Thirthy Years of Natural Disasters 1974-2003 the Numbers

8/9/2019 Thirthy Years of Natural Disasters 1974-2003 the Numbers

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Centre for Research

on the Epidemiology

of Disasters

THIRTY YEARS OF NATURAL DISASTERS

1974-2003: THE NUMBERS

D. Guha-Sapir

D. Hargitt

P. Hoyois


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THIRTY YEARS OF NATURA1974-2003: TH


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THIRTY YEARS OF NATURA1974-2003: TH


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Presses universitaires de Louvain, 2004

Registration of copyright: D/2004/9964/32

ISBN :2-930344-71-7


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Acknowledgements:

This report was made possible thanks to the unflagging encouragements by Margaret Arnold of the World Bank's Hazard Management Unit (Management Facility) and Kelly Sponberg of the U.S.National OceanograAgency's Climate Information Program (NOAA/CIP).The CRED team alsociation to Rhonda Davis, Harry Proctor and Nate Smith at the OfficAssistance (OFDA) who were suppor tive of this initiative from its early s

Funding for this report was made available by the Provention CManagement Facility, World Bank). Additional funds have been provideUSAID/OFDA.

This report has been prepared by:Rgina Below

David BrchetDebarati Guha-SapirDavid HargittPhilippe Hoyois

Consulting EditorDianna Rienstra,Phoenix Ink Communications - Brussels

Printed by:Jacoffset Printers Louvain-La-Neuve

Brussels,November 2004


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About CRED and our partners

The Centre for Research on the Epidemiology of Disasters (CRED) was at the School of Public Health of the Universit catholique de Louvain (

with international status under Belgian law.In 1980,CRED became a WorCollaborating Centre as part of WHOs Global Programme for Emergen

Since then, CRED has increased its international network substantiallynumerous UN agencies,inter-government and governmental institutions,nas well as several research institutes and universities.

The goalsWith a special focus on public health,epi-demiology, structural and socioeconomicissues, CRED promotes research, training,information dissemination and technicalservices on disasters and other humanitar-ian emergencies. It aims to enhance the

effectiveness of developing countries' dis-aster management and prevention capabil-ities as well as fostering policy orientedresearch.

The scope

CRED's activities focus on all emergency

situations with a major human impact.Thisincludes all types of sudden, natural orman-made catastrophes, such as hurri-canes, earthquakes and industrial acci-dents,and longer-term disasters and com-plex emergencies, such as famines andarmed conflicts. CRED focuses primarily

on the public health and sanitary aspectsof mass disasters, as well as on theirsocioeconomic and developmental effects.However,disaster preparedness,mitigationand prevention for vulnerable populationsi i i hi h fil

Some of CREDs partners

International Agencies

World Health Organization (WH

United Nations Office for the C

(UN/OCHA)

United Nations Inter-Agency Secr

Disaster Reduction (UN/ISDR)

United Nations High Commission

World Bank Hazard Management

United Nations Children's Fund (U

Inter-Governmental and Governm

European Union

United States Government

Belgian Government Directio

Internationale (DGCI)

Non-Governmental Organizations

International Federation of Red Cro

Save the Children - UK (SCF/UK)

Mdecins Sans Frontires (MSF)

ASEAN Committee on Disaster MAsian Disaster Reduction Center

Universities and Research Institute

St. Luc Hospital Departments of

Belgium


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Table of contents

A look behind the numbers

Disaster data handle with care

Disasters have evolved over time

W here do disasters occur?

How are people affected by disasters?

The inextr icable link between poverty and disasters

Tallying the costs

EpidemicsDonors prefer certain types of disasters

Looking to the future

Annex 1: disaster maps

Annex 2:statistical tables


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A look behind the numbers

Today, the world is facing disasters on an unprece-dented scale: more than 255 million people were

affected by natural disasters globally each year, onaverage,between 1994 and 2003,with a range of 68million to 618 million.During the same period,thesedisasters claimed an average of 58,000 lives annually,with a range of 10,000 to 123,000.In the year 2003,1 in 25 people worldwide was affected by naturaldisasters.

During the last decade disasters caused damage of anestimated US$67 billion per year on average, with amaximum of US$230 billion and a minimum ofUS$28 billion.The economic cost associated with nat-ural disasters has increased 14-fold since the 1950s.

Scientific predictions and evidence indicates thatglobal climate change will increase the number ofextreme events,creating more frequent and intensi-fied natural hazards such as floods and windstorms.Population growth, urbanization and the inability ofpoor populations to escape from the vicious cycle ofpoverty makes it all the more likely that there will be

an increase in the number of people who are vul-nerable to natural hazards,with a resulting increaseof natural disasters and environmental emergencies.

Relief tops funding

Most decision makers agree that the integration of

disaster preparedness, mitigation and preventionmeasures into policy development is key to reducingthe vulnerability of human populations to naturalhazards.Yet funding patterns,an undeniable indicatorof real priorities, show that it is disaster relief not

people and comand multiple de

Finally,the realimers often nereduction due analyses of trenlittle demand reliable and s

assess their sshort term andAs a result, disappear costly.

An ad hoc respo

The need for systtion and preventioof both developmagencies.Until receon an ad hoc basistime of the emerincomplete, outdat

reasons. Generallyquickly for fundraismount. As a resulinformation suffers

Public sector agencthemselves to p

Calculations of riskwere a lower prioapproach to disastreactive,focusing onand reconstruction


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in Turkey,Iran and India.All of these events divert-ed development funds towards reconstruction.

These events resulted in an increased demandfrom policy makers and development planners fordata on disasters, their impact and frequency.Accurate data that are comparable across coun-tries and consistent over time are in demand andare required for priority setting between compet-ing demands for national and international budgetallocations.

The harsh reality behind the statistics

Based on the data in CREDs EM-DAT database,between 1974 and 2003 there were 6,367 naturaldisasters,not counting epidemics.This resulted in thereported deaths of slightly more than 2 million indi-

viduals, about 5.1 billion people being cumulativelyaffected, 182 million persons made homeless andestimated reported damages of US$1.38 trillion.Only in the last decade, 86% of all disaster-relateddeaths were caused by natural hazards, with just14% resulting from technological disasters such astransport or industrial accidents.Asia alone suffered

75% of the deaths from natural disasters.

These figures may seem very high, but they areprobably underestimates. For example, droughtsreportedly killed 500,367 people in Ethiopia overthe last three decades.But some estimate that thenumber of people who died from the great

Ethiopian drought of 1984-1985 alone may havenumbered between 600,000 and 1 million. Evenworse is the case of economic damages,where notmore than a third of reported disasters estimateeconomic losses.

The devastating impacbehaviour

Natural disasters are often pgod,with little causal relatioThis may be true for someearthquakes and volcanoes,a disaster is based on a humof lives lost or homes destro

Over the last 50 years, thbody of evidence pointingbehaviour on the global natthe possibility that certain tsuch as floods, may be incrquence of human activity.

The purpose of this publianalyse the occurrence and ural disasters over the last data quality and coverage hWhile the EM-DAT databasbers at this scale provide sato appreciate the directionimpact of different disasters

The report begins with anand its reporting and takesdisasters have evolved ovoccur most frequently. It eaffected by different types dand draws links between disasters.In tallying the costimportant conclusions aboupoor and vulnerable as cotions with a higher income.It warns about the need toresponse to infectious dis


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Disaster data handle with care!

Data on disaster occurrence, their effect uponpeople and cost to countries remain at best

patchy. No single institution has taken on the roleof prime provider of verified data.The data in EM-DAT (see Box What is EM-DAT) is culled from avariety of public sources, including repor ts by gov-ernments,insurance companies,press agencies andaid agencies.The original information is not specif-ically gathered for statistical purposes and

inevitably, even though CRED applies strict defini-tions for disaster events and parameters, the orig-inal suppliers of the information may not.The fig-ures should be regarded as indicative.As a result,relative changes and trends can be more useful tolook at than absolute, isolated figures.

compilation of datdata came from va

agencies, 27% frofrom United Natipress agencies andhumanitarian organ

Information systemlast 30 years and s

ly available. Howestandardized data revealing itself as aplanning.Despite ethe quality of disagood as the repo

Reporting sources of EM-DAT natural disasters: 1974 -

0

50

100

150

200

250

300

350

400

450

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

199 5

Number ofreported

natural disasters

Insurance companies

Humanitarian & disaster agencies

Governments

Figure 1


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W hat is EM-DAT?

