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Current status and Best Practices for Disaster Loss Data recording in EU Member States

2 13 January 2015

Contributors

Country

1 Austria

2 Belgium

3 Bulgaria

4 Croatia

5 France

6 Germany

7 Greece

8 Italy

9 Netherlands

10 Portugal

11 Romania

12 Slovenia

13 Spain

14 Sweden

15 United

Kingdom

WHY DO WE NEED LOSS DATA ?

3 13 January 2015

27-28 July 2013

Hailstorm

Germany

Source: SIGMA 1/2014

Natural catastrophes and man-made disasters 2013

4 13 January 2015

APPLICATION AREAS

Compensation Accounting

Forensics Risk modeling

LOSS DATA

Avoiding sovereign insolvency

Balance prevention budget and loss

compensation

Fair and efficient solidarity mechanism and/or insurance market

Evaluate prevention measures Improve prevention policy

Accurate risk assessment based on

locally relevant loss exceedance curves

5 13 January 2015

International

level

European Level

National level

Post-2015 Framework for Disaster Risk Reduction

National process involving a number of stakeholders: decision makers, scientists, practioners…

Strong legal basis: EUSF, Green paper on Insurance, Floods & INSPIRE Directives...

LOSS DATA SERVING SEVERAL PURPOSES

6 13 January 2015

AT THE NATIONAL LEVEL

7 13 January 2015

AT THE EUROPEAN LEVEL

STRONG LEGAL BASIS

• Solidarity clause of the European Treaty • European Union Solidarity Fund • Council conclusions: Further Developing

Risk Assessment for Disaster Management • Revised Union civil protection legislation • Floods and INSPIRE Directives • Green Paper on Insurance of Natural and

Man-made Disasters • EU Strategy on adaptation to climate

change • ….

8 13 January 2015

MINIMUM REQUIREMENTS FOR LOSS DATA SHARING

9 13 January 2015

ANALYSIS FRAMEWORK

Conceptual loss data model

10

13 January 2015

Event ID

Hazard event identification

Affected elements

Loss indicators

Version

Metadata

Directly affected

population

Direct damages/

losses

Aggregated loss data

Killed

Missing

Evacuated

Direct economic loss

Sector

Owner

Location

Population

Occupancy

Event classification

Year

Location

Comparative analysis

11 13 January 2015

Purpose of loss databases

Application areas

12 13 January 2015

Comparative analysis

13 13 January 2015

Methodology of recording

Comparative analysis

14 13 January 2015

Main findings

• 12 out of 15 participating Member States have established and maintained a loss database,

• Large differences in the processes of loss data collection and recording,

• Lack of standards (e.g. for human and economic losses) that prevent aggregation at EU or global levels,

• Differences in IT systems,

• Differences in terminologies for peril classification,

• Drivers for loss data recording mainly linked to:

i) (semi) public national compensation schemes, ii) existing national and EU legislations and iii) for improving prevention and response mechanisms.

Gaps and aspirations

13 January 2015

Need for national and European legal frameworks:

Austria, Belgium, Bulgaria, Romania, Slovenia, Spain and Sweden

have binding legislation.

Public Private Partnership (PPP) or Public Public

partnership (PuP)

Mission Risques Naturels in France is a PPP (and to a certain extent a PuP) and an example of a good practice, reinforcing the insurance strategic role in disaster loss recording and data sharing.

Standardization/Classification

16 13 January 2015

Agreed Terminologies/Definitions

Family Main event Peril

Earthquake Ash Fall

Mass Movement Fire following EQ

Volcanic Activity Ground Movement

Landslide following EQ

Lahar

Lava Flow

Liquefaction

Pyroclastic Flow

Tsunami

Flood Avalanche: Snow, Debris

Landslide Coastal Flood

Wave Action Coastal Erosion

Debris/Mud Flow/Rockfall

Expansive Soil

Flash Flood

Ice Jam Flood

Riverine Flood

Rogue Wave

Seiche

Sinkhole

Convective Storm Cold Wave

Extratropical Storm Derecho

Extreme Temperature Frost/Freeze

Fog Hail

Tropical Cyclone Heat Wave

Lightning

Rain

Sandstorm/Dust storm

Snow/Ice

Storm Surge

Tornado

Wind

Winter Storm/Blizzard

Drought Forest Fire

Glacial Lake Outburst Land fire: Brush, Bush, Pasture

Wildfire Subsidence

Animal Incident Bacterial Disease

Disease Fungal Disease

Insect Infestation Parasitic Disease

Prion Disease

Viral Disease

Impact Airburst

Space Weather Collision

Energetic Particles

Geomagnetic Storm

Radio Disturbance

Shockwave

Climatological

Biological

Extraterrestrial

Geophysical

Hydrological

Meteorological

IRDR peril classification: unified terminology - for events classification - for operating loss databases

MAIN EVENT: A minimum requirement for shared loss data

Gaps and aspirations

17 13 January 2015

Data Collection/Recording Methodologies

• Systematic approach for recording loss data, • Assessment forms tailored to the type of damage and customized

by sector, • Staff training, • Strict division of duties, • Clear documentation, • Use of new technologies for damage assessments : Remote Sensing data mobile mapping crowd-sourcing, etc. (Ajmar et al., 2010)

