EXECUTIVE SUMMARY
The geography of poverty,
disasters and climate
extremes in 2030
Andrew Shepherd (ODI)
Tom Mitchell (ODI)
Kirsty Lewis (UK Met Office)Amanda Lenhardt (ODI)
Lindsey Jones (ODI)
Lucy Scott (ODI)
Robert Muir-Wood (RMS)+EYMESSAGESƔ Extreme weather linked to climate change
is increasing and will likely cause moredisasters. Such disasters, especially thoselinked to drought, can be the most importantcause of impoverishment, cancelling progresson poverty reduction.
Ɣ Up to 325 million extremely poor people
will be living in the 49 most hazard-prone
countries in 2030, the majority in South Asiaand sub-Saharan Africa.
Ɣ The 11 countries most at risk of disasterinduced poverty are Bangladesh, Democratic
Republic of the Congo, Ethiopia, Kenya,
Madagascar, Nepal, Nigeria, Pakistan, South
Sudan, Sudan and Uganda.
Ɣ Disaster risk management should be a key
component of poverty reduction efforts,
focusing on protecting livelihoods as well assaving lives. There is a need to identify andthen act where the poor and disaster risks aremost concentrated.
Ɣ The post-2015 development goals must include
targets on disasters and climate change,
recognising the threat they pose to the headline
goal of eradicating extreme poverty by 2030.

4HEFULLREPORTISAVAILABLEFROMWWWODIORGPOVERTY DISASTERS /CTOBER

Climate change and exposure to ‘natural’ disasters threaten
to derail international efforts to eradicate poverty by 2030.
As temperatures warm, many of the world’s poorest andmost vulnerable citizens will face the growing risks linked
to more intense or lengthy droughts, extreme rainfall andflooding and severe heat waves – risks that threaten lives
and livelihoods, as well as the hard-won gains made on
poverty in recent decades. The impoverishing impact of bothclimate change and natural disasters is so grave that the UN
Secretary General’s High Level Panel (HLP) on Post-2015
Development Goals1 has suggested a target to be added to
the first proposed post-2015 development goal on ending
poverty: ‘to build resilience and reduce the number of deaths
caused by disasters’.
We already know that disasters have a distinct geography,2that poverty is concentrated in particular parts of the world
and that climate change has an impact on extremes of heat,rainfall and droughts in many regions.3 But how will thesepatterns overlap in 2030, the probable end point for the
next set of development goals, and how serious a threat
do disasters and climate change pose to our prospects ofeliminating extreme poverty in the next two decades?
This report, The geography of poverty, disasters andclimate extremes in 2030, examines the relationshipbetween disasters and poverty. It concludes that, without
concerted action, up to 325 million extremely poor people
could be living in the 49 countries most exposed to the fullrange of natural hazards and climate extremes in 2030.4 It
maps out where the poorest people are likely to live anddevelops a range of scenarios to identify potential patternsof vulnerability to extreme weather and earthquakes – whois going to be vulnerable and why. These scenarios are
dynamic: they consider how the threats may change, whichcountries face the greatest risk and what role canbe played by disaster risk management (DRM).

45 countries most exposed to these hazards by
2030. This is a major concern as drought and flood
hazards are among the most potent shocks when it
comes to causing long-term impoverishment.

The report argues that if the international
community is serious about eradicating poverty
by 2030, it must put DRM at the heart of poverty
eradication efforts. Without this, the target ofending poverty may not be within reach.

Natural disasters spiral into human catastrophes
when they entrench the poverty that alreadyexists and pull more people down into poverty
as their assets vanish, together with theirmeans to generate an income. The risk of
impoverishment is linked to lack of accessto the markets, capital, assets and insurance
mechanisms that can help people to cope and torebuild. This combination of exposure to climate
vulnerability and limited access to social safety
nets, to land and to work is a serious risk factor,
as is living in a remote rural area.