The EM-DAT database presents core data on the occurrence and effects of over 14,500 disasters from Natural disasters

Technological disasters

Disasters in EM-DAT are defined as:

A situation or event which overwhelms local capacity,necessitating a request to the national or internattance,or is recognized as such by a multilateral agency or by at least two sources,such as national,regiongroups and the media.

Criteria

For a disaster to be entered into the database at least one or a combination of the following criteria mu

10 or more people reported killed 100 people or more reported affected A declaration of a state of emergency A call for international assistance

Content

EM-DAT includes the following fields:

DISNO: A unique disaster number for each disaster event (8 digits:4 digits for the year and 4 digits foexample,19950324).

Country: Country(ies) in which the disaster occurred.

Disaster group:Two groups of disasters are distinguished in EM-DAT natural disasters and techno

Disaster type and subset: Descript ion of the disaster according to a pre-defined classification.Foand subset: Cyclone or type: Transport; and subset: Rail.

Date (start and end):The date when the disaster occurred and ended. (Month/Day/Year.)

Killed: Persons confirmed dead and persons missing and presumed dead.

Injured: People suffering from physical injuries, trauma or an illness requiring immediate medical treadisaster.

Homeless: People needing immediate assistance for shelter.

Affected: People requiring immediate assistance during a period of emergency;it can also include dis

Total affected: Sum of injured, homeless and affected.

Estimated damage S l i tit t i h d l d th d l i t tif th l


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Key problem areas

Key problems with disaster data include a lack ofstandardized collection methodologies and defi-nitions. Furthermore, ambiguities exist regardingthe intent behind the reporting of the data, theloose definition of people affected, the datesreported and changing national boundaries.

Data can be biased because of the rationalebehind data gathering. Reinsurance companies,

for instance,systematically gather data on disasteroccurrence to assess insurance risk,but principal-ly in areas of the world where disaster insuranceis widespread. As a result, their data may omitpoorer disaster-affected regions where insuranceis unaffordable or unavailable.Yet populations inthese regions are some of the most heavily affect-

ed by disasters.

Dates can be a source of ambiguity.The date of an earthquake is easy to determine,but that of a famine is much harder to define famines do not occur on a single day.Similarly,adrought can occur over many years and entering

it into EM-DAT as such creates several entries,while in reality it is one prolonged disaster.Whenconfronted with this situation, the date on whichthe appropriate body has declared an officialemergency has been used.

Data on the number of people affected by a dis-

aster can provide some of the most potentiallyuseful figures for planning both disaster pre-paredness and response, yet these are alsoamong the most loosely repor ted figures. Thedefinition of affected is open to interpreta-i li i l h i C i i

operation is over death can be veriDAT's sources acously reported nurospective annual two and sometimeFor this reason, Ereviewed and ubecomes availablecal towards improvgies and enhancing

tion and general p

For example, for Iran,the first figuresaster mentioned akilled. Over the foincreased to more

the Iranian Govern26,796 deaths,mufeared.However,apublication,a figurepublished by a presbeen validated ansources.

The importance

An issue to keep indata is the very strrecorded. Each dievent, thus potent

sion of the relativgeographic locatiosurface area incurencing more disasttries. In addition, thl d h


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assessments. It is only recently that disaster datareporting at sub-national level has started improv-ing.However,there is still much work to be donein this field. It is still common of EM-DAT datasources to report geographically aggregated disas-ter impact data on deaths, people affected andeconomic damages, which makes analysis at sub-national level very difficult.

The reporting conundrum

As mentioned, the EM-DAT database is compiledfrom various sources, including UN and govern-mental agencies, non-governmental organizations,

insurance companies,reseagencies. CRED does havthese sources based on twe are dependent on sucwith trustworthy and comity of cases, a disaster wiEM-DAT if two or more soter's occurrence and its cothe number of people kille

Strict criteria must be mentered into the database.Taccess to this information aticular disaster was entered

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

1.

2.

3.

Table 1 - Proportion of essential disaster data reported by country:1974 - 200

All countries

Highest performances (1)

Guam

Tonga

Korea,Rep.

Dominica

Philippines

Thailand

Kazakhstan

Vietnam

Barbados

China

Lowest performances (2)

Luxembourg

Ireland

Gambia

% of disaster with

34.74

85.71

77.78

70.91

57.14

58.17

48.48

42.86

42.39

40.00

44.04

0.00

8.33

0.00

68.58

85.71

100.00

80.00

85.71

90.87

86.36

85.71

88.04

80.00

78.12

0.00

16.67

30.77

89.55

100.00

89.89

94.55

100.00

93.54

95.45

100.00

95.65

100.00

95.57

16.67

50.00

61.54

Deathsreported (3) Affectedreported Damagesreported


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killed or affected reached the appropriate threshold,

if there was a declaration of a state of emergency,

or if there was a request for international aid.

It is interesting to look at the different fields thatmake up the EM-DAT database and the propor-

tion of these for which information has been

actually repor ted and included. Deaths from dis-

asters are the factor that remains the quintessen-

tial aspect of a major crisis.As the data shows,it is

the characteristic most commonly reported. In

nearly 90% of all disasters, information on thenumber of deaths, including the absence of death,

was provided. Affected populations are alsoreported in more than two-thirds of the records.

The problems begin with economic losses.With

the exception of five countries,all other countries

have economic damages for disasters that are

repor ted in less than half of the cases.

Some of the most incomplete reporting comes

from the developed nations, in particular coun-

tries of Western Europe such as Austria, the

Netherlands, Ireland and Belgium.

Part of the problem in Western Europe is thefragmented jurisdiction over the different types of

disasters.Floods,windstorms or wildfires are man-

aged by different authorities such as the Ministry

of the Interior, the Ministry of Water and Forests

or the Ministry of Public Works.Disasters are also

often handled at provincial level, such as Landes

authorities in Germany or Departments in France.

Information is not always centralized at a national

level similar to the Federal Emergency

Management Authority in the US,which monitors

all major disasters in the country even if the

No internationa

Another reason fofrequently reporteddamage assessmenprovide estimates value that may nolevel of insurance sity of that commods for assessingdevelopment by tLatin America andexample, there isaccepted method tand across all disboth direct and ind


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Disasters have evolved over time

To better understand the evolution of disasteroccurrences over the last three decades it is impor-

tant to take a step back and look how disaster eventshave evolved over the span of the 20th century.

The last century

Since 1900, more than 9,000 natural disasters havebeen registered in EM-DAT. Of these, about 80%

have occurred over the last 30 years.Although thissounds like a dramatic increase, it should be viewedwith caution and with some understanding of thecomplexities between disaster occurrences and sta-tistical repor ting and registering.

One of the main contributors to this apparent

increase of natural disasters is the launch of activedata collection by the Office of US Foreign DisasterAssistance (OFDA) in 1960 and CRED in 1973.Thepunctual increases are indicated in Figure 2.

Figure 2 might lead one to believe that disastersoccur more frequently today than in the beginning of

the century. However, reaching such a conclusionbased only on this graph would be incorrect. In fact,

what the figure is really shthe registration of natural d

Over the past 30 years,devnications,media and increas

ation has played a critical rasters reported at an interincreases in humanitarian reporting of more disasters

that were previously manag

Another factor to consideEM-DAT data is the way because this influences toccurrences. Because disawith the country as the u

unit it can influence the nued in the database. For exin 1998 affected seven corecords in EM-DAT for oHowever,it is interesting t

tion of multi-country disadisasters has remained re

There has been about onefive single-country event

Occurrence of natural disasters as reported in EMDAT: 1900 - 2003

350

400

450

500

Figure 2


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century,affecting only slightly the general trend of

disaster occurrence as it appears in Figure 2.

Small disasters are increasingly reported

Another impor tant aspect is the increase in the

repor ting of small disasters compared to that of

large catastrophes.As the active data collection for

EM-DAT started in the late 1960s, the disasters

prior to that date were compiled retrospectively.

This resulted in a list that included mainly events of

major importance,as neither humanitarian aid nortelecommunications were particularly developed

and few organizations were interested in the com-

pilation of data on natural disasters. When active

registering of disasters took on a more impor tant

role, both the larger disasters were recorded,

together with increasingly more of the smaller ones.

Figure 3 shows the decrease in the relative pro-

por tion of large disasters over the last century.

