Socio- Vulnerability Index for Risk Analysis Mohsen Ghafory-Ashtiany Affiliated Faculty: Disaster Management Research Institute of Shakhes Pajooh Professor: International Institute of Earthquake Engineering and Seismology President: Iranian Earthquake Engineering Association Chairman: Strong Ground Motion, Hazard and Risk Commission of IASPEI Bijan Khazaie Karlsruhe University, Germany Global Risk Forum, IDRC 2014 Davos, Switzerland 24-28 August 2014 Integrated Earthquake Risk Assessment RISK = Hazard x Vulnerability x Socio- Value Resilience Sustainable Development Safety and Security Creating Incentive for Risk Reduction and Risk Transfer Providing Resilience to the Society and Individuals 1
Urban Earthquake Risk Index Urban System Buildings Lifeline Policy Population Facilities Resilience Architecture Roads Land Use Distribution Medical Centers Governance Structure Water Occupancy Density Rescue Health Non- Structural Gas Construction Code and Practice Income Open Space Economy Utilities Electricity Growth Culture Communication Preparedness Contribution of Urban Earthquake Risk Factors Human Exposure Hazard Physical Exposure Disaster Management 2
Socio- Losses from Disasters Direct material losses: Property, Infrastructure, Lifelines, Livestock, Critical facilities,.. Human Losses: Death, Injury, Population displacement, Long term trauma, Environmental Losses: Deforestation, Hazardous material release, Weakening of Institutions and Disturbance of Social Structures- Security Reduction of and Human Potential of Society: Exacerbated Poverty, Impaired Small Business And Industry, Disabled Lifelines and Infrastructure. Diversion of Funds From Development and From Social Services. Disaster Losses Physical Damage Built Environment Human Direct Losses: Structural Capital Human Capital Residential Capital Fixed Capital Stock Natural Habitats InDirect: Tangible Business interruption Human Displacement InDirect: Intangible Phsycological Impact Social Mental Procedures for Casualty Estimation Hazard Population Distribution (towards: Spatio-Temporal Inventory) Building Damage Mapping (Damage Distribution) (towards: Building Specific Damage Grades) Algorithm (Regional towards Country Specific) 3
Common Procedures for Casualty Estimation ATC-13 Casualty Rates (Estimation factors provided for US) Building Specific Damages Common Procedures for Casualty Estimation HAZUS-MH Methodology based on EVENT TREE (Source:HAZUZ-MH) 4
Common Procedures for Casualty Estimation RISK-UE Method Italy data (Brameini et al. 1995) Effects of Damage Grades on Built Environment Common Procedures for Casualty Estimation Coburn and Spence Method (1992) A Global Model Based on Masonry and RC Building and Human Loss Data Ks: Fatalities due to Structural Damage Ksb = TCb * [M1 * M2 * M3 (M4 + M5 (1 - M4))] TCb: Tot Number of Collapsed Buildings (type b) M1: Population per building factor (regional factor) M2: Occupancy at time of day factor M3: Trapped under Collapsed buildings factor M4: Different Injury levels of Trapped (tabulated values) M5: Change of Injury levels of Trapped (tabulated values) 5
Iran Damage and Casualty Estimation Aggregated Damage Distribution Casualty Map (Severely Injured and Death) 2475 years return period and VS: 300 m/s (Soil) Damage Grades D3 D5 D4 & D5 Damaged Housing Units 3515187 2932976 6458107 Severity S4 S3 & S4 Human Loss 1718899 3975164 Mashhad Damage and Casualty Estimation T R =475 Yrs Building Type Count (%) Expected Building Damage % For: 475 yrs 2475 yrs Scenario Eq Adobe 1.4 48-59 70-79 58-63 Masonry 28.8 29-37 68-76 39-46 RC Half Skeleton ~ 0.0 15-20 46-52 20-26 Steel Half Skeleton 31.6 15-20 46-52 20-26 T R =475 Yrs RC 0.2 4-6 19-25 7-10 Steel 17.7 9-11 24-30 10-12 Expected Fatality = 40,000 people 6
GEM-EMME Casualty Estimation SOCIO-ECONOMIC DATABASE In socio-economic analysis; various factors such as: land use planning, public awareness, governance, population growth and its density, migration, resilience, resource allocation, wealth or poverty, social behavior, etc. can lead to adverse consequences of natural disaster. Socio- Vulnerability Database at National Level Hazard Resilience: Health, Education Governance Infrastructure and Economy Socio Index Population and Human Influence Land use Vulnerability of Built Environment Land Use Population Human influence 7
GEM-EMME Casualty Estimation Development of comprehensive, spatially enabled databases representing social and economic vulnerability indices at the national and city level in coordination with GEM-SE module; Around 1500 reported socio-economic variables that can affect the human and economic losses; Classification of variables according to a broad range of parameters concerning Hazard to Resilience; Collection, harmonization, development, and analysis of the available data sets or databases at city and national level. GEM-EMME Casualty Estimation To assess the socio-economic effects, the following steps are considered in conjunction with other EMME working packages: Collection of available data related to socio-economic indicators in the region for analysis. Quality assessment of the collected data; Socio- Database Statistical Approach Expert Opinion Approach Correlations s Completeness Consultation Pre-PCA data Processing Principal Components Analysis Social and Vulnerability Database Overview of the steps towards the creation of the parsimonious Social and Vulnerability Database 8
Socio- Vulnerability Database at National Level Data Quality Assessment: Achieving data confidence is a main objective of this work and should be made by applying following quality control and assurance measures: Relevance, Is the indicator relevant? Completeness, How complete is the data? Consistency, When was the data collected? Cross-Correlation, Does it add new information? Socio- Database Statistical Approach Expert Opinion Approach Correlations s Completeness Consultation Pre-PCA data Processing Principal Components Analysis Social and Vulnerability Database Christopher Power, James Daniell, Bijan Khazai, Christopher Burton, Christoph Oberacker 9