4HELINKSBETWEENDISASTERSANDPOVERTY
In combining climate, disaster and poverty
projections, the report finds that high levels ofpoverty will still be seen in 2030 if we follow
a ‘business as usual’ approach. Discounting
earthquake and cyclone exposure, and assessing
just drought, extreme temperature and flood
hazards alone, reveals that between 176 and 319
million extremely poor people will be living in theGood DRM can reduce the impact of disasters on
poor people, as highlighted by the vast differencein the human impact of natural hazards. In 2010,%XPOSURETOEARTHQUAKES CYCLONES DROUGHTS EXTREMEHEATANDFLOODSIN

&IGURE!0ROJECTEDPOVERTYLEVELSININCOUNTRIESRANKINGHIGHESTONTHE
MULTI HAZARDEARTHQUAKES CYCLONES DROUGHTS EXTREMEHEATANDmOODS INDEX
35

34

Population below$1.25/day (millions)
COUNTRY
0.000

INDIA
126.5

Millions inpoverty

MYANMAR
3.075

LAOS PDR
0.295

Baseline

00.001 to 0.01
0.01 to 0.1
0.1 to 1
1 to 1010 to 100
> 100

VIET NAM
4.908

BELIZE
0.027

NICARAGUA
1.436

31

CUBA
0.382

INDONESIA
3.430

30

EL
SALVADOR
0.313

33

32

29

28

COSTA RICA
0.008

THAILAND
4.797

PHILIPPINES
13.18

CHINA
7.127

GUATEMALA
3.733

PAPUA
NEW GUINEA
1.085
PERU
0.262

ECUADOR TURKEY SRI LANKA
0.648
0.215
0.292

CAMBODIA
1.501

COLOMBIA
3.845

MOZAMBIQUE
7.505
VENEZUELA
0.034

ALBANIA
0.001

HONDURAS
3.25

HAITI
6.802

27

26

NEPAL
18.45

BANGLADESH
20.93

PAKISTAN
57.56

DOMINICAN
REPUBLIC
0.073

BOLIVA
0.175

MEXICO
4.048

MACEDONIA
0.059

MADAGASCAR
27.24

GEORGIA
0.118

TIMORLESTE
0.007

25
LowestLow

Moderate

High

Highest

6ULNERABILITYTOPOVERTY
NOTE: The figure shows a set of countries with the highest exposure to the five hazards in 2030, plotted against their 'vulnerability to poverty', which is ameasure of the risk they face of future poverty when presented with shocks, such as 'natural' disasters (see Chapter 2). The circles indicate projected poverty
numbers for each of the countries in 2030 assuming a baseline projection. This graphic does not account for the capacity of each country to manage disaster
risk, which is why the countries plotted here differ from the lists of countries highlighted in the text.

2

EXECUTIVE SUMMARY| THE GEOGRAPHY OF POVERTY, DISASTERS AND CLIMATE EXTREMES IN 2030

for example, 11% of those exposed to the Haiti
earthquake lost their lives, compared to 0.1% of
those who experienced the Chile earthquake.6 In
2008, Cyclone Nargis killed 138,000 people in
Myanmar, while Hurricane Gustav, a storm ofsimilar strength, killed just 153 in the Caribbean
and US. Hazard-prone countries with big
populations living in poverty, particularly thoseclustered in sub-Saharan Africa and South Asia,
lack the capacity to manage disaster risks or the
threats from climate change. So, continuing withthe status quo will result in millions of poor people
left without proper protection in the face of evergrowing disaster threats.

When combining all of the data sets,9 thefollowing findings emerge.
By 2030, 11 countries will have high numbers ofpeople in poverty, high multi-hazard exposure
and inadequate capacity to minimise the impacts:
Bangladesh, Democratic Republic of the Congo,
Ethiopia, Kenya, Madagascar, Nepal, Nigeria,
Pakistan, South Sudan,10 Sudan and Uganda.