Classification a controversial and

complex issue

The classification of disasters is a controversialand complex issue.A specific event can be cata-

strophic for an in

munity or for the s

egorizations also

impact,mor tality o

sidered as the de

For the purposes

disasters into cate

small.The thresho

distribution of freq

number of deaths,

damages,taking intdisasters, regions o

of the impact.The

example, is usually

of floods or winds

ters occur is also im

natural disasters i

than in developingimpact of disasters

also be incorpora

persons affected p

progressively over

The human impac

ered by CRED asdeaths was lower t

Proportion of large disasters over total reported natural disasters: 1900 -

70%

80%

90%

100%

Figure 3


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of people affected was lower than or equal to1,500,or the amount of reported economic dam-ages was lower than or equal to US$8 million,adjusted to 2003 dollars.

The human impact of a natural disaster was con-sidered large when the number of deaths wasgreater than or equal to 50, the number of peo-ple affected was greater than or equal to 150,000,or the amount of repor ted economic damageswas greater than or equal to US$200 million,adjusted to 2003 dollars.

By comparison,OFDA classifies a natural disaster asmajor if it causes more than 50 deaths and affectsmore than 100,000 people1.Sheehan and Hewitt2

use the term major disasters for those that kill orinjure more than 100 people and cause more than

US$1 million of property damage. Michaelis3

usesthe term accident when the number of deaths isbetween one and 999.The term disaster appliesto 1,000 to 1 million deaths, and catastropherefers to more than 1 million deaths.

The International Monetary Fund4 classifies a dis-

asters as large if it affected at least half a percentof a country's population or caused damages ofat least half a percent of the national GDP orresulted in more than one fatality per 10,000population.

The Insurance Service Office5, Inc.classifies a nat-

ural disaster as a catastrophe when the eventcauses US$25 million or more in insured proper-ty losses and affects a significant number of prop-erty/casualty policyholders and insurers.Alexander6 considers a threshold of US$5 millioni i b bl l d D b k 7 l ifi

is relatively safe to say thadisasters that occur today criteria are being reported

Shifts between disaste

Although there has beenmajor disasters, it is inteshifts between disaster cplays the polynomial trecentury of the four mainfloods and related disastedisasters,windstorms,and

Floods and related d(84%), landslides andavalanches (3%).

Windstorms include s(20%), cyclones (16%)ter storms (9%), tornastorms (4%).

Geological disasters

(83%), volcanic erupwaves (1%).

Droughts and relatdroughts (58%), extremand wildfires (21%).

Figure 4 shows an increasewith floods and droughts shincrease relative to geologstorms. This underscoreaddressing issues such asi l d h


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However,scientists debate the hypothesis that theoccurrence of earthquakes is not linked to

occurrences. Revieover a shorter tim

Worldwide polynomial time trends for the four major types of natural disas

0

20

40

60

80

100

120

140

160

180

1900

1903

1906

1909

1912

1915

1918

1921

1924

1927

1930

1933

1936

1939

1942

1945

1948

1951

1954

1957

1960

1963

1966

1969

1972

1975

Numbe

rofDisasters

Polynomial (f loods & related) Polynomial (droughts & related) Polynomial (windstorms)

Figure 4

The polynomial equations for time trends and R2 are as follows:

Floods and related disasters: y = 0.0005 x3 0.0523 x2 + 1.621

Droughts and related disasters: y = 0.0002 x3 0.0161 x2 + 0.415

Windstorms: y = 0.0154 x2 - 0.7778 x + 9.4657

Geological disasters: y = 0.0058 x2 - 0.3084 x + 6.058;R

Polynomials are a mathematical function used to make a curve that minia graph,smoothing and summarizing the overall trend of the series. Thesen according to the best R2 fit, which measures how successful the po

variation of the data (best fit:R2 = 1).


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The number of people affected has followed moreor less steadily the same pattern of increase as thenumber of disasters.Some disasters,such as floods

in particular, affect alarming propor tions of thepopulation living in the area. For example, theYangtze River floods in China in 1991 and 1998affected a total of 210 million and 238 million peo-ple respectively.The latter disaster forced China torequest international aid for the first time.

Although the number of affected has increasedover the last 30 years, the number of deaths hasdeclined.This was particularly true from 1974 to1979,when it reached less than half the level at thebeginning of that period. It would be encouraging

ib hi d i i

to the real effects of awaexpansion of disaster prepprevention.

A glimmer of hope

In recent years, internatiodisasters and their impacrisen closer to the top of da. For many years, resp

largely confined to emerterm life-saving actions.decades, the critical impoparedness, mitigation, prequate training of relief wo

i d

Polynomial trends in numbers of natural disasters,persons killed and persons affected: 1974 - 2003

0

100

200

300

400

500

600

700

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

200

number ofaffected

(x 1 million )

Number of deaths Number of affected Number of nat

Polynomial (Number of deaths) Polynomial (Number of affected) Polynomial (N

Figure 5

L d h d di d b


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Large donor programmes have dedicated substan-tial budget lines to disaster preparedness and pre-vention and have placed this issue higher on theagenda of development assistance.

Key players

The World BankThe Hazard Management Unit (HMU), formerly called the Disaster Management Facility,was e

to champion the integration of disaster prevention into development effor ts and to promote

emergencies.The unit serves as a central resource of hazard risk management knowledge for W

The HMU provides:

Technical support to World Bank operations.

Develops corporate strategy and policy analysis for hazard risk reduction. Generates knowledge through work with the World Bank Group and external partners.

Provides learning and training activit ies.

Effor ts have focused on such activit ies as documenting the longer-term economic impacts of d

for assessing damage and needs following a disaster,and conducting country-level analyses to

better manage disaster risk.

The US Agency for International Development (USAID) - Office of Fo

(OFDA)OFDAs Disaster Response and Mitigation division devises,coordinates and implements progrscience and technology to prevention, mitigation, and national and international preparedness

human-caused disaster situations.Their mitigation-related programs range from investing in dr

possibly head off a famine to training local relief workers to manage the response to a disaste

The ProVention Consort iumThe consor tium represents a global coalition of governments,international organizations,acade

civil society organizations dedicated to increasing the safety of vulnerable communities and to re

oping countries.Consortium members share knowledge and resources on disaster risk managebetween members.

The United Nations International Strategy for Disaster Reduction (ISD

This is the focal point in the UN System to promote links and synergies between,and the coo


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17

160

6

351

39

14

3

11

346

947

Evaluating the evolution of the impact

Analysing data in terms of ratios of affected to killedis another way of evaluating the evolution of theimpact of different of types of disasters over time.

Table 2 compares the ratios of the number of affect-ed to killed between the first 15 years and the last 15years of the study period by disaster category. Itshows the number of people affected for every oneperson killed by a specific disaster type.

Table 2 reveals the type of impact on human popula-

tions and indicates the difference in approach for pre-paredness and prevention between the types. Forexample,the low affected to killed ratios indicate dis-asters that require rapid response capacities and pre-paredness for acute trauma.Disasters with a high ratiof ff t d t kill d t d t i fl l ti ith

There has been a sea chextreme temperatures, flobetween the two 15-yearter types, such as flooddestroy livelihoods, shelte

These effects are particulathey do not kill outright,for already marginal popeven continue their lives.are less spectacular than inearthquakes,but they takemedia have gone home a

has dried up.

Drought

Earthquake

Extreme temperature

Flood

Slide

Volcano

Wave/surge

Wildfire

Windstorm

Total

44

8

14

11

3

11

3

2

21

13

17

248

48

874

144

17

4

39

655

2,046

119,883

20,780

2,545

9,503

1,193

5,395

61

995

5,977

11,526

Total

number ofdisasters (1)

Mean

of paffecone

Table 2 - Proportion of change in ratio of affected to killed by disast1974-1988 versus 1989-2003

1974-1988 1989-2003

Total

number ofdisasters (1)

Mean number

of pesonsaffected forone killed

(1) Only entries included with both killed and affected data

1.World Bank.World Developme

Oxford University Press;2001

Wh d di t ?


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The risk of disaster is partially linked to the geo-physical and meteorological characteristics of

regions.This makes it easier to identify high-riskzones in the world based on their physical and cli-

matic characteristics. However, as disasters are

entered in the EM-DAT database by country andthe criteria for inclusion is primarily based on the

human impact of an event, disasters occur more

frequently in countries covering a large area and

having a large population.