Gaps and aspirations

18 13 January 2015

Framework For Human Impact Loss Indicators

Need for clear and unambiguous definitions for human losses

Main fields Definitions

Killed

Missing

Injured/disease/in need of medical assistance

EARLY WARNING RESPONSE CAPACITY RECOVERY

Pre-event Sheltered by emergency services Permanently homeless

Post-event Sheltered by private arrangements Temporarily homeless

Relocated Not homeless

Without shelter

Isolated

Incr

easi

ng p

rior

ity

of n

eeds

DIR

ECTL

Y A

FFEC

TED

prim

ary

leve

l by

ECLA

C

IND

IREC

TLY

AFF

ECTE

D

Evacuated

People that are removed from

a place of danger to a safer

place. Breaking down that field

is related to the management

of different disaster phases.

People that suffer physical damage of infrastructure which threatens their basic livelihood conditions (limited access

to water, food, electricity, ….) but they have not been evacuated

PEO

PLE

IN N

EED

Tertiary level - outside affected area (by ECLAC)

Fatalities

Victims

Secondary level - within affected area (by ECLAC)

Breaking down the fields

(general options: by gender, by age, by vulnerable groups, ...)

People that are in need of immediate medical assistance as a direct result of the disaster

People that suffer of a disaster's indirect effects (e.g., loss of flow, deficiencies in public service)

People that suffer physical damage of their property but are not in need

Total mortality

1. level 2. level 3. level

Similar to direct and indirect losses (ECLAC)

• Rule of priority of needs • Temporal component

Specific requirements of different disaster stages

… of disaggregation

Dis

ag

greg

ati

on

/

su

mm

ati

on

Gaps and aspirations

19

Framework For Damage/Economic Loss Indicators

Direct tangible losses in national currency

Tangible Intangible

Direct

loss/damage

Physical damage to property

converted to monetary value

People

directly affected

Cultural heritage

Natural environment

Indirect loss Loss of flow People

indirectly affected

Loss of future usage

(agriculture, forestry, tourism, ...)

Total loss Economic loss Affected people Economic loss/number-size of

assets

Common

denominator Monetary value Number of persons -

EC

LA

C

Direct losses

Gaps and aspirations

Uncertainty Handling

0

1

2

3

4

5Measurement

Disagreement

Human errorCrediblity 1

Crediblity 2

Average Pedigree score = 3.6

For each step of the process: 1- Data collection methodology 2- Data recording methodology

DETAILS IN PRESENTATION: Xavier Romão, Esmeralda Paupério

Gaps and aspirations

21 13 January 2015

Guidelines

Loss data sharing among Member States and with the EU

• Publicly accessible and interoperable national loss databases are encouraged to allow for easy data exchange and information sharing between different systems (e.g. the Shared Environmental Information System (SEIS), EU open data portal)

• For better understanding the trans-boundary effects of disasters • For a better comparison of progress towards increased resilience

across countries • For a common EU framework that allows monitoring of progress

in the Post-2015 Framework for DRR

22 13 January 2015

Data model

Loss

accou

nti

ng

Data

-sh

arin

g

HFA

-2

DesIn

ven

tar

Hazard event identification

Geographical location

National unit (NUTS1)

Subnational units (NUTS2) To be

defined

by the

MS

Subnational units (NUTS3)

Lat/Lon (points, footprints)

Temporal information

Year

Duration (in days)

Month (beginning/ending)

Event type specific attributes

Severity key data

Reference to external

database

Hazard event ID

Hazard event classification

(Main

event)

Affected elements

Geographical location

Subnational units

Data model

Loss

accou

nti

ng

Data

-sh

arin

g

HFA

-2

DesIn

ven

tar

Loss Indicators

Directly affected population

Killed

Missing

Evacuated

Isolated Victims

Direct damage/loss

Physical damage

Direct economic loss

(Total

% of

GDP)

Sector

(Total)

Owner (private, business,

public, etc.)

(Total)

Who bears the loss

(Total)

Quality assurance

Sources

Data collection

methodology

Data recording

methodology

Guidelines Minimum Requirements

Guidelines

23 13 January 2015

Totals per ownership

Insurer

Individual

Business

NGO

Government

Totals over all sectors

sectors

Social sector • Residential

• Education/research

• Culture/recreation

• Health sector

• Public administration

Infrastructure • Energy

• Drinking water and sanitation

• Transport

• Communication

Economic sector • Agriculture/forestry

• Trade/industry

• Tourism

Other

• Clean-up costs

• Emergency relief costs

Possible divisions of sectors

Minimum requirements

For Loss data sharing

24 13 January 2015

RECOMMENDATIONS

Data collection at Local level

• Engage municipalities and civil protection

Building a process at National level

• Considering the best practices in Member States and the presented guidelines

Design of an advanced IT system

• Including a data model linked to other government databases

• Expand with GIS platforms

25 13 January 2015

RECOMMENDATIONS

Supporting legislation and active involvement of local governments

• Political commitment

• Dedicated budget for loss databases

Encouraging PuP and PPP

• Ensure participation and ownership of all stakeholders

Information sharing

• Data-sharing of summary or aggregated statistics

• Open and interoperable databases