Figures A and B highlight the countries of concernthat are assessed in this study. Every one ofthem is prone to the multiple hazards assessedin this study, and is also likely to see high levelsof extreme poverty in 2030. Here, we see that,unless something changes – and changes fast – up
to 118 million extremely poor people in subSaharan Africa will be exposed to drought, floodand extreme heat hazards alone in 2030:7 Chad
(4-5 million), Central African Republic (3 million),
Democratic Republic of the Congo (20-30 million),
Ethiopia (12-22million), Liberia (1-2 million),
Nigeria (14-22 million), Uganda (3-6 million) arecountries with the highest concentrations.8

Another 10 countries have high proportions ofpeople in poverty, high multi-hazard exposure
and inadequate capacity to minimise the impacts:
Benin, Central African Republic, Chad, Gambia,
Guinea Bissau, Haiti, Liberia, Mali, North Korea
and Zimbabwe.
Niger, Somalia and Yemen could also feature inthis list. While their total exposure to hazards,
other than drought, is relatively low, these arecountries that have high levels of poverty and low
levels of DRM capacity.
Afghanistan, Cameroon, Myanmar and Papua
New Guinea also endure high exposure to hazard
and moderate poverty (with at least 10% of their
populations and/or 1 million people under the$1.25 per day poverty line) and limited DRM
capacity. While this report does not focus on therelationship between conflict, fragility, disasters
and climate extremes, there is a striking overlap%XPOSURETODROUGHT HEATANDFLOOD&IGURE"0ROJECTEDPOVERTYLEVELSININCOUNTRIESWITHTHEHIGHESTEXPOSURETODROUGHTS EXTREMEHEATANDmOODS
Population below$1.25/day (millions)
COUNTRY
0.000

21
BOLIVIA
0.175

PARAGUAY
0.498

PERU
0.262

Millions inpovertyCAMEROON
1.535

Baseline
BRAZIL2.1

00.001 to 0.01
0.01 to 0.1
0.1 to 1
1 to 1010 to 100
> 100

GUINEA
2.038

GUINEABISSAU
1.204

INDIA
126.5

MEXICO
4.048

INDONESIA
3.43

NIGERIA
21.75

UGANDA
6.568

COLOMBIA
3.845

LIBERIA
2.333

DEM. REP.
CONGO
29.96

GABON
0.022

SIERRA
LEONE
0.884

VENEZUELA
0.034

GUYANA
0.037

ECUADOR
0.648

LAO PDR
0.295

MYANMAR
3.075

PAPUA
NEW GUINEA
1.085

THAILAND
4.797

GUATEMALA
3.733

SUDAN
18.24

NEPAL
18.45

ANGOLA
0.335

CONGO
0.21

BELIZE
0.027

SRI LANKA
0.292

VIET NAM
4.908

CÔTE
D’IVOIRE
3.086

ETHIOPIA
21.76

BANGLADESH
20.93

CENTRAL
AFRICAN REP
3.117

CHAD
5.463

20

LowestTURKEY
0.215

Low

CAMBODIA
1.501

Moderate

High

Highest

6ULNERABILITYTOPOVERTY
NOTE: The figure shows a set of countries with the highest exposure to the three hazards in 2030, plotted against their 'vulnerability to poverty', which is ameasure of the risk they face of future poverty when presented with shocks, such as 'natural' disasters (see Chapter 2). The circles indicate projected poverty
numbers for each of the countries in 2030 assuming a baseline projection. These countries differ from figure A as it features just the countries particularly
exposed to the three hazards rather than the full list of five hazards included in figure A.

3

between today’s fragile states and the countries
that are of greatest concern in terms of poverty
and exposure to hazards in 2030.
India represents a special case. It has the highest
numbers of people who are still likely to be living inpoverty in 2030 and some of the highest exposure
to hazards, yet has the central capacity to manage
disaster risk. Given its size India needs to be treatedas a cluster of separate sub-national entities, withsome states causing considerable concern, including
Assam, Madhya Pradesh, Odisha, Uttar Pradesh
and West Bengal.
This list of countries and states represents a
useful set of targets for serious attempts to end
poverty, providing a checklist for international
efforts to strengthen DRM systems and link theseto poverty reduction efforts.

