moore, Teresa Regan, and Jovana San Nicolas-Shirley of WhartonSchool Publishing provided unstinting support in bringing this bookto completion so that it would be available in time for the Annual

xvi LEARNING FROM CATASTROPHES

Meeting of the World Economic Forum in Davos, Switzerland, in2010. We hope, in time, that lessons from this book will help toreduce the potential impact of future catastrophes.

—Howard Kunreuther and Michael UseemThe Wharton School, University of Pennsylvania October 2009

PREFACE xvii


Principles and Challenges for ReducingRisks from Disasters

Howard Kunreuther and Michael Useem

The Wharton School, University of Pennsylvania

OverviewThis chapter provides a framework and a set of guiding principles

for designing alternative strategies for reducing losses from low-probability, high-consequence events. This framework highlights theimportance of expert assessment of the risk, as well as the importanceof understanding how the public perceives the risk. These two ele-ments should serve as a basis for developing and evaluating strategiesto manage risk. Seven principles provide guidance to leaders indesigning measures that will reduce losses in advance of a disasterand in developing efficient and equitable means to aid the recoveryprocess following a catastrophe.

The past decade has been particularly devastating on the naturaldisaster front, especially in developing countries. The tragic tsunamiof December 2004 killed more than 280,000 people in SoutheastAsia. Cyclone Nargis in May 2008 killed an estimated 140,000 inMyanmar. A 7.9-Richter-scale earthquake in the same month killednearly 70,000 and left some 5 million homeless in China. Widespreadflooding in Mozambique following a tropical storm in February andMarch 2000 displaced more than a million residents.

1

1

2 LEARNING FROM CATASTROPHES

Even in a developed country like the United States, which hasextensive experience with natural catastrophes and ample resourcesto prepare for them, the 2004 and 2005 hurricane seasons proveddevastating. Hurricane Katrina, which hit Louisiana and Mississippiat the end of August 2005, killed 1,300 people and forced 1.5 millionto evacuate—a record for the country. Economic damages were esti-mated at more than $150 billion.

The world experienced comparably catastrophic shocks in 2008.The subprime mortgage crisis of mid-2008 overwhelmed dozens offinancial companies in the United States, from Fannie Mae and Fred-die Mac to Lehman Brothers and AIG. The stock market crash in theautumn destroyed more than a trillion dollars in investor wealth world-wide. The great credit squeeze directly impacted Main Street in devel-oped countries and “No Street” in emerging economies, leading toworldwide recession in 2009.

This book provides experience-based and research-informedinsights into how individuals engaged in disaster mitigation can bettermanage the risk associated with both natural and unnatural calami-ties. Here we provide a framework that highlights the importance oflinking risk assessment and risk perception in designing strategies formanaging risks in our increasingly interconnected world. The frame-work also outlines a set of guiding principles for the role that leaderscan take to mitigate those risks and effectively respond when the pos-sibility of an extreme event turns into reality.

Framework for AnalysisSystematically investigating the impacts of natural and unnatural

disasters requires input from many disciplines. Engineering and thenatural sciences provide data on the nature of the risks associatedwith disasters of different magnitudes and the uncertainties sur-rounding them (risk assessment). Geography, organizational theory,psychology, sociology, and other social sciences provide insights intohow individuals, groups, organizations, and nations perceive risks andmake decisions (risk perception and choice). Economists and policyanalysts examine various strategies for reducing future losses and fordealing with recovery problems (risk management strategies).

1 • PRINCIPLES AND CHALLENGES FOR REDUCING RISKS FROM DISASTERS 3

Risk AssessmentThe science of estimating the chances of specific extreme events

occurring and their potential consequences originates in the field ofproperty insurance and the science of natural hazards. In the 1800s,residential insurers managed their risk by “mapping” the structuresthat they covered, pinning tacks onto a wall map to display the degreeof physical concentration of exposure. Although crude, the techniqueserved insurers well at the time and limited their risk. Widespreadusage of such “mapping” ended in the 1960s when it finally becametoo cumbersome and time-consuming to execute. Now, GeographicInformation Systems (GIS) software and other digital productsachieve the same with much more extensive data and sophisticatedtechnologies.1

Whatever the risk-assessment process method, four basic ele-ments for assessing risk remain the same: hazard, inventory, vulnera-bility, and loss (see Figure 1.1). The first element focuses on the riskof a hazard. For example, an earthquake hazard is characterized byits likely epicenter location and magnitude, along with other signifi-cant parameters. A hurricane is distinguished by its projected pathand wind speed. One could also describe the hazard associated withterrorism or a pandemic by characterizing the target of a violentattack or the spread rate of a potentially catastrophic disease such asswine flu or severe acute respiratory syndrome (SARS). The hazardcan also be usefully characterized as a range of potential scenarios.For example, what is the likelihood that a hurricane of magnitude 3,4, or 5 on the Saffir-Simpson scale might strike the Miami, Florida,area in 2010?

Hazard

Vulnerability

Inventory

Loss

Figure 1.1 Elements of the risk-assessment process model


The risk-assessment process model’s second element identifiesthe inventory of properties, humans, and the physical environment atrisk. To fully inventory structures, for instance, requires evaluation oftheir location, physical dimensions, and construction quality. Takentogether, the hazard and inventory elements enable calculation of themodel’s third element, the damage vulnerability of the structures orpeople at risk. And from the measure of vulnerability, the human andproperty loss, the fourth element, can be evaluated.

In working with catastrophes in this model, it is also useful to dis-tinguish between direct and indirect losses. Direct losses includeinjuries, fatalities, financial losses, and the cost to repair or replace astructure, restore a service, or rescue a company. Indirect lossesinclude future foregone income, slower growth, and other longer-term consequences of evacuation costs, disrupted schooling, and com-pany bankruptcies.

Scientists and engineers develop reasonably accurate models forassessing risk with this model and specifying the degree of uncer-tainty in each of the components. In doing so, analysts take specialcare to minimize the role of subjective assessments and personalbiases in building their estimates. But because such factors stillsometimes intrude, it is not uncommon for the public to learn fromone expert that there is little about which to be concerned related toa given risk, and from another expert that the alarm bells should besounding.

Not surprisingly, the public responds in disparate ways to theadded uncertainty resulting from conflicting expert forecasts. Somemay simply decide to ignore the expert judgments. Others may bedrawn to the expert prediction most compatible with the individual’sown predispositions. Still others may seek out a host of expert opin-ions and then draw independent assessments of where the prepon-derance of informed forecasts are pointing.

Consider the uncertainties inherent in the following natural andunnatural disasters:

• What are the chances that Tokyo will experience an earthquakeof magnitude 7 or greater next year, and what will be the result-ing property damage, human loss, and interruption of com-merce in Japan, East Asia, and beyond?