Map 1 clearly shows the countries with the high-

est number of disasters.The classification of disas-

ter occurrences into three classes represents amaximum average of one disaster per year for

Class 1, one to four disasters annually for Class 2

and more than four disasters per year for Class 3.

The United States and Mexico, together with

South and Southeast Asia and Australia,are partic-ularly prone to disasters, followed by Latin

America, Russia, some European countries, andvery few countries in Africa. Map 1 shows natural

hazard boundaries, such as the Pacifics volcanic

ring of fire, the cyclone and storm paths of EastAsia, the Eastern seaboard of North America and

tectonic plates,as well as countries covering a very

large surface and/or having a large population.

More die in the developing world

As Table 3 shows,the most impor tant disasters in

terms of numbers killed or affected over the last30 years have occurred in all three continents of

the developing wotop 10 ranking,wit

It has suffered mawhich missed the tand droughts also

The two phenofamines that spreatop the list with ne

tered due to drouas deaths due to deaths are often rinfectious diseasesrhea, but rarely drought .These mations of the re

droughtrelated fnumbers of regissomber indication many,many more.

The 1976 Tangshathe deadliest ear

with a total of 24struck in the midwas asleep, a factonumber of casualttude 7.8 earthquaright under the cunstable, alluvial so

The tropical cycBangladesh in 199of up to 250 kilompens with windstor

Where do disasters occur?

Map 1


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Map 1

ter's occurrence However many deaths indirectly Asia andAfrica


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ter s occurrence. However, many deaths indirectlyresult from increases in malnutrition,poverty,diseaseoutbreaks and the deterioration of living conditionsand of health,sanitation and other basic services.

More affected in the developing world

EM-DAT defines the number of people affectedby as disaster as "people requiring immediateassistance during a period of emergency, that isrequiring basic survival needs such as food,water,shelter, sanitation and immediate medical assis-

tance".These figures also underestimate the realnumber of people affected over the longer termby a disaster's occurrence.

Table 4 shows the 10 disasters with the mostnumber of people affected over the last threedecades.

Among the top ten affected, India ranks first andsecond, again with droughts. In this instance, thelarge and dense population of the country con-tributes to the huge numbers affected by any nat-ural event The same holds true in China Although

Asia and Africa

Just as there are number of peoplethere are also gre

nents are more afdisasters.Asia and burden of losses dyears, approximatreported killed anaffected lived in th

Of the total numbdisasters worldwidthan 75% were in Afor droughts and 71% for avalanchewindstorms.Of thby volcanic erupti

with more than 7disaster types,Asiawith 88% for avaldroughts and famifor windstorms 9

1.Drought

2.Drought

3.Flood

4.Flood

5.Drought

6.Flood

7.Flood

8.Flood

9.Flood

10.Flood

1987

2002

August 1988

May 1991

1979

1996

July 1993

May 1995

June 1999

July 1989

India

India

China

China

India

China

India

China

China

China

300,000,0

300,000,0

223,000,0

206,000,0

190,000,0

150,000,0

128,000,0

114,400,0

100,000,0

100,000,0

Disaster type Year(s) Countr y(ies) N umber of people affecte

Table 4 - Top 10 disasters with highest numbers affected:1974-2003

How are people affected by disasters


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Examining worldwide disaster data by the numberof occurrences in each country provides substantial

information about which countries suffer more dis-asters.However,looking at the total number of dis-asters relative to a country's area or the total num-ber of people affected relative to a country's pop-ulation can provide a different perspective on nat-ural disaster occurrence and impact.

Considering the classification of countries accord-ing to the numbers of people affected standardisedby 100,000 population,the pattern differs from thesimple distribution of events.This analysis controlsfor variability among countries with very large andvery small populations, although some countriescovering large areas still come out on top.

South and East Asia, particularly India, Bangladeshand China, are still in the highest category with ahigh proportion of its population being affected bynatural disasters. All of them have areas of highpopulation density,especially in river basins,and arehome to populations whose livelihoods are often

based on agriculture.When floods occur,the num-ber of affected communities quickly reach into thehundred thousands,and in some cases,millions.

Several countries in Africa are added to this list,although they did not figure in Map 1 based on theranking by disaster occurrence. On Map 2,

Southern Africa, Botswana, Zambia, Mozambiqueand Zimbabwe are in the highest category, togeth-er with Ethiopia and Mauritania.The developmentburden of disasters where rates of affected aremore than 5,000 per 100,000 population can be

Indonesia in Map 1 were based on disaster occurren

the lowest category, withaffected by disasters per hlation being 59, (US) 1(Indonesia).

Looking at the number o1,000 km2 can also give us

into which countries have aster occurrence.Howeveproblematic as the countrues are all small island statecernible on a global map.

Tuvalu (129),Bermuda (12

(58) and Montserrat (47),Pacific or in the Caribbeadisasters per 1,000 km2.

Countries such as China,wegory based on the absolasters and on the total

100,000 inhabitants, in thtotal of 0.05 disasters per 1has only experienced 0.98in the period 1974-2003 about 0.002.

Just as the occurence an

regions,different disaster tyof mortality, injuries,and pstructure and agriculturevarying rates of frequendictability.

How are people affected by disasters

Map 2


32/190

Map 2

earthquakes top the scale of immediate mortality possible to respond to d


33/190

q p yand structural destruction.However,except whenlandslides occur due to the tremors, earthquakeshave little impact on standing crops.

Statistics published following the Kobe earth-quake,showed that about 71% of the victims diedwithin 14 minutes of the earthquake, with a fur-ther 10.7% percent dying within six hours of thetremors.About 54% of the deaths resulted fromcrush injuries and other types of physical traumasustained in the collapse of buildings1.

Population density,structural fragility, time of strike,and intensity of seismic activity seem to be themain risk factors.Mortality rates vary from countryto country, primarily due to differences in buildingstyles and the density of settlements.The strongtremors of the recent Bam earthquake in Irandestroyed close to 90% of the city's buildings,killing26,796 people.Four days earlier,an earthquake ofthe same intensity, 6.6 on the Richter scale, struckthe city of San Simeon in California.This earthquakeleft two dead and 40 buildings damaged.

Droughts and famines cover wide areas

A total of 640 droughts or famines were report-ed in EM-DAT over the last three decades.Theycaused the death of more than one million indi-viduals and affected over 1.8 billion.The ratio ofaffected to killed over those 30 years was about

2,000 affected for each person killed.

Droughts and famines do not result in infrastruc-ture or shelter damage but in heavy crop and live-stock losses.They cover wide areas of land andf ff l i hb i i

p pSeveral regional early warnFamine Early Warning Syhave been set up aroundpose.

Floods have a pervasiv

Over the last 30 years,a toreported in EM-DAT, res206,303 people and affectThe affected to dead ratio

people affected for one pmore than for any other ty

Floods can cause extensivture and crops. Their depends in part on the tcycle of the crops in the reby floods can be immenextent on topographical 1998 in China submergehectares of farmland, an athe size of Belgium.

Floods can develop slowlcan occur suddenly, such floods. Most of the mortcaused by flash floods.Flople than they affect, but thpervasive and long term.

Volcanoes' impact can

There were 123 volcano-relast 30 years, with a total and more than 3 million pf ff d kill d 14

The most serious consequences of volcanic erup-


34/190

tion can actually arise from secondary effects.Ash

contains silica,a mineral that causes silicosis,a chron-

ic respiratory disease. Also, when deposited over

large areas,ash can destroy crops and make it very

difficult for livestock to forage for food or water.

W indstorms are among the most

destructive

Over the 30-year study period, a total of 1,864

windstorms caused the death of 293,758 individ-uals and affected more than 557 million.The ratio

of affected to killed was of 1,899,significantly less

than for floods but over 10 times more than for

earthquakes or volcanoes.

Windstorms are among the most destructive dis-asters.They often cover very wide areas and can

cause significant deaths, injuries, agricultural or

property loss.The most lethal windstorm of the

last 30 years was in Bangladesh in 1991 with

138,866 people killed. On average, each wind-

storm affected close to 300,000 people, although

a windstorm in China in 2002 affected 100 million.

In many cases,flooding from heavy rains and wind

surges has a greater impact on mortality than that

of the wind itself. However, collapsing buildings

and wind-strewn debris can account for many of

the injuries experienced during windstorms.