4HEDISASTERTHREATTOPOVERTYREDUCTION
Detailed analysis of data from rural Ethiopia andAndhra Pradesh in India for this study suggeststhat where drought is a major risk it is also thesingle most important factor in impoverishment– outstripping, for example, ill health or dowry
payments. This counters a view that is common

in the literature: that health-related shocks are
the biggest factor in impoverishment. It should be
noted that this result is only from two droughtprone areas, and would need to be confirmed byfurther research. Disaster-related impoverishment
also appears to have a distinct within-country
geography, being largely rural rather than urban.
Figure C highlights this stark rural dimension andshows how impoverishment trends can easily cancelout escape routes from poverty in some countries.
The report also examines data from Ethiopia andAndhra Pradesh to explore whether there is an
income threshold beyond which the risk of falling
into poverty as a result of a disaster is reduced.
While initial analysis found different plausible
thresholds (suggesting that any threshold would becontext-specific), further analysis suggests that theprobability of impoverishment falls as householdprosperity rises, rather than any particular income
level acting as a threshold. Further research could
explore this issue in more detail to find out if such
thresholds exist. If so, they would be a useful aid
to poverty reduction and DRM planning.
Analysis of trends suggests that poverty will beconcentrated in particular areas in most countries
in the future and in rural or disadvantaged regionsin particular.11 However, an assessment of poverty,
hazards and DRM efforts in five countries ofOFPOPULATIONINPOVERTYNATIONALPOVERTYLINES&IGURE#)MPOVERISHMENTTRENDSCANCANCELOUTPROGRESS
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SOURCE: Lenhardt, A. and Shepherd, A. (2013) ‘What happened to the poorest 50%?’, Chronic Poverty Advisory Network, Challenge Paper 1.
NOTE: The figure shows historic poverty averages for the dates attached to each country name. While it highlights an overall positive trend inpoverty reduction, for particular countries and geographies, for certain periods of time, impoverishment rates can cancel out escapes from poverty.

4

EXECUTIVE SUMMARY| THE GEOGRAPHY OF POVERTY, DISASTERS AND CLIMATE EXTREMES IN 2030

&IGURE$0ROJECTEDCHANGEINTHEGLOBALDROUGHTHAZARDINDICATORBETWEEN AND 

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NOTE: The drought hazard indicator is a measure of how exposed an area is to droughts. This is measured as the deficit in rainfall during
periods when the rainfall is below average, i.e. when rainfall is below average, how dry it is. The absolute measure of drought by this means is theshortfall of precipitation, compared to the mean precipitation at the time of year, in an average dry spell. The figure shows the change in droughtby highlighting the increase or decrease in the dryness of drought periods, in mm. Blue squares indicate that droughts are getting less severe, red,more severe. The larger the square, the greater the agreement between multiple climate models.

concern – Ethiopia, Haiti, Madagascar, Nepal andPakistan – finds that DRM policies and systems
rarely focus on poverty or target the most disasterprone regions explicitly. This may be explained by
DRM programming being directed to high-value
assets and to saving lives rather than protecting
livelihoods. We need, therefore, risk modelling andmapping to focus the combined efforts of DRM andpoverty reduction, and make them fit for purpose.

(OWCLIMATECHANGEWILLSHAPEHAZARDTRENDSBYClimate models suggest that the severity anddistribution of some hydro-meteorological hazards
will change in the near future – even by 2030.
Figure D, for example, shows how one indicator of
the average drought severity will change between
the late 20th century and the middle of the 21st.
It shows the strong likelihood of more droughthazard in parts of Central and South America,
Southern Europe, Eastern and South-eastern Asiaand in a broad belt spanning southern Africa. These
trends are particularly important for countries andareas that are likely to have high poverty rates in
2030, such as Democratic Republic of the Congoor northern India where drought exposure is
only expected to increase.12 While climate change
will become an increasingly important driver ofchanging hazard geography in the next two decades,
the distribution of hazard exposure we see today
will remain a strong predictor of exposure in 2030.

2ECOMMENDATIONSThis report argues that the post-2015 development
goals must recognise the threat posed by disasters
and climate change to the global headline goal oferadicating extreme poverty by 2030. The current
Millennium Development Goals have not paid
sufficient attention to the risk factors that push
people into poverty and this should be rectified;including recognition of the role played by disasters.
Poverty eradication efforts need to look beyond
those living in poverty today to raise people aboveand beyond extreme poverty and reduce the riskof poverty reversals at a later date. This means
addressing the risk factors – including disasters.
This is crucial if the promise of a world free fromextreme poverty is not to evaporate, just as