• What is the prospect of a major terrorist attack in Europe, andwhat would be the resulting human casualties and economicimpacts?

• What is the probability of an African pandemic in the next fiveyears, what type of disease is most likely to spread, where will itstart, and how soon will it reach other continents?

• What is the probability that 5 of the 20 largest financial institu-tions worldwide will fail within the next 24 months and eithergo bankrupt, as did Lehman Brothers, or enter governmentreceivership, as in the case of the Royal Bank of Scotland?

• What is the chance that the top ten insurance companies andcommercial banks will have their credit rating dropped fourtiers—say from AAA (almost no credit risk) to A1 or A+ (safeunless unforeseen events arise)—in the coming year?

When expert analysts attempt to answer these questions, theyusually ask for more precise information to define the event for theirmodel. Take the question related to the chances of an earthquake ofmagnitude 7 or greater in Tokyo next year. Experts will want to knowhow to define Tokyo (the city proper or the entire metropolitanregion), whether next year means the calendar or fiscal year, andwhat should be included among the indirect losses. Because expertsoften take variant responses to these kinds of questions into account,divergent forecasts for even relatively specific events can leave peo-ple and their leaders unclear whether and how to prepare andrespond.

For many years, the focus of hazard-loss estimation for naturaldisasters had been largely confined to property damage and loss oflife. And estimations were generally limited to the immediate periodof the disaster, just hours or days after the earth shook or floodwaterspeaked. Now, risk-assessment models are incorporating longer timeperiods extending to weeks and even months, and to more diversemeasures, such as disrupted commercial flows or post-traumaticstress disorders. As experts have expanded the time periods andrange of losses in their models, risk assessment has become muchmore complex and forecasts are likely to be fraught with uncertainty.That, in turn, has added to public and leadership hesitation on howbest to prepare for and react to disasters.

Risk Perception and ChoiceWhereas risk assessment focuses on objective losses such as

financial costs, risk perception is concerned with the psychologicaland emotional factors associated with risk. Research has demon-strated that the perception of risk has an enormous impact on behav-ior, regardless of the objective conditions.

In a set of path-breaking studies begun in the 1970s, decision sci-entists and psychologists such as University of Oregon’s Paul Slovic,Carnegie Mellon University’s Baruch Fischhoff, and others beganstudying people’s concerns about various types of risks. They foundthat people viewed hazards with which they had little personal knowl-edge and experience as highly risky, and they especially dreaded theirpossibility. In the case of unfamiliar technologies with catastrophicpotential such as nuclear power, people perceived the risks as muchhigher than did the experts.2

Research also found that people often perceive the world of low-probability and high-consequence events quite differently fromexperts, and that this impacts on their decision-making process andchoice behavior. For years, however, this disparity was simply ignoredby expert analysts, who made little effort to communicate the inven-tory, hazards, vulnerability, and losses from risks in ways that the pub-lic could accept and act upon. Sometimes, important underlyingassumptions were not made explicit; other times, complex technicalissues were not explained well; and often, little effort was made tohelp the public appreciate why experts could disagree with oneanother. Rarely were public perceptions even considered.

In recent years, however, the scientific and engineering communi-ties have devoted increased attention to the psychological factors thatimpact on how individuals make decisions with respect to risks fromnatural and technological hazards. Rather than simply urging policymakers and organizational leaders to take actions on the basis of theirtraditional risk-assessment models, experts are increasingly incorporat-ing salient human emotions such as fear and anxiety into the models.

Researchers have discovered that people are generally not wellprepared to interpret low probabilities when reaching decisionsabout unlikely events. In fact, evidence suggests that people may not



even want data on the likelihood of a disastrous event when the infor-mation is available to them. One study found, for instance, that whenfaced with several hypothetical managerial decisions that are risky,individuals rarely ask for data on the probabilities of the alternativeoutcomes. When one group was provided limited information aboutthe choices they were facing and given an opportunity to find outmore about their risks, fewer than one in four requested informationon the probabilities, and none sought precise likelihood data. Whenanother group was presented with precise probability data, fewerthan one in five drew upon the concept of probability when makingtheir choices between alternative courses of action.3

If people do not think probabilistically, how then do they maketheir choices in the face of risk? Extensive research on decision mak-ing now confirms that individuals’ risk perceptions are affected byjudgmental biases.4 One of the important forms of bias in the case ofextreme events such as large-scale disasters is a tendency for people toestimate the risk they face on the basis of their own experience regard-less of what the experts may have communicated. If an event is partic-ularly recent or impactful, people tend to ignore information on thelikelihood of a recurrence of the event and focus their attention on theconsequences should another similar disaster occur.5 Following theterrorist attacks with hijacked aircraft on September 11, 2001, manyof those living in the United States refused to fly because theybelieved that the chances of ending up on a hijacked aircraft were dan-gerously high—even though the actual likelihood was extremely lowgiven the tightened security measures introduced in the wake of 9/11.

More generally, researchers have found that people tend toassess low-probability, high-consequence events by focusing on oneend of the likelihood spectrum or the other: For some people, suchevents will surely happen, for others they will surely not happen, andfew fall in between. For very unlikely events, however, people crowdtoward the “will not happen” end of the spectrum. It is for this reasonthat there is a general lack of public interest in voluntarily purchasinginsurance against natural disasters and in investing in loss-protectionmeasures. People underestimate both the probability of a disasterand the accompanying losses, and they are often myopic when itcomes to proper planning for disasters. If a disaster does occur,

people then tend to overinvest in seeking to prevent a recurrence.Protective measures are thus undertaken when it is too late. A study ofhomeowners in California, for example, showed that most purchasedearthquake insurance only after personally experiencing an earthquake.When asked about the likelihood of another quake occurring in theirarea, they correctly responded that it was lower than prior to the disas-ter because the stress on the fault had been reduced. And yet that iswhen they finally decided to acquire the insurance.6

Risk-Management StrategiesIn developing effective risk-management strategies for reducing

losses from natural and unnatural disasters, leaders of public agenciesand private and nonprofit organizations will want to appreciate thefindings of risk-assessment studies and the factors that influence riskperception and choice. Drawing on that research, we propose sixareas for improving risk management:

1. Risk forecasting. The broadening of disaster losses to includelonger-term impacts and indirect costs has made forecastingmore complex. Improvement in the precision of these forecastsis critical for both averting disasters and minimizing theirimpacts. For example, more detailed weather forecasts of thepath and severity of a tropical storm can be key to wise evacua-tion decisions and avoiding unnecessary flight. So, too, would bebetter data on the systemic risks that little regulated but highlyleveraged financial products can invisibly create.