Human cost should top the agenda

Regardless of the disaster type, the vast majority

The inextricable link between poverty and disasters


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The occurrence of a natural disaster is based onthe convergence of two factors.The first is the

hazard factor, which is the risk of an earthquake,tornado,flood or other natural phenomenon.Thisfactor,as noted previously, is based on the geolog-ical,meteorological or ecological characteristics ofa region.The second is the vulnerability factor.Thiscan be best described as the number of people atrisk of being harmed by a hazard's occurrence,

whether it be through loss of lives or property,injuries or the disruption of livelihoods and eco-nomic activity.

It might seem self-evident that disasters have agreater impact on poorer countries.This relation-ship has been well documented, but it is impor-

tant to understand how poverty and the impactof disasters are linked.The key factor in this rela-tionship is the vulnerability of a population to ahazards occurrence.

figures are eclipsed by theEritrea and Malawi, rep

between 6,000 to almost per 100,000 population ov

Factors influencing vu

Several factors influencepopulation.These can be c

groups defined by physicand economic factors:

Physical aspects of vthe exposure of the phazard.This can mean as in a flood plain or in

Social vulnerability ipopulation growth, thand insecurity,ethnic, s

e e t cab e bet ee po e ty a d d saste s

Luxembourg

United States

Norway

SwitzerlandIreland

Canada

Belgium

Denmark

44,000

37,600

31,800

31,70030,500

29,400

29,000

29 000

0

59

5

24

72

2

0

CountryGDP (U S$)per capita

2002

Annual average victims/

100,000 population

1974 - 2003

CountryGDP (U S$per capit

2002

Somalia

Sierra Leone

Burundi

Congo,RDTanzania

Malawi

Afghanistan

Eritrea

550

580

600

610630

670

700

740

Table 5 - Comparing the human impact of natural disaster

between the 10 richest and 10 poorest countries

as water, electricity, communication networks Figure 6 shows th


36/190

and health care.

Environmental vulnerabilit y includes such fac-

tors as soil degradation and erosion,deforesta-

tion, chemical or biological pollution and theavailability of water,whether for drinking, irriga-

tion or other uses.

Poverty is closely linked to all four of these groups.

Poor populations often end up living in high risk or

environmentally degraded areas, have the least

access to social safety nets or infrastructure and

have few savings or available credit.

As with any complex situations, these factors do

not act independently of each other but are inti-

mately linked.Together they create conditions that

increase a population's vulnerability to hazards,and hence to the more frequent occurrence of

disasters.A certain number of these disaster con-

ditions are typical of increased vulnerability of

poor populations.These conditions are combina-

tions that interact to disproportionately affect the

poor when a hazard occurs.

the World Bank's

year periods betw

come as no surp

have the highest re

ural disasters.

Low-income coun

tion of victims rela

tion in all five-yea

middle-income co

income countries,

last three decad

countries had high

year periods even

income countries,

victim rate plunge

the lowest rate in

Migration and u

A primary factor li

the migration of po

areas. A good exa

cotton plantations

which forced poor factors) to move

Mean number of victims per 100,000 inhabitants per World Bank incfive-year periods 1974 - 2003

2 500

3 000

3 500

Figure 6

shantytowns on the slopes of the Casitas volcano( h i l f t ) I 1998 th h t t

Physical infrastructuret


37/190

(physical factor). In 1998, the shantytownsbeneath the deforested volcanic slopes (ecologicalfactor) were completely exposed to HurricaneMitch.When the crater lake collapsed under the

pressure of the water from the hurricane, it cre-ated a deadly landslide, killing dozens of slumdwellers in its wake.

Rural to urban migration is another factor thatputs more vulnerable people into high risk zones.Typically, the poorest of the rural populations

move into the least desirable settlements on theperiphery of cities and create large slums,such asthose in Calcutta or Rio. These settlements areoften established on unstable slopes,such as thoseon the outskirts of Guatemala City and MexicoCity, both of which are highly seismic and subjectto landslides at the slightest tremor.Other exam-ples include the migrant settlements on canalembankments such as those in Manila or in thelowlands of Dhaka.These communities live in con-stant fear of floods, which occur with devastatingregularity.

Dependency on agriculture createsvulnerability

The World Bank estimates that 70% of theworld's poor live in rural areas.Nearly two-thirdsof all natural disasters over the past two decadeshave been of hydro-meteorological origin. Theyhave their greatest impact on the agricultural sec-tor,sweeping away harvests,destroying plantationswith high winds or rainfall,or salinating large tractsof arable land.

C i i h il d d i l

poverty

Another important link benerability is the availability

to infrastructure, whethertion, irrigation or transpormeasure of poverty. Infraponent of development The destruction of infrastrters creates conditions poor,worsening their alrea

For example, a high proflooding are due to infrasestimates that infrastructu65% percent of all flood loOver the same period, theally loaned about US$25related projects. In Asia ainfrastructure represents atotal lending activity2.

Environmental degraddeadly toll

Rapid environmental dedeforestation, triggers disaslides kill people and desthousing and harvests.Theless spectacular than deathreat to the economy ofzens, especially those whrevenue or livelihood is de

The Yangtze River floodsmore than 3,000 people,fl d Th i

The vicious cycle of poverty


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The interaction of poverty and vulnerability is avicious cycle that can only be broken throughappropriate sustainable development mecha-

nisms. Vulnerable populations are economicallyfragile by definition and are less able to recoverfrom disasters. Savings or assets are few, or formany, non-existent. When a disaster strikes, itdestroys not only existing wealth,but also incomeopportunities and livelihoods, thereby furtherincreasing the vulnerability of the already poor

population.

For tunately, natural disaster prevention is nolonger a marginal issue. In the wake of the devas-tation witnessed in Mozambique, India, CentralAmerica and Kobe, it is recognized that the con-sequences of natural disasters are clearly not rel-

egated to a divine hand.Development actors aretaking action. Activities to reduce the impact ofhydro-meteorological events are possible andhave been successfully employed in many disasterprone countries. Physical preventive measuressuch as embankments or flood plain zoning,together with cooperative insurances and other

social protection systems can help vulnerablepopulations recover from catastrophic events orprevent them altogether.

Addressing basic environmental measures thatreduce global warming can be the most effectiveover the long term. But in the short term, local

effor ts in flood management and cyclone mitiga-tion actions have been shown to be extremelycost-effective. Soil depletion, erosion, water log-ging,and deforestation are preventable risk factorsfor disasters Many of these are suitably dealt with

Tallying the costs


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Tallying the costs of disasters is a formidable taskunder the best of circumstances. But it becomesdoubly difficult if authorities do not repor t losses.Over the past three decades, economic loss fig-ures were reported for less than 40% of all natu-ral disasters. In the early 1990s, the propor tionimproved to about half, but unfortunately hassince decreased. Since 2000, fewer than 25% ofthe disasters that meet the EM-DAT criteria have

reported economic losses.

Without evidence of the economic impact of therepeated onslaught of natural disasters, the devel-opment incentive to invest in disaster prepared-ness and prevention is even more difficult to justi-fy.This even more true for small recurrent disas-

ters for which costs are the least repor ted.

Losses are reported for a very small proportionof disasters. Since the early 1990s this propor-tion has been steadily declining. Of those thathave repor ted economic costs, the Kobe earth-quake of 1995 was by far the costliest disaster

ever with a total cost of over US$131 billion.Putt ing this event aside, the trend of costly dis-

asters appears to be rdecade.

Economic impact can

The economic impact of underscored by HurricaAmerica and the floods ofearthquakes in Turkey in 19

2003, the fires in Indonesiastorm that affected FranceEurope in 1999.The floods 1999 and particularly in 20try. In absolute terms the floods were not very imporepresented colossal econo

already crippled by years o

The Caribbean island ofastated by Hurricane Hestimated 98% of the destroyed.The subsequea long dormant volcano

island's capital and deinfrastructure that had b

Total reported economic losses in US$ million (2003)

Percentage of natural disasters with losses reported

200 000

250 000

US$million(2003)

&

Figure 7

following the hurricane. These major disasters

attracted much media attention and the setbacks

fer between organiz

to another Lossesf


40/190

attracted much media attention and the setbacks

they created for the development process were

also noted.For example, Hurricane Mitch's impact

on Honduras was said to have set back the coun-

try's development by 20 years.

Smaller but recurrent disasters often do not receive

media attention, nor is their destructive economic

erosion assessed.Furthermore,only the direct costs

of a disaster are usually evaluated and reported.

