thirthy years of natural disasters 1974-2003 the numbers
TRANSCRIPT
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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
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Map 2
earthquakes top the scale of immediate mortality possible to respond to d
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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-
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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
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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
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(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
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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
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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
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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
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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)
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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
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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
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8/9/2019 Thirthy Yea