2. Communicating risk information. Because people generallydismiss low-probability events by assuming that they will notpersonally experience such events, expanding the time frameover which the likelihood of an extreme event is presentedcan garner more attention. If a company is considering flood-protection insurance for the 25-year life of a production facility,for example, managers are more likely to take the risk seriouslyif a 1-in-100-year flood is presented as having a greater than 1-in-5 chance of occurring during a 25-year period rather thana 1-in-100 chance during the coming year.7

3. Economic incentives. Both positive and negative economicincentives encourage individuals to take protective measures.



But here again, the way people process information on thecosts and benefits of reducing the risk can play an importantrole in their decision on whether to adopt the measures.

What would be the effectiveness, of say, a policy of reducinghomeowners’ insurance premiums for homeowners whoundertake loss-reduction measures along the Mississippi River,or a policy of incentivizing villagers in Bangladesh to avoidmigrating into flood-prone areas? Given that people think onlyabout the potential benefits of such measures over the nextyear or two, not the next decade or two, they may not viewthese measures as financially attractive if there is a significantup-front cost. Had they considered a longer time period whenevaluating the protective measure, the costs may well havebeen viewed as worthwhile.

Fines coupled with specific regulations or building standards canalso be used to encourage protective measures, but they, too,must be coupled with measures that ensure a high likelihood thatnegligent individuals will be penalized. If people perceive theprobability of detection to be low or the cost of noncompliance asmodest, they may conclude that it does not pay to take protectiveaction.

4. Private-public partnerships. Because the public, private, andnonprofit sectors share in the costs and benefits of preparing fordisasters, furthering collaboration among them ahead of timecan be vital for building effective leadership and strategies forfacing disasters. Public-private partnerships should thus be cre-ated before they are needed.

Insurance premium reductions should be given to those whoinvest in risk-reducing measures to reflect the lower lossesfrom a future disaster. Building codes may be desirable whenproperty owners would otherwise not adopt cost-effective miti-gation measures because they either misperceive the benefitsfrom them or underestimate the probability of a disaster occur-ring. This might have been a factor in the widespread loss oflife in the Pakistan earthquake, magnitude 7.6, in October2005, which killed more than 70,000 inhabitants, many buriedunder poorly constructed schools and homes. So, too, with

investment codes: Had there been stronger regulation onderivative products, such as insurance on subprime mortgagesecurities, investment bankers would have been less likely tocontribute to the systemic risks that rocked the world’seconomy in 2008.

5. Reinsurance and other financial instruments. The shortageof reinsurance—insurance for insurance companies that allowsthem to offer greater protection to policyholders than the assetsof the insurers would ordinarily permit—following HurricaneAndrew’s damage to Florida in 1992 and the Northridge, Cali-fornia, earthquake in 1994, led U.S. financial institutions tomarket new instruments for providing protection against megadisasters. Known as catastrophe bonds, these were offered athigh interest rates to overcome investors’ qualms about the like-lihood of losing their principal should a major disaster occur.The market for such bonds grew rapidly in the 2000s, with $2.7billion in new and renewed catastrophe bond issues in 2008.8

In anticipating exceptionally massive disasters, it may be neces-sary for the government to provide insurance protection to payfor losses that the private sector is not willing to cover. Floridaestablished the Florida Hurricane Catastrophe Fund followingHurricane Andrew in 1992, for instance, when a number ofinsurers reported that they could no longer include windstormdamage as part of their standard homeowner coverage. After theNorthridge earthquake in 1994, insurers backed off from earth-quake coverage, and the state formed the California EarthquakeAuthority to provide homeowners with earthquake coverage.

In providing coverage against large-scale catastrophes, it isimportant that premiums closely reflect risk. Equity andaffordability considerations may justify some type of subsidy forthose deserving special treatment, such as low-income resi-dents. This subsidy should not be in the form of artificially lowpremiums, but should preferably take the form of a grant fromthe public sector. For example, if a risk-based flood insurancepremium of $2,000 is considered to be unaffordable to a house-hold in a high hazard area, the family could be provided aninsurance voucher to buy a policy in much the way that food



stamps are provided to those in need of household staples. Ifthe family reduces its risks by investing in a mitigation measuresuch as elevating its house, it receives a premium discount.

6. Resiliency and sustainability. The resilience of a communityafter a disaster and its sustainability over the long run haveimportant ramifications for estimating the extent of hazarddamage and developing risk management policies. Resiliencerefers to the ability of a business, household, or community tocushion potential losses through inherent or explicit adaptivebehavior in the aftermath of a disaster and through a learningprocess in anticipation of a future one. Businesses may havealternative power generators in place, households may rationtheir water supply, and communities may open shelters forthose forced to evacuate their homes.9

Resilience also includes the ability to use price signals, such aspremium discounts for investing in mitigation measures, toencourage appropriate actions before and after a disaster. Andit entails the ability of community, company, and other leadersto remain focused on recovery even as they may be at risk orpersonally suffering in the immediate aftermath of a disaster.In the wake of Hurricane Katrina, for example, the presidentand senior administrators of Tulane University in New Orleanswere marooned on campus for four days without food, water,power, or regular contact with the outside world. Despite theirsevere personal circumstances, they plunged into the arduouswork of staff rescue and university restoration. After “beingstranded for four days,” recalled the president, Scott S. Cowen,“I realized that I could either focus on the darkness, or I couldtry to see beyond it and focus on the light. I chose the latter.” Inreflecting on the experience and its personal hardships, he said,it “has taught us as an institution to stay focused on our missionand goals even in the face of financial and physical crisis. It hastaught us the responsibility that comes with our role as thelargest employer in our home city—a responsibility to helprebuild our city and heal its people.”10

Advanced economies are becoming increasingly interlinkedand dependent on sophisticated, vulnerable systems—especially

infrastructural services such as highways, electric supply, andthe Internet—for which substitution is difficult and thusresilience more critical. When the west coast of Japan was hitby a minor earthquake in July 2007, a supplier of auto pistonrings was forced to close, and because Japanese auto makingwas built on a just-in-time inventory system, the supplier’s clos-ing forced Toyota and Honda to suspend production.11

Researchers have a role to play here in identifying ways toimprove resilience in a more interdependent and intercon-nected world, such as the establishment of informationclearinghouses for suppliers without customers and forcustomers without suppliers.

Sustainability refers to the long-run viability and self-sufficiencyof the community in the face of hazard threats. The more gen-eral definition of the term emanates from economic develop-ment and stipulates that decisions taken today should notdiminish productive capacity—broadly defined to include nat-ural resources and the environment of a community—in thefuture. In the case of natural hazards, sustainability implies thatland-use decisions made today—such as forest management orstrip mining—should not place the community in greater jeop-ardy in the future or make it more dependent on external assis-tance to survive. Sustainability emphasizes the importance ofintegrating mitigation measures into overall economic develop-ment policy and eliminating practices that increase a commu-nity’s exposure to hazards.12

Many developing countries are especially vulnerable to disas-ters because of low-quality structures, poor land use, inade-quate emergency response, environmental degradation, andlimited funds. Climate change may especially increase the like-lihood of disasters in these areas, such as flooding in low-lyingBangladesh. Developing countries often lack the infrastructureand institutions that developed countries take for granted informulating risk management strategies. And in areas wherepoverty is extreme, the indirect effects of disaster may includea surge in endemic disease, widespread starvation, and human-rights violations. In the wake of the Mozambique flooding in



2000, for instance, families irretrievably lost birth certificates,marriage documents, and land titles because few personalrecords had been backed up or computerized.

