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 LivelihoodNumber of people affected

Flood (31’395,654)

Cyclone(11’633,140)

Drought(3’408,999)

Rains (3’776,359)

Patterns: floodsTotal number of Victims and Affected by Floods in Orissa

Pattern: EpidemicsPeople 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 SeasonalSeasonal 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