The economic consequences of disasters can be

broken down into direct and indirect costs and sec-

ondary consequences. Direct costs relate to the

capital costs of assets, such as buildings, infrastruc-

ture or crops destroyed or damaged by the disaster.

Indirect costs encompass damages to the flow of

goods and services and losses due to decreasedoutput. For a farmer, indirect losses can representloss of income because of damaged equipment or

inability to bring the crops to the market due to the

damaged infrastructure. Indirect costs also include

changes in productivity due to a higher incidence of

deaths, injuries or diseases. Secondary costs of dis-

asters represent both short and long-term changesin economic performance.These can be due to

changes in external trade, government budgets,

interest rates or indebtedness.

Unfortunately,the evaluation of economic damages is

not systematically undertaken and methodologies dif-

to another.Losses f

get reported, if onl

purposes,but most

direct losses,with lit

even less of second

As a result, it is

costs of disasters i

timated.

Its all in the re

Are economic los

disaster categorie

tion of disasters fo

repor ted in the E

about a third.The

the chances econand reported as t

for reconstruction

siderations push

banks to undertak

interesting to anal

which costs are m

Disaster losses are

windstorms entered

due to the infrastruc

clearly attributable

group of disasters

more reported ar

Number ofdisasters

Number of

disasters with

Proportion of

disasters withTo

reported$

Table 6 - For which disasters are costs more report

Again,physical damage as a direct consequence ofthe event is significant and requires heavy invest-

economic costs.Furthlossescan be of an ind


41/190

the event is significant and requires heavy investment in reconstruction. Roads, bridges, and otherinfrastructure is destroyed in violent cyclones andearthquakes and as a result,economic losses gen-

erally tend to be quickly assessed and repor ted.

Floods are the next largest category, with lossesreported for about one-third of the total events.Most countries at risk of floods are poor and haveagricultural-based economies. Flooding typicallydestroys cultivated lands established on riverbanks

and floodplains,as well as inflicts damage on infra-structure and undercuts foundations. Massiveagricultural losses are central to many of the pooreconomies, and often get repor ted for food aidand development purposes.

For other disaster types such as droughts,extreme temperatures, slides, volcanic eruptionand waves/surges,less than one disaster event outof five has losses repor ted.There may be severalfactors for this.

First, the costs of certain disasters may begrouped into another category.Slides,for exam-ple, can occur following an earthquake or awindstorm resulting in their costs beinggrouped in another disaster category.

Secondly, droughts and extreme temperaturesmay only draw the international attention in

terms of lives lost, with little consideration for

losses can be of an indand difficult to quantify

Finally, whether a disa

costs associated withwhether insurance pro

Rich countries report

As noted,the most expenwas the Kobe earthquake

billion.When adjusted to the costs amount to UShighest loss,adjusted againues,was the earthquake othat totaled about US$4most expensive disasters States with hurricane Andbillion) and the earthquaAngeles in 1994 (US$32.3

Richer countries tend to ring of the most expensiJapan, Italy and the Unitehead the list for earthquaof floods and wave surgeson top in every other cateinsured values of propertycosts for reconstruction,thas those with highest losse

A li

Year US$ (billion)

Table 7 - Top 10 most expensive disasters by type: 1974 200

1982 6 00

Drought

Italy

United States

1980

1994

20.00

26.00


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Armenia

China

United States

Algeria

Iran

Turkey

Taiwan

United States

United StatesChina

United States

Canada

Brazil

United States

France

Spain

United States

Flood

China

United States

China

ItalyChina

Germany

China

China

China

Spain

Landslide

Italy

Italy

Tajikistan

1988

1976

1989

1980

1990

1999

1999

1977

19981997

1986

1992

1975

1999

1991

1995

1989

1998

1993

1996

19941991

2002

1999

1993

1996

1983

1982

1987

1987

20.50

7.00

12.00

5.20

8.00

10.00

9.20

2.80

3.703.00

1.75

2.00

0.60

1.00

0.77

0.82

0.50

US$ (bill

20.00

12.00

12.60

9.307.50

9.13

8.10

6.06

6.31

3.90

US$ (bill

0.70

0.50

0.45

Year US$ (billExtreme temperature

Year US$ (billFlood

Year US$ (billLandslide

Cold wave

Heat waveCold wave

Heat wave

Cold wave

Cold wave

Heat wave

Cold wave

Cold wave

Cold wave

Philippines

Indonesia

1991

1983

0.21

0.15

Mount Pinatubo

Mount Gamalama


43/190

A i di t f it i l i thi f di t

Japan

Indonesia

Chile

Iceland

Philippines

Thailand

Philippines

Wildfire

IndonesiaUnited States

Mongolia

United States

United States

Italy

Australia

Yugoslavia

United States

Chile

Windstorm

United States

France

United StatesJapan

Korea,DPR

United States

Western Europe

United States

Caribbean

United States

Western Europe

Germany

1977

1983

1991

1996

1983

1999

1982

19971991

1996

1993

2000

1990

1983

1983

1998

1999

1992

1999

19951991

2000

1992

1990

1979

1989

2003

1990

1976

0.02

0.03

0.02

0.02

2.27

0.27

0.06

17.001.50

1.71

1.00

1.00

0.71

0.40

0.20

0.28

0.28

30.00

11.06

10.005.20

6.14

5.00

4.60

2.30

3.58

5.00

3.20

1.30

Year US$ (billion)W ave/surge

Year US$ (billion)W ildfire

Year US$ (billion)W indstorm

Mount Usus

Mont Colo

Cerro Hudson

Grimsvo

Hurricane Andrew

Winter storm

TornadoTyphoon Mireille

Typhoon Prapiroon

Hurricane Iniki

Hurricane Frederic

Hurricane Hugo

Hurricane Isabel

Hurricane Vivian

Capella Gale

Contrary to expectation, however, GDP actuallyoften increases in a disaster year as a result of

in 1992 and whichterms of costs in E


44/190

reconstruction and rehabilitation investments.

Clearly, the most expensive disasters relative toprevious year GDP have mostly been in smallisland states.With the exception of Mongolia andthe Central American countries that were affect-ed by Hurricane Mitch,six of the top 10 are small

island states.

The Kobe disaster, the most expensive disaster inabsolute terms (US$159 billion),in fact represent-ed less that 3% of Japans GDP compared to theearthquake that shook Guatemala in 1976,whichrepresented almost 25% of its GDP. Similarly,

Hurricane Andrew which hit Florida and Louisiana

0.3% of the GDP

struck Niue, a smPacific, the cost oment-owned build40% of the island's

Small but recurringimpact on developmated that recurresent an annual losAnalyzing the costrelative to a countpicture than when

St. Lucia

Mongolia

Vanuatu

Samoa

Dominica

Mongolia

St. Kitts & Nevis

Samoa

Nicaragua

Honduras

Country YearDisaster

Type

Cost

US$ (Million)

CostUS$ (m

1988

1996

1985

1991

1979

2000

1995

1990

1998

1998

Hurricane

Forest Fire

Cyclone

Cyclone

Hurricane

Winter Storm

Hurricane

Cyclone

Hurricane

Hurricane

Table 8 - Top 10 disasters costs as a proportion of G

1,000

1,713

173

278

44

875

197

119

1,000

2,000

1,5

2,0

2

3

1

9

2

1

1,

2,2

Table 9 - Most expensive disasters relat ive to GD P, by typ

Earthquake

Guatemala

year

1976

US$ (billion)

1.00

2003 US$ (billion)

3.24

Earthquake Year US$(billion) 2003 US$ (billion)


45/190

El Salvador

Algeria

Georgia

Nepal

El Salvador

El Salvador

Costa Rica

Chile

Iran

Flood

Yemen

Nepal

Jamaica

Bolivia

Bangladesh

Macedonia,FYRBangladesh

El Salvador

Tajikistan

Afghanistan

Landslide

Bolivia

Ecuador

Tajikistan

Kyrgyzstan

Volcanic eruption

Papua New Guinea

Wild fire

Mongolia

Samoa

Nicaragua

Indonesia

1986

1980

1991

1980

2001

2001

1991

1985

1990

year

1996

1987

2002

1982

1988

19951987

1982

1992

1988

year

1992

1993

2003

1994

year

1994

year

1996

1983

1991

1997

1.03

5.20

1.70

0.25

1.50

1.30

0.50

1.50

8.00

US$ (billion)

