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Table of Contents
Intro
Book_5125_C000
Half Title
Title Page
Copyright Page
Contents
Blue Ribbon Panel (In Alphabetical Order)
Authors (In Alphabetical Order)
Preface
Introduction
Book_5125_C001
Chapter 1 : Toward Community Resilience Assessment
1.1 Evolution of Community Resilience
1.2 Critical Infrastructure and Lifelines
1.3 Business and Household Systems
1.4 Community-Level Studies
1.5 Concluding Remarks and Future Directions
References
Book_5125_C002
Chapter 2 : Probabilistic Resilience Assessment of Critical Infrastructure Systems under Blast Risk
2.1 Introduction
2.2 Resilience Definitions
2.3 Variability in Blast Load and Structural Response
2.4 Probabilistic Risk Assessment of Blast Scenarios
2.5 Deterministic Resilience Assessment under Blast Risk
2.6 Probabilistic Resilience Assessment Under Blast Risk
2.7 Probabilistic Assessment of Blast Resilience: An Application
2.8 Best Practices
2.9 Conclusions
Bibliography
References
Book_5125_C003
Chapter 3 : Resilience and Recurrent Hazard: A Case Study of Healthcare Systems
3.1 Introduction
3.2 Resilience Assessment
3.2.1 Resilience in Health Systems
3.2.2 Resilience Quantification
Segment 1
3.3 Hazard Recurrence during Recovery
3.4 Resilience of Healthcare Systems: COVID-19
3.4.1 COVID-19 Data
3.4.2 Comparison of Different Countries' Resilience
3.4.2.1 Resilience-Daily New Infected Cases. Using the number of daily new infected cases as a performance indicator, we calculate the instantaneous resilience of the healthcare systems of the seven countries over time, as shown in Figure 3-5 . The
3.4.2.2 Resilience-Daily Deaths. Adopting the number of daily death cases and transferring it into a survival rate-related measure (specifically, ) as Indicator 2, we repeat the aforementioned approach to obtain the instantaneous and average
3.4.2.3 Resilience-Case Fatality Ratio. Following the same procedure as previously described, we obtain and compare the resilience of the seven countries over time ( Table 3-4 and Figures 3-9 and 3-10 ) by considering case fatality rate as the
3.4.3 Results
3.5 Conclusions
3.6 Recommendations
References
Book_5125_C004
Chapter 4 : Resilience of Transportation Infrastructure Systems to Climatic Extreme Events
4.1 Introduction
4.2 Definition of Resilience
4.3 Fundamentals of Network Science
4.4 New York City as an Example Network
Book_5125_C000
Half Title
Title Page
Copyright Page
Contents
Blue Ribbon Panel (In Alphabetical Order)
Authors (In Alphabetical Order)
Preface
Introduction
Book_5125_C001
Chapter 1 : Toward Community Resilience Assessment
1.1 Evolution of Community Resilience
1.2 Critical Infrastructure and Lifelines
1.3 Business and Household Systems
1.4 Community-Level Studies
1.5 Concluding Remarks and Future Directions
References
Book_5125_C002
Chapter 2 : Probabilistic Resilience Assessment of Critical Infrastructure Systems under Blast Risk
2.1 Introduction
2.2 Resilience Definitions
2.3 Variability in Blast Load and Structural Response
2.4 Probabilistic Risk Assessment of Blast Scenarios
2.5 Deterministic Resilience Assessment under Blast Risk
2.6 Probabilistic Resilience Assessment Under Blast Risk
2.7 Probabilistic Assessment of Blast Resilience: An Application
2.8 Best Practices
2.9 Conclusions
Bibliography
References
Book_5125_C003
Chapter 3 : Resilience and Recurrent Hazard: A Case Study of Healthcare Systems
3.1 Introduction
3.2 Resilience Assessment
3.2.1 Resilience in Health Systems
3.2.2 Resilience Quantification
Segment 1
3.3 Hazard Recurrence during Recovery
3.4 Resilience of Healthcare Systems: COVID-19
3.4.1 COVID-19 Data
3.4.2 Comparison of Different Countries' Resilience
3.4.2.1 Resilience-Daily New Infected Cases. Using the number of daily new infected cases as a performance indicator, we calculate the instantaneous resilience of the healthcare systems of the seven countries over time, as shown in Figure 3-5 . The
3.4.2.2 Resilience-Daily Deaths. Adopting the number of daily death cases and transferring it into a survival rate-related measure (specifically, ) as Indicator 2, we repeat the aforementioned approach to obtain the instantaneous and average
3.4.2.3 Resilience-Case Fatality Ratio. Following the same procedure as previously described, we obtain and compare the resilience of the seven countries over time ( Table 3-4 and Figures 3-9 and 3-10 ) by considering case fatality rate as the
3.4.3 Results
3.5 Conclusions
3.6 Recommendations
References
Book_5125_C004
Chapter 4 : Resilience of Transportation Infrastructure Systems to Climatic Extreme Events
4.1 Introduction
4.2 Definition of Resilience
4.3 Fundamentals of Network Science
4.4 New York City as an Example Network