World Congres on Disaster Management New Delhi

Generation of Historical Vulnerability Indices using a DesInventar Database Sujit Mohanty Manager-Disaster Information Systems World Congress on Disaster Management New Delhi

Introduction
Concept
The InDisData project
Methodology and Tool - DesInventar
The Orissa Experience
Qualitative results

in·dex (în¹dèks´) noun
plural in·dex·es or in·di·ces (-dî-sêz´)
a. Something that serves to guide, point out, or
otherwise facilitate reference…
b. A number derived from a formula, used
to characterize a set of data…
Excerpted from The American Heritage« Dictionary of the English Language, Third Edition ® 1996 by Houghton Mifflin Company ..

Historical Vulnerability
Patterns : repeated periodic occurrence of losses
Trends : increasing magnitude of losses
Impact : high losses being caused by low magnitude events
Will be defined and calculated based on:

The InDisData Project
A database of disasters to understand trends and patterns.
A systematic geo-referenced inventory of small, medium and large-scale disasters for past 30 years.
To rationalize decision making for disaster preparedness, as well as providing an objective base for vulnerability assessment and priority setting.
To support planning & policy decisions for disaster preparedness and mitigation.

Orissa Pilot Process
Data collected for 30 districts and 314 blocks from newspapers over a period of 32 years.
Data collected from media is compared with Government records.
Institutionalization with Government for sustainability.
Interpretation and analysis of the data shows new dimensions of risk & vulnerabilities of the State.
Orissa ‘Vulnerability Analysis Report’ is being prepared in association with ‘Center for Development Studies’.

DesInventar
A methodology
A tool
The previous experience in Latin America
http://www.desinventar.org

DesInventar
Methodology
Disaggregation of the effects
Geo-referenced data
Inclusion of Small and Medium Disasters

DesInventar The Software Tools Stand-alone and Web-enabled version

Preliminary Findings
Epidemics and cyclones are the greatest causes of deaths
Epidemics are highly associated with floods, but also occur as independent incidents.
Fire is the greatest cause of household destruction, comparable to Cyclone.
Floods affect people more than any other type of disaster.

Impact on Life Number of people killed in disasters in Orisa Epidemics (19,963 ) Cyclone (20,449)

Impact on Property Number of Houses Destroyed in Disasters Orissa Fire (436,212) Cyclone (376,285) Floods (135485)

Impact on Livelihood Number of people affected Flood ( 31’395,654) Cyclone(11’633,140) Drought(3’408,999) Rains (3’776,359)

Patterns: floods Total number of Victims and Affected by Floods in Orissa

Pattern: Epidemics People Killed by Epidemics in Orissa

Spatial Distribution of Disasters

Relation Floods-Epidemics Number of reports of floods and people killed by epidemics, 11 years, with apparently non-flood related epidemics.

Spatial Distribution of Floods and Epidemics

Relation Floods-Epidemics Number of reports in floods and people killed by epidemics, 11 years, in 5 less-flood prone districts. Districts of Koraput, Kandhamal, Kalahand, Rayadada and Gajapat

Trend: Epidemics Ascending trend of the effects of epidemics in Orissa.

Trend: Fire effects on Housing

Pattern: Fire Seasonal Seasonal Variation in Fire Pattern

Way forward:
Definition of a methodology to generate a numeric index based on trends, patterns and impact
Calculation of these indices for Orissa
Comparison of these indices against other vulnerability index
Fine tuning of the whole process
Use of the indices in Risk Assessment

InDisData is supported by: Ministry of Home Affairs National Institute of Disaster Management NIDM United Nations Development Programme UNDP The Network for Social Studies on Disaster Prevention in Latin America

THANK YOU

World Congres on Disaster Management New Delhi

by Sujit Mohanty on Feb 18, 2009

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