1.20

0.73

1.11

0.40

2.80

0.352.10

0.28

0.30

0.26

US$ (billion)

0.40

0.50

0.04

0.04

US$ (billion)

0.40

US$ (billion)

1.71

0.03

0.08

17.00

1.73

11.63

2.30

0.55

1.56

1.35

0.68

2.57

11.28

2003 US$ (billion)

1.41

1.18

1.14

0.76

4.36

0.423.47

0.54

0.39

0.41

2003 US$ (billion)

0.53

0.64

0.04

0.05

2003 US$ (billion)

0.50

2003 US$ (billion)

2.01

0.58

0.11

19.00

Flood Year US$ (billion) 2003 US$ (billion)

Landslide Year US$ (billion) 2003 US$ (billion)

Volcanic eruption Year US$ (billion) 2003 US$ (billion)

wildfire Year US$ (billion) 2003 US$ (billion)

W i d Y US$ (billi ) 2003 US$ (billi )

When expressing the losses by disaster category asa proportion of the previous year's GDP,the picturei i l diff I T bl h ki


46/190

is entirely different. In Table 9,the top ranking coun-tries are all developing nations and no industrializedcountry figures in the top 10 of any disaster catego-

ry. In addition, in Table 8 earthquakes representedthe disaster category with the highest relative costs,but in Table 9 windstorms take on that role.

From these figures,one can more easily grasp theserious impediment to growth that natural disas-ters represent for developing countries.Without

external aid, it would have taken the island of St.Lucia over four years for its GDP to equal thedamage caused by Hurricane Gilbert in 1998.

Disasters a window of opportunity?

The World Bank and the United States Geological

Survey calculated that the worldwide economiclosses from natural disasters in 1990s could havebeen reduced by US$280 billion if US$40 billionhad been invested in disaster preparedness, miti-gation and prevention strategies.

Having an emergency programme devote funds to

disaster mitigation and prevention is not a long-term, sustainable solution.This approach should bebuilt into community development plans, nationalindustrial and urban plans, and international devel-opment programmes. It should be an integral partof development programming. Paradoxically, in thisregard, disasters can open a window of opportuni-ty.In fact,the optimal time to introduce disaster pre-paredness and planning is in the wake of a disaster.

The World Bank has established the HazardM U i f l k h Di

Epidemics


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Another disaster category included in EM-DAT andclassified as a natural disaster is epidemics.EM-DATdefines an epidemic as either an unusual increase in

the number of cases of an infectious disease,whichalready exists in the region or population con-cerned;or the appearance of an infection previous-ly absent from a region.The actual disease causingthe epidemic,such a cholera or meningitis,is includ-ed in EM-DAT as a disaster subset.

The compilation of data on epidemics is a verycomplex issue, and one that CRED has notapproached with as much diligence and thor-oughness as its has with other types of natural dis-asters. Part of the reason for this is the existenceof other renowned epidemiological surveillanceorganizations such as the World Health

Organization's Department of CommunicableDisease Surveillance and Response and theCenter for Disease Control and Prevention'sCenter for Infectious Diseases or EpidemiologyProgram Office of the US Government.

Another reason CRED has not used the same

thorough approach to epidemics as it has withother natural disasters and technological disastersis the very complexity of tracking and registeringthese events.Although a generic definition of anepidemic can be found in dictionaries, no onecomprehensive definition exists with thresholdsthat can be applied to all diseases and across all

regions of the world.

Certain epidemics such asHIV/AIDS and tuberculosis

t i l d d i th EM

an epidemic of an unprecemust be tackled with all ava

According to World Hemates for 2001, infectious26% of all deaths worldwalmost 40% were from rediarrhoeal diseases alone.cines, along with providinnated food and water,cou

of these deaths

The inclusion of an epidemthe same criteria as for annological disasters.The crideaths,100 people affecteal assistance or a declara

gency must be met beforeed in EM-DAT. Howeverdependent on specialized press agencies for exampmation than for any other

The top 10 epidemics

The influenza epidemic ofmore than 20 million wthere have not been anHIV/AIDS aside over theshows the world's top ten 30 years in terms of num

Rank Date Country Disease*

Table 10 - Top 10 epidemics by numbers kill

Of the epidemics entered in our database, themost lethal over the last 30 years was the 1991cholera epidemic in Peru This epidemic was actu

The Democratic Nigeria, India, Banghighest occurren


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cholera epidemic in Peru.This epidemic was actu-ally started when a foreign ship dumped sewageinto a bay within reach of an important coastal

town. The epidemic quickly spread throughoutSouth America and even made it to the UnitedStates when infected passengers arrived fromPeru on commercial airlines.

Six of the top 10 epidemics occurred on theAfrican continent, three in Asia and one in South

America.This follows the general geographic pat-tern of epidemic occurrences over the last 30years, with the majority occurring in Africa fol-lowed by Asia.

highest occurrenundoubtedly, manymonitoring authoriti

conflict,such as Siersuch as Myanmar m

An interesting trenoccurrence of epthe equator. Mandengue fever or m

tropics that isregions. It is one othe only one,whichdemics in Central

Figure 8

Proportion of epidemics by continent: 1974

121076

47

239

Africa Asia Europe Latin America North A

Map 3


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regarded the outbreak of epidemics as a nationalsecurity issue and did not share the informationeasilyThiswashighlighted asrecently as2002 dur-

The increase in em

issue that can only

laboration Survei


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easily.This was highlighted as recently as 2002,during the SARS epidemic when cases were report-ed very late to international authorities, compro-

mising the early recognition of the epidemic.Fortunately, implications of the outbreak soonconvinced authorities of severely affected coun-tries to cooperate fully with international healthagencies, a requirement that is critical in todaysglobalized world where borders to not stop thespread of an infectious agent.

The global struggle continues

The optimism in the battle against infectious dis-eases, which fostered in the 1960s and 1970s,reached its peak in 1978 when the World HealthOrganization predicted that even the poorest

nations would undergo a positive health transitionbefore the millennium2.This optimism was basedon two erroneous assumptions.The first was thatthe evolution of infectious agents was static andthe second that diseases would not change intheir geographic occurrence patterns.

Unfor tunately, these assumptions soon proved tobe flawed.A number of factors, including popula-tion expansion, complex humanitarian emergen-cies such as conflicts, international travel andtrade, changing land use patterns, absent or inef-fective health and surveillance systems as well asmicrobial adaptations have made the global strug-

gle against infectious diseases more importanttoday than ever in the past.

The number of emerging pathogens, that is thoseh l di d d h h h

laboration. Survei

applied research, p

as public health in

ened.Furthermore

tions have an an

surveillance of anim

lel with human sur

On average international donationsfor emergency Examining received aid on

Donors prefer certain types of disasters


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On average,international donations for emergency

humanitarian aid totaled about US$7 million per

disaster over the last decade.However,the basis on

which the international community makes availablehumanitarian aid remains unclear.Donor reaction to

disasters in different countries varied significantly

during this period for reasons that are not immedi-

ately discernable.The allocation of humanitarian aid

does not seem to be clearly linked to the magnitude

of human needs. Furthermore, donors seem to

show preferences for certain types of disasters over

others, providing vastly variable aid for one com-

pared to another.

Overall, global humanitarian assistance more than

doubled over the 1990s from US$2.1 billion at the

beginning of the decade to US$5.9 billion in 2000.A sizeable part of this went to complex emergen-

cies such as civil conflicts.Humanitarian aid peaked

as a proportion of total overseas development aid

in 1994-1995 in most countries except the UK,

which doubled its humanitarian aid in 20022003

compared to what it gave in 19981999.

Examining received aid on

sons affected by droughts

most widespread,frequent

received US$2.8 and USrespectively.The highest pe

fires, tidal waves and othe

with the first two registerin

aid per victim.

When ranking disasters

event, the most specta

receive the largest amoun

This is hardly surprising as

emergency aid is widely k

tend to capture the headl

growing flood or creepin

windstorms and volcanoesaround US$10 million per

ients of aid according to

and cold waves,wildfires,a

Recently, however, there

donors to allocate resourc

tive criteria of need. Queby decisions to respond

Figure 9

Amount of humanitarian aid per victim: 1992-2003

Value in US$ - Figures in parentheses give ranking for amount of humanitarian aid per disaster occurr ence

Volcano (3)

0 100 200 300 400

repor ts only, which have later been shown to behighly exaggerated. For example, the volcaniceruption in Goma in 1977 was reported as having

to this was massiveaffected by one singlist of humanitarian a


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p p gkilled more than 2,000 persons when in fact, thevalidated number was 147.Similarly,the 2003 Bam

earthquake initially registered more than 40,000deaths, which was subsequently validated at26,796,although this figure may yet change.