Guiding PrinciplesIn characterizing and developing strategies and leadership for

perceiving, assessing, and managing risks associated with extremeevents, it is useful to focus on a set of guiding principles. These prin-ciples apply not only to leadership in averting and responding to nat-ural catastrophes but also to leadership facing other extreme events,whether terrorist attacks, financial crises, or governance failures. Webriefly highlight these principles here:

Principle 1: Appreciate the importance of estimating risksand characterizing uncertainties surrounding such esti-mates. For developing the strategies and leadership for reduc-ing and managing a specific risk, it is essential to have reliableestimates of the likelihood of the event and its consequences.Consider a business facing a decision on whether to invest$100,000 to make its property more fire resistant. An informeddecision on whether to incur this cost depends on having accu-rate estimates of fire frequencies and likely losses. Its execu-tives will be more likely to make this investment if they learnthat the chances of a fire next year are 1-in-100 rather than 1-in-1,000, and if the likely property damage and businessinterruption would total $5 million rather than $500,000. Theless uncertainty surrounding these estimates, the more confi-dent the executives will be regarding their decision as towhether to undertake these measures.Principle 2: Recognize the interdependencies associatedwith risks and the dynamic uncertainties associated withthe interdependencies. Many factors contribute to extremerisk, and they are connected through ever-changing linkages.For disaster strategies and leadership, understanding the evolv-ing interconnectedness can be very challenging because thelinkages are often hidden or indistinct.

On December 21, 1988, Pan American flight 103 explodednear Lockerbie, Scotland. In Malta, terrorists had checked abag containing a bomb onto Malta Airlines, which maintainedminimal security procedures. Airport personnel transferred thebag at Frankfurt’s airport to a Pan Am feeder line, and person-nel at London’s Heathrow airport in turn loaded the bag ontoPan Am 103. The bomb was designed to explode above 28,000feet, a flight altitude normally attained over the Atlantic Ocean,though not over Europe. Terrorists had deliberately exploitedwidely varying security procedures in place across the airportsand airlines. Measures to prevent an aircraft disaster were onlyas strong as the weakest link in the system.13

Relationships among these interdependencies evolve overtime, and measures to thwart their catastrophic impact on oth-ers may become inadequate later on. Airport authoritiesaround the world improved security for bag transfers in thewake of the loss of Pan Am 103, but terrorists did find otherways of working around airline security measures, as the worldlearned on September 11, 2001. And even though governmentregulators in a host of countries tightened their rules in thewake of the financial crisis of 2008, new forms of systemic riskmay nonetheless insidiously reappear beyond the reach of thenew regulatory provisions. Evolving uncertainties point to theneed for continuous vigilance and updating of risk-projectionmeasures.Principle 3: Understand people’s behavioral biases whendeveloping risk management strategies. Among the well-documented biases are misperceptions of the likelihood of cat-astrophic events, a focus on short-term concerns and returns,and a falsely optimistic confidence that a calamity will simplynot happen on my watch—the NIMTOF (not in my term ofoffice) phenomenon. Appreciating such biases is an importantstep for creating remedies and building cultures that canreduce or eliminate them.Many individuals, for instance, will not invest in protectivemeasures for a property unless they believe they can recouptheir investment in two or three years, even though the meas-ures will be of benefit as long as the property stands. Peopleoften purchase insurance following a disaster, not before, and



then tend to cancel their policies after a few years if they havenot collected on their policy. Rarely do people concur with theprinciple that “the best return on an insurance policy is noreturn at all” (that is, no loss whatsoever).Principle 4: Recognize the long-term impact of disasterson a region’s or nation’s politics, culture, and society.Catastrophes often create enduring change in areas far fromthe epicenter in ways that public and private leaders need toappreciate in taking preventive measures prior to a disaster anduse to their advantage in developing strategies following a cata-strophic event. The massive earthquake of 2008 in southeastChina, for example, stimulated private charitable giving,attracted international support, and revised how Chinese offi-cials view substandard schools, homes, and office buildings.Principle 5: Recognize transboundary risks by develop-ing strategies that are global in nature. Most disasters donot recognize political borders. The terrible Southeast Asiatsunami of 2004 killed residents of 11 countries. The Pakistanearthquake of 2008 left more than a thousand dead in neigh-boring areas of India. The failure of Lehman Brothers and thenear collapse of other American banks in 2008 had catastrophicconsequences for banks in dozens of other countries, fromBritain and Iceland to China and Mongolia.One strategy to address and minimize risks is to have countriessign a treaty to reduce certain environmental risks, such asglobal warming or atmospheric pollution. There are potentialbenefits to all societies if enough countries take action, butthere is also a net cost to any single country for adopting thetreaty, as the United States argued at one point in refusing tosign the Kyoto treaty. What incentive is there for any onenation to adopt a treaty if it knows that a number of other coun-tries will not join? How can policy makers and national leadersconvince countries with leverage to sign the treaty to induceothers to follow suit?Principle 6: Overcome inequalities with respect to thedistribution and effects of catastrophes. Whether naturalor human caused, disasters often bring disproportionate hard-ships to those already at risk from low income or poor health.

Public policies and private actions can help prepare a readinessplan on the part of those with more financial resources to sup-port those in distress with fewer resources.Consider the flow of domestic and international assistance toChina’s southeast Sichuan Province in the aftermath of its greatearthquake in 2008, with more than 69,000 dead (including19,000 school-children), 274,000 injured, and 4.8 millionhomeless. The Chinese government invested more than $100billion in the region’s restoration, dispatched more than 50,000soldiers and police to the area, and accepted humanitarian sup-port from abroad, including South Korea, Japan, Russia, theUnited States, and even Taiwan. The Red Cross Society ofChina and many private organizations and individuals providedrescue and restoration equipment and funds (Yao Ming, of theHouston Rockets, donated more than $300,000.) Together,they helped thousands of families of modest means recoverfrom the disaster. The experience points to the value of havinggovernment agencies and organizations such as the Red Crossprepared to provide assistance when it is most needed.