Validated and accurate figures are key to targetingemergency aid and improving its effectiveness.Disasters reporting large numbers of dead will

trigger a different type of aid response than thosewith fewer dead and more injured but living vic-tims. CRED, having started a process to improveaccuracy and quality of disaster related data, isadvocating for better rapid data collection meth-ods and their use for emergency decision makingby donors.

Response to Hurricane Mitchtops the list

The largest single contribution for anatural disaster was made for CentralAmerican countries after hurricane

Mitch, with about US$700 million inemergency aid.This amount represent-ed almost the entire humanitarianbudget of both the EuropeanCommission and the US governmentin 1998 and exceeded the total givenfor all natural disasters in the previous

five years.The emergency aid response

India, Bangladesh a

list of single nationmum of humanitarpartly reflects the the worlds most countries.India is baffected in these cmillions as soon a

gering an internatio

Because some cmore disasters thaing at the distributper-disaster basis.

Hurricane Mitch sfollowed not by Chsmall Caribbean

Table 11 - Top 10 recipients

of humanitarian aid:1992-2003

Central America

Egypt

Montserrat

El Salvador

Mozambique

Democratic Republic of Congo

Turkey

Poland

Bangladesh

China

Countryof

Table 12 - Largest recipients of human

An inequitable distribution of resources

The previous section presented some analyses of

These substantial differencby the varying costs of assistance in different cou


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p p yallocation patterns and preferences in humanitari-an aid for natural disasters. The Overseas

Development Institute (ODI) in the UK publisheda report1 analysing the past six years of bilateralhumanitarian assistance to both civil conflicts andnatural disasters. This report finds that aid hasbeen split fairly evenly between three regions Africa, Asia and Europe with each receivingaround a fifth of the total.For the main multilater-

al agencies, the picture is different. In 2000, forexample, 64% of the World Food Programmes(W FP) expenditure allocable by region went toAfrica. ECHOs allocation of humanitarian expen-diture shows a strong European bias, with 47%being spent in Central and Eastern Europebetween 1993 and 2000,almost half of it in the

former Yugoslavia.

Data on the allocation of funds per affected per-son is also revealing. ODI notes that during the1990s, funding per affected person in the GreatLakes and the former Yugoslavia was roughly twicethe average for surrounding countries. Funding

requests also far outstripped those for otherregions.The average request for Africa between1995 and 1997 was between US$50 and US$90per affected person,however, for the Great Lakesit was never lower than US$150 and peaked atUS$235. In the former Yugoslavia,requested fund-ing per head ranged from US$150 to US$300

compared with a regional average of less thanUS$120.

In 2000:

a different story. They imdards tend to be applied

gency aid are neither state

Patterns of aid such as chapter indicate that humhas some ways to go befoimpartial and evidence-bathe major destinations of

funds tend to be high-prthose in countries or regioer politically or strategicall

Consider that over the patries or regions have incluIraq, Rwanda and Afgha

unpopular governmentsgencies tend not to attracis why WFP was unable toresponse to the cripplinCuba in 1998.

Are natural hazards increasing?Probably not sig- programmes, the

Looking to the future


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g y gnificantly. But the number of people vulnerableand affected by disasters is definitely on the

increase. And the two are not the same thing.Globally,a little more than 90 million were affect-ed by natural disasters in 1990. In 2003,the com-parable number was nearly 255 million, bringingthe cumulative total between 1990 and 2003 to3.4 billion. The numbers affected have increasedmore than 180% from 1990 to 2003 compared to

just more than a 60% increase in numbers ofreported disasters over the same period.

A 60% increase may not represent a significantincrease in numbers of events in view of vastlyimproved reporting and media coverage. But a180% increase in victims is a definite trend and

one that is likely to continue into the future.

These statistics reveal many harsh realities con-cerning natural disasters. Mitigation of hazards,such as early warning for cyclones or better floodplain management, has much improved over thelast decades due to more accessible technology

and greater know-how.Furthermore,effectivenessand efficiency in both national and internationalrelief response has made great progress duringthis period, bringing down the death tolls fromdisasters. On the other hand, environmental fac-tors and population pressures are far more com-plex and difficult to control.

While excess mor tality related to acute andchronic disasters has decreased, there is anincrease in the number of victims who survive

i h h i l i j i i l d

p gmost likely continu

Indirect causes, sdesertification andand markets forcerisky areas in and centration of resouschools and healtfamilies to move in

tle or no economriverbeds, gorges,lands to be near centres. Inadequatdoes not give them

Mega-disasters are

size of the populatioRichter scale readinwind scale.Therefoto have more disaevents because largConversely,disasterareas affect fewer p

as a major humanita

When the earthq26, 2001, the popfrom what it was iknown to be at a massive migration

2001, most of estiin the city,creatingnot have been cooutskirts of Dhakad h

Figure 10

Number of small, medium and large natural disasters: global forecast for years 200


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Low and lower middle income countries

0

50

100

150

200

250

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

N

umberofnaturaldisasters

small medium

large Polynomial (small)Polynomial (medium) Polynomial (large)

Figure 11

Number of small, medium and large natural disasters: global forecast for years 2004-2High and upper middle income countries

20

40

60

80

100

120

140

160

180

200

Num

berofnaturaldisasters

mitigate the occurrence of the most commonforms of natural disasters.

L ki i l b ll i i k b i d

Finally,evaluation ato be developed inferent countries o

i


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Looking into a crystal ball is a risky business andeven more so for phenomena that are so closely

linked to notoriously unpredictable physical,mete-orological and social parameters. At the sametime,by pointing a finger at uncontrollable naturalevents,we draw attention away from the fact thatinequitable distribution of resources are forcingincreasing numbers of people to live in risky areas.Disaster preparedness, mitigation and prevention

should move out of the humanitarian agenda andbecome an organic part of the developmentframework.

In the future, environmental and population pres-sures will particularly affect the occurrence offloods and droughts. Progressive impoverishment

of people will mean that small and previouslyinsignificant disasters will be classified as majorones due to the impact on human communities.Rising sea levels caused by climate change threat-en millions of people living in low-lying areas suchas Bangladesh, small island states, China or Egypt.In addition, global warming is furthermore

expected to increase the occurrence of naturalhazards and epidemics over the next century.

A call to action

First, disaster management and response shouldbecome more evidence-based. Data should be

used more frequently to justify resource allocationand targeting of action. Data quality shouldimprove but only to the point that it is collectedfor a clear,concrete and specific use. It should notb d i i lf

systematic approaspent on prepared

will remain unknow

This report shouldfor the time to tak


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Annex 1:disaster maps

The following maps show global disaster data by main disaster categor


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occurrences and the number of victims per 100,000 inhabitants.

The main disaster categories are:

Hydrological disasters include floods, landslides, mudflows, avalanches, scanes,winter storms,tornadoes,tropical storms,droughts,wildfires and e

Geological disasters include earthquakes,volcanic eruptions,tsunamis,an Droughts and related disasters include droughts,extreme temperatures, Floods and related disasters include floods,landslides,mudflows and aval

Windstorms and related disasters include storms,typhoons,cyclones,hurand tropical storms.

Earthquake and related disasters include earthquakes,tsunamis and tidal Volcanic eruptions.

The mean annual number of victims per 100,000 inhabitants was calcupeople killed and the number of people affected by a disaster every year,d

number of inhabitants in the country or territory that same year and mul

For countries such as the former USSR or Yugoslavia,which have experievious 30 years, data were disaggregated and associated with the countrWhen it was impossible to disaggregate the data they were not included have not been included on the maps usually represented less than 1% o

The classification of the data into the four classes shown on the maps wpart on the mean and range of the data. Classes were also selected so tvictims over the 30 years could be broken down to get annual values.Tmaps showing the number of disasters and the number of victims,a propobetween the two.

The class representing zero disasters or victims includes situations when

and when no victims or population data were available.

Map Annex 1


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Map Annex 2

8/9/2019 Thirthy Yea

Documents

Thirthy Years of Natural Disasters 1974-2003 the Numbers