Principle 7: Build leadership for averting and respond-ing to disasters before it is needed. The best time to createa readiness to face and overcome a low-probability, high-consequence disaster is before the event occurs. Leadershipdevelopment is a time-consuming and labor-intensive process,and investing in it now can be seen as a preemptive and cost-effective measure to ensure that the six principles above areturned into active practice.Had American financial institutions and regulators takengreater care to understand the growth of systemic risk in theU.S. housing and derivatives market, and had they created agreater readiness among their leaders to anticipate sharpdownturns in those markets, the deep recession that the sys-temic risk caused in 2008 might not have reached such a depth.The failures of a host of banks, insurers, and manufacturersmight have been averted, and the jobs of millions in the UnitedStates and abroad might have been saved.



The risk-management strategies and guiding principles wehave identified here are intended to furnish a foundation forpublic and private policies and practices for preventing andreducing losses from low-probability, high-consequenceevents. The chapters that follow expand and draw upon thesestrategies and principles for catastrophic risks ranging fromnatural disasters to financial crises, and they provide guidanceto leaders in all institutions for designing and developing meas-ures to reduce losses and create a sustainable recovery in thewake of a catastrophe.

INDEXAAbandoned Mine Land Fund, 97abandoned mines, United States,

95-97Adelaide, Australia, heat waves,

46-47affective processes versus

cognitive processes, 74-75, 78Africa

drought, 109early-warning systems,

Kenya, 105flooding, 13, 109-113weather predictions, Ethiopia,

152-154agricultural practices, 220-221AIDS/HIV pandemic, 212AIG (American International

Group) and Financial ProductsDivision failures, 2, 252-258

airplane catastrophesPan American flight 103, 14World Trade Center (September

11, 2001), 7, 14, 180Alps, avalanches, 116alternative risk transfer (ART),

146, 154-155

317

American International Group(AIG) and Financial ProductsDivision failures, 2, 252-258

analytic processes. See cognitiveprocesses

Andrew (hurricane), 10antibiotic resistance, 217-220antibiotics in livestock

farming, 220Army Corps of Engineers, 33ART (alternative risk transfer),

146, 154-155Asia

cyclonesBangladesh, 104Myanmar, 1, 101-103, 113

earthquakesChina, 1, 16Pakistan, 9, 15

floodingChina, 191Southeast Asia, 109

SARS, 191-196tsunamis

December 2004, 1, 15early-warning systems,

104-106, 116asteroid collisions, 88

318 INDEX

atmospheric scientists, riskassessment role, 44-45

Australiaheat waves, Adelaide, 46-47cyclones, Dominic, 55-58forest fires, 62

Australian Bureau of MeteorologyAdelaide heat wave, 46-47cyclones, Dominic, 57-58forest fires, 62

avalanches, Alps, 116AXA French insurer, 152-153

BBangladesh

Cyclone Sidr, 104early-warning systems, 103, 113floods, 12

behavioral economics, 67Berkeley Pit, Montana, 96biological events

agricultural practices, 220-221antibiotic resistance, 217-220deliberate spreading, 214dual-use research of concern,

221-224International Compact for

Infectious Diseases, 231-233low-probability risks, high-

consequence, 214-217preparedness against

disease hallmarks, 226-227recommendations, 227-230

bionanotechnology, 222bioterrorism, 222-224“bounded rationality”

principle, 67

Ccalculus distortions, 69California

earthquakesinsurance, 10risk perception, 8

flooding, Napa Valley, 91wildfires, Ventura County, 38

California Earthquake Authority, 10

carbon dioxide (CO2) levelsoceans, 173preindustrial to current day,

171-172removing from atmosphere,

174-176case studies, neglects

Italy’s Pontine Marshes, 93-95

United States, abandonedmines, 95-97

catastrophe bonds, 147-151alternative uses, 150-151

catastrophesinsurance

ART (alternative risktransfer), 146, 154-155

catastrophe bonds, 147-151ILWs (industry loss

warranties), 146-147insured losses, 142

1970–2008, most costly, 142, 145

lack of loss-reduction strategiesorganizational attitudes,

237-239organizational

interdependencies,245-247

research needed, 248uncertainties, 4-5, 13

INDEX 319

Center for Risk and EconomicAnalysis of Terrorism(CREATE), 180-181, 185

Chinaearthquake, May 2008, 1, 16financial interdependence with

United States, 159NSEM 1.0 (national system for

emergency management), 191SARS and NSEM

weaknesses, 191-196Yangzi River flooding 1998,

191NSEM 2.0 (national system for

emergency management)after SARS, 197Emergency Response

Law, 205nationwide contingency

plans, 199-202new challenges, 206-207new institutional structure,

197-199NSEM 3.0 issues, 208-210response mechanism

improvements, 202-205Clark Fork Basin Sites, Montana,

96-97climate change

global warming, 171-176Greenhouse effect, 170risk-assessment, 106-107

CO2 (carbon dioxide) levelsoceans, 173preindustrial to current day,

171-172removing from atmosphere,

174-176cognitive biases, 70-71cognitive errors, 71

cognitive processes versusaffective processes, 74-75, 78

Colorado, Summitville Mine, 95-97

Columbia Space Shuttle risks, 178consequence neglect, 86-88consequences, element of risk

analysis, 177, 181, 184-186corporations, catastrophe

bonds, 150countercyclical capital, 166Cowen, Scott S, 11CREATE (Center for Risk and

Economic Analysis ofTerrorism), 180-181, 185

crisis management, 19. See alsorisk management strategiesdisaster events, 23-33

Cuba, early-warning systems, 103cultural thought patterns, 66cyclones

Australia, Dominic, 55-58Bangladesh, Sidr, 104early-warning systems, 103impact on economies, 239Myanmar

Nargis, 101-103, 113May 2008, 1

risks and uncertainties, 54-56,59-60

DDepartment of Defense (U.S.)

Army Corps of Engineers, 33budgetary bargaining with

Pentagon and White House, 36Department of Homeland

Security (U.S.), 180

320 INDEX

developing countrieslow-probability risks, 101-103natural catastrophes, 1risk regulation, 133warning systems

high-probability events,103-105

low-probability events, 105-106, 114-119

DHS (Department of HomelandSecurity), U.S. 180

disadvantaged countries. Seedeveloping countries

disaster eventsdeveloping countries

high-probability eventwarnings, 103-105

low-probability eventwarnings, 105-106

low-probability risks, 101-103

early-warning systemsclimate change effects,

106-107cost responsibilities, 107-114low-probability events,

114-119interventions

crisis management andresponse, 23-33

prevention and mitigation,23-24, 28-33

recovery, 24-29, 32-33risk analysis, 180social welfare paths, 21-23

disciplinary thought patterns, 66disease controls

agricultural practices, 220-221antibiotic resistance, 219-220biological event preparedness,

226-230

deterioration, 212-214dual-use research of concern,

221-224emerging and re-emerging

diseases, 224-226International Compact for

Infectious Diseases, 231-233DOD (Department of

Defense), U.SArmy Corps of Engineers, 33budgetary bargaining with

Pentagon and White House, 36Dominic cyclone, 55-58drought, West Africa, 109dual-use research of concern,

221-224

Eearly-warning systems

climate change effects, 106-107cost responsibilities, 107

community, 110-114global, 108regional, 109-110state, 110

developing countrieshigh-probability events,

103-105low-probability events,

105-106, 114-119earthquakes

Californiainsurance, 10risk perception, 8

China, May 2008, 1, 16impact on economies, 239loss-reduction strategies

long-term loans/insurance,242-243

Pakistan, 9, 15risk analysis, 180

INDEX 321

economic catastrophescapital requirements, 165-166courage restoration, 168-169global considerations, 158-161government and private

investments, 166-168government responses, 163-164hazard/loss time period

extension, 5, 15local considerations, 161-163mortgage crisis, mid-2008, 2, 72risk analysis, 187risk identification/control,

164-165uncertainties, 4-5, 13

economic incentives, 8-9economics. See also

neuroeconomicsegocentric interpretation, 68-69Emergency Management Office

(EMO), China, 198Emergency Response Law,

China, 202-205EMO (Emergency Management

Office), China, 198epidemics/pandemics

antibiotic resistance, 220consequences, 214-215HIV/AIDS, 212preparedness, 215-216SARS (Severe Acute Respiratory

Syndrome), 191-197Ethiopia, weather predictions,

152-154EU (expected utility) theory,

83-85exceedance probability curves,

178-180expected utility (EU) theory,

84-85

experience-anchoredleadership, 251actions in low-probability, high-

consequence events, 258-259active listening to subordinates,

251-252AIG and AIGFPD failures,

252-258firefighting crises, 263-266long-term strategic thinking,

259-262risk situations, 267-268

external risk neglect, 86, 91-92Pontine Marshes, 93-95United States, abandoned mines,

95-97

FFannie Mae, 2FEMA (Federal Emergency

Management Agency), 33FIFA (International Federation

of Association Football),catastrophe bonds, 150

financial crisiscapital requirements, 165-166courage restoration, 168-169global considerations, 158-161government and private

investments, 166-168government responses, 163-164hazard/loss time period

extension, 5, 15local considerations, 161-163mortgage crisis, mid-2008, 2, 72risk analysis, 187risk identification/control,

164-165uncertainties, 4-5, 13

322 INDEX

financial institution regulators,162-163

firefighting crisis leadership, 263-266

five neglectsconsequence neglect, 86-88external risk neglect, 86, 91-92

Pontine Marshes, 93-95United States, abandoned

mines, 95-97probability neglect, 86-87solution neglect, 86, 90-91statistical neglect, 86, 88-89

United States, abandonedmines, 97

floodingAfrica, 109Bangladesh, 12China, Yangzi River, 191impact on economies, 239loss-reduction strategies

long-term insurance, 243-245

long-term loans and long-term insurance, 242

property owner viewpoint,236-241

Mozambique, 1, 13, 111-113Napa Valley, California, 91protective measures, 9risk analysis, 180Southeast Asia, 109St. Louis, Missouri, 91United States, 33

Florida Hurricane CatastropheFund, 10

flu epidemics, 89forest fires

Australia, 62risks and uncertainties, 61

Framework Convention onClimate Change, 174-175

Freddie Mac, 2Freeplay Lifeline radio, 118

Ggambler’s fallacy, 89Geographic Information Systems

software (GIS) software, 3GEOSS (Global Earth

Observation System of Systems), 115

GIS (Geographic InformationSystems) software, 3

Global Agenda Councils, 314-316Global Assessment Report

on Disaster Risk Reduction(2009), 121

Global Earth Observation Systemof Systems (GEOSS), 115

global financial crisis, 158-161capital requirements, 165-166courage restoration, 168-169government and private

investments, 166-168government responses, 163-164local considerations, 161-163risk analysis, 187risk identification/control,

164-165global warming, 171-176Goldman Sachs, 162-163Greenhouse effect, 170greenhouse gases, 170-171group behavior and risk

perception, 71-72

INDEX 323

HHAIs (healthcare-associated

infections), 218-219hazard, risk-assessment process

model, 3-5, 15healthcare-associated infections

(HAIs), 218-219heat waves, 45-48

Australia, 46-47IPCC’s Working Group II

predictions, 50-51Western Europe, 47-48

heuristics, 66-67, 69-71HFA (Hyogo Framework for

Action 2005-2015), 110high-consequence biological

events, 214-217high-consequence events

low-probability risks, leadershipprecepts, 258-259

risk regulation, 125high-probability events

developing countries, 103-105early-warning systems

climate change effects, 106-107

cost responsibilities, 107-114HIV/AIDS pandemic, 212hurricanes

Andrew, 10impact on economies, 239Katrina, 2, 11, 23-24, 91,

101, 186risk analysis, 180United States, 2004 and 2005, 2,

11, 91hydrological scientists, risk

assessment role, 44-45Hyogo Framework for Action

2005-2015 (HFA), 110

Iidiosyncratic thought patterns, 66ILWs (industry loss warranties),

146-147Indian Ocean, tsunami

early-warning systems, 104-106, 116

industry loss warranties (ILWs), 146

infectious diseaseschallenges, 212consequences, 214-215control, deterioration of,

212-214deliberate spreading, 214emerging and re-emerging,

224-226enduring threat, 216-217hallmarks, 226-227International Compact for

Infectious Diseases, 231-233preparedness, 215-216recommendations for biological

event preparedness, 227-230insurance, 14

ART (alternative risk transfer),146, 154-155

catastrophe bonds, 147-151catastrophic accidents

organizational attitudes,237-239

organizationalinterdependencies,245-247

research needed, 248developing countries, 152-154ILWs (industry loss warranties),

146-147

324 INDEX

natural disastersimpact on economies, 239long-term insurance,

243-245long-term loans and long-

term insurance, 242-243property owner viewpoint,

236-241reinsurance, 10-11risk-sharing strategies, 131-133

insured losses, 1421970–2008, most costly, 142, 145

Intergovernmental Panel onClimate Change (IPCC), 171extreme weather events, 49-51heat waves, 50-51qualifiers expressing

uncertainty, 41terminology, 48-49

International Compact forInfectious Diseases, 231-233

International Federation ofAssociation Football (FIFA), 150

International Journal of RiskAnalysis, 180

International Strategy forDisaster Reduction, 137

inventory, risk-assessmentprocess, 3-4

investment portfolio for riskmanagement, 29-36

IPCC (Intergovernmental Panelon Climate Change), 171extreme weather events, 49-51heat waves, 50-51qualifiers expressing

uncertainty, 41terminology, 48-49

Italy, Pontine Marshes, 93-95

J–KJARring action, 91Journal for Medical Decision

Making, 180

Katrina (hurricane), 2, 11, 23-24,91, 101, 186

Kenya, early-warning systems, 105

Lleadership

experience-anchored, 251actions in low-probability,

high-consequence events,258-259

active listening tosubordinates, 251-252

AIG and AIGFPD failures,252-258

risk situations, 267-268firefighting crises, 263-266long-term strategic thinking,

259-262risk-management strategies, 267risk-reduction strategies, 266

learned behaviors, 69Lehman Brothers

catastrophe bonds, 151financial catastrophes, 2, 15

limbic processes. See affectiveprocesses

Lockerbie, Scotland, PanAmerican flight 103 crash, 14

loss, risk-assessment processmodel, 3-4direct or indirect, 4extension of time periods, 5, 15

INDEX 325

loss-reduction strategiescatastrophic accidents

organizational attitudes,237-239

organizationalinterdependencies,245-247

research needed, 248long-term insurance, 243-245long-term loans/insurance,

242-243natural disasters, economic

impact, 239property owner viewpoint,

236-241Louisiana, Hurricane Katrina, 2,

11, 23-24, 91, 101, 186Love Canal’s toxic waste, 87low-probability risks/events

developing countries, 101-106early-warning systems


cost responsibilities, 107-114developing countries,

114-119high-consequence events

biological, 214-217leadership precepts, 258-259risk regulation, 125

MMadagascar, early-warning

systems, 105malaria, 212, 219MANPADS (Man-Portable Air

Defense Systems), 182-184

Master Plan, China, 199, 201-202Emergency Response Law,

202-205media advice/warnings, weather

events, 53-54Mediterranean Sea, tsunami

early-warning systems, 106Merck & Co., Inc., 259-261Mexico, catastrophe bonds, 151Missouri, St. Louis, flooding, 91monocausal assumptions, 68Montana, Clark Fork Basin Sites,

96-97Morgan Stanley, 162-163mortgage crisis, mid-2008, 2, 72Mozambique

early-warning systems, 103-105flooding, 1, 13, 111-113

MyanmarCyclone Nargis, 101-103, 113cyclone, May 2008, 1

NNapa Valley, California,

flooding, 91Nargis (cyclone), 101-103, 113National Flood Insurance

Program (U.S.), 243National Hurricane Center

(U.S.), 60National Meteorological

and Hydrological Services(NMHSs), 44coordination with WMO (World

Meteorological Organization),54, 60

heat wave risks, 45-48

326 INDEX

weather event risk assessment,52-54

cyclones, 54-56, 59-60forest fires, 61

national system for emergencymanagement, China. SeeNSEM 1.0 and NSEM 2.0

National Weather Service (U.S.),57-60

natural capital, 80natural capital neglect, 90-97natural catastrophes

catastrophe bonds, alternativeuses, 150-151

developing countries, 1hazard/loss time period

extension, 5, 15uncertainties, 4-5, 13United States, 2, 91Global Agenda Councils,

314-316impact on economies, 239insurance

ART (alternative risktransfer), 146, 154-155

catastrophe bonds, 147-151developing countries,

152-154ILWs (industry loss

warranties), 146-147insured losses, 142, 145loss-reduction strategies

long-term insurance,243-245

long-term loans and long-term insurance, 242-243

property owner viewpoint,236-241

risk analysis lessonsfor terrorism risk analysis,

181-186from terrorism risk analysis,

186-188risk assessment and management

challenges, 78-79neglects

consequence neglect, 86-88external risk neglect, 86, 91-92

Pontine Marshes, 93-95United States, abandoned

mines, 95-97natural capital neglect, 90-97probability neglect, 86-87solution neglect, 86, 90-91statistical neglect, 86-89

United States, abandonedmines, 97

neuroeconomics, 74-78New Orleans, Louisiana,

Hurricane Katrina, 2, 11, 23-24,91, 101, 186

Niagara Falls, New York’s LoveCanal, 87

NMHSs (National Meteorologicaland Hydrological Services), 42, 44coordination with WMO (World

Meteorological Organization),54, 60

heat wave risks, 45-48weather event risk assessment,

52-54cyclones, 54-56, 59-60forest fires, 61

INDEX 327

NSEM 1.0 (national system foremergency management),China, 191SARS and NSEM weaknesses,

191-193communication/coordination

breakdown, 194-195public communication

inadequate, 195-196slow response to SARS,

193-194Yangzi River flooding 1998, 191

NSEM 2.0 (national system foremergency management), ChinaEmergency Response Law, 205nationwide contingency plans,

199-202new challenges, 206-207new institutional structure,

197-199NSEM 3.0 issues, 208-210response mechanism

improvements, 202-205after SARS, 197

nuclear power plant safety, 178

O–PPacific Ocean, tsunami

early-warning systems, 105Pakistan, earthquake, 9, 15Pan American flight 103, 14pandemics/epidemics

catastrophe bonds, 150consequences, 214-215HIV/AIDS, 212preparedness, 215-216SARS (Severe Acute Respiratory

Syndrome), 191-197

paradigms, 66-67Planning-Programming-

Budgeting System (PPBS), 36Pontine Marshes, Italy, 93-95poor countries. See developing

countriesPPBS (Planning-Programming-

Budgeting System), 36prejudices in risk perception, 71probability, element of risk

analysis, 177, 181, 184-186probability neglect, 86-87protective measures, 8-9public-private partnerships, 9-10

Q–RRANET project, 118rational choice theory, 67rational thought patterns, 67reasoning methods, 66-67Red Cross, earthquakes,

China, 16REDD (reduced emissions from

deforestation and forestdegradation), 175

regulators, financial institutions,162-163

reinsurance, 10-11remediation neglect, 90-91, 97resiliency, 11-13risk analysis

consequences, 177, 181, 184-186history, 178-180probability, 177, 181, 184-186scenario, 177, 181, 185-186terrorism risk analysis lessons

for natural/technologicaldisasters, 186-188

from natural/technologicaldisasters, 181-186

328 INDEX

risk assessmentatmospheric and hydrological

scientists, 44-45challenges, 78-79early-warning systems


cost responsibilities, 107-114high-probability events,


101-106, 114-119financial crisis, risk

identification/control, 164-165Geographic Information Systems

(GIS) software, 3heat waves, 45-48IPCC (Intergovernmental Panel

on Climate Change)extreme weather events,

49-51heat waves, 50-51terminology, 48-49

methods of 1800s, 3process model

catastrophe uncertainties, 4-5

expert forecast conflicts, 4hazard, 3-5, 15inventory, 3-4loss, 3-5, 15vulnerability, 3-4

weather eventscyclones, 54-56, 59-60forest fires, 61NMHSs (National

Meteorological andHydrological Services), 52-54

probability of occurrenceand impact, 42-44

risk-avoidance strategies, 127-128risk culture, 72-73risk forecasting, 8. See also

weather-risk forecastingcatastrophe uncertainties, 13

risk homeostasis, 73-74risk-management strategies, 8,

10-13challenges, 78-79financial crisis

capital requirements, 165-166

courage restoration, 168-169government and private

investments, 166-168Global Agenda Councils,

314-316global scope, 15government jurisdictions, 33-36information, communicating, 8interdependencies, 13-14investment portfolio, 29-36leadership development, 16-17,

79-82leadership qualities, 267-268NSEM 1.0 (national system for

emergency management),China, 191

SARS and NSEMweaknesses, 191-196

Yangzi River flooding, 191NSEM 2.0 (national system for

emergency management), Chinaafter SARS, 197Emergency Response

Law, 205nationwide contingency

plans, 199-202new challenges, 206-207new institutional structure,

197-199

INDEX 329

NSEM 3.0 issues, 208-210response mechanism

improvements, 202-205overcoming inequalities, 15timely actions, 37-39weather events, NMHSs

(National Meteorological andHydrological Services), 42-44

risk perceptionscognitive biases, 70-71group behavior, 71-72neuroeconomics, 74-78patterns, 78psychological and emotional

factors, 6-8, 14-15risk-recovery strategies, 136risk-reduction strategies, 128-131

catastrophic accidentsorganizational attitudes,

237-239organizational

interdependencies,245-247

research needed, 248leadership qualities, 266long-term insurance, 243-245long-term loans and long-term

insurance, 242-243natural disasters, impact on

economies, 239property owner viewpoint,

236-237, 240-241risk regulation, 123-124

central-local governmentrelations, 133-135

corruption in government, 135cultural influences, 133developing countries, 133information’s importance,

125-127

lessons, 135-138recommendations, 135-138

risk-related decisionsEU (expected utility) theory,

83-85neglects, 85

consequence neglect, 86-88external risk neglect, 86,

91-97probability neglect, 86-87solution neglect, 86, 90-91statistical neglect, 86-89, 97

risk-sharing strategies, 131-133risk tolerance, 72-73risks. See high-probability

risks/events; low-probabilityrisks/events

SSARS (Severe Acute Respiratory

Syndrome)NSEM 1.0 weaknesses, 191-193

communication/coordinationbreakdown, 194-195

public communicationinadequate, 195-196

slow response to SARS, 193-194

NSEM 2.0, 197scenario, element of risk analysis,

177, 181, 185-186Severe Acute Respiratory

Syndrome. See SARSSidr (cyclone), 104Society for Risk Analysis, 180solution neglect, 86, 90-91Somalia, early-warning systems,

105-106Southeast Asia, flooding, 109

330 INDEX

sports federations, catastrophebonds, 150

St. Louis, Missouri, flooding, 91State Council of China

Emergency Response Law, 202-205

EMO (Emergency ManagementOffice), 198

Master Plan, 199-202public incident management,

198-199statistical neglect, 86-89, 97status quo bias, 90stock market, 2009 crash, 2Summitville Mine in Colorado,

95-97sustainability, 11-13swine flu, 89Switzerland, heat waves, 47-48

TTanzania, early-warning systems,

105-106TCIP (Turkish Catastrophe

Insurance Pool), 242-243technological disasters, risk

analysis lessonsfor terrorism risk analysis,

181-186from terrorism risk analysis,

186-188temperature change

global warming, 171-176Greenhouse effect, 170

terrorismcatastrophe bonds, 150Pan American flight 103, 14

risk analysis lessonsfor natural/technological

disasters, 186-188from natural/technological

disasters, 181-186World Trade Center, (September

11, 2001), 7, 14, 180thought patterns (humans), 66-69tornadoes, risk analysis, 180tsunamis, 112

December 2004, 1, 15early-warning systems

Indian Ocean, 104-106, 116Mediterranean Sea, 106Pacific Ocean, 105

tuberculosis, 212Turkish Catastrophe Insurance

Pool (TCIP), 242-2432009 Global Assessment Report

on Disaster Risk Reduction, 121

U–VUnited Nations

Framework Convention onClimate Change, 174-175

International Strategy forDisaster Reduction, 137

REDD (reduced emissions fromdeforestation and forestdegradation), 175

2009 Global Assessment Report on Disaster RiskReduction, 121

United Statesabandoned mines, 95-97Department of Defense

Army Corps of Engineers, 33

INDEX 331

budgetary bargaining withPentagon and WhiteHouse, 36

Department of HomelandSecurity, 180

financial catastrophes, 2, 72financial crisis

capital requirements, 165-166

courage restoration, 168-169global considerations,

158-161government and private

investments, 166-168government responses,

163-164local considerations,

161-163risk analysis, 187risk identification/control,

164-165financial interdependence with

China, 159flooding, 33National Flood Insurance

Program, 243National Hurricane Center, 60National Weather Service, 57-60natural catastrophes, 2, 91World Trade Center, September

11, 2001 catastrophe, 7, 14, 180unnatural catastrophes

hazard/loss time periodextension, 5, 15

uncertainties, 4-5, 13

Ventura County, Californiawildfires, 38

virgin risks, 87-88volcano eruptions, 180vulnerability, risk-assessment

process model, 3-4

W–Zwarning systems

climate change effects, 106-107cost responsibilities, 107

community, 110-114global, 108regional, 109-110state, 110

developing countrieshigh-probability events,


105-106, 114-119WASH 1400 report, 178-180weather events

cyclones, 54-56, 59-60forest fires, 61heat waves, 45-48

Adelaide, Australia, 46-47IPCC’s Working Group II

predictions, 50-51Western Europe, 47-48

IPCC (Intergovernmental Panelon Climate Change)

extreme events, 49-51terminology, 48-49

NMHSs (NationalMeteorological andHydrological Services), 42-44,52-54

cyclones, 54-56, 59-60forest fires, 61

332 INDEX

probability of occurrence andimpact, 42-44

risk assessment, 52-54risk management, 42-44

weather-risk forecasting,uncertainties, 41. See also riskforecasting

Western Europe, heat waves, 47-48

wildfiresAustralia, 62California, 38firefighting crisis leadership,

263-266WMO (World Meteorological

Organization)coordination with NMHSs,

54, 60qualifiers expressing

uncertainties, 41World Economic Forum

Global Agenda Councils, 314-316

World Food Program, 152-153World Meteorological

Organization (WMO)coordination with NMHSs,

54, 60qualifiers expressing

uncertainties, 41World Trade Center, September

11, 2001 catastrophe, 7, 14, 180

Yangzi River, China, flooding1998, 191

zoonotic diseases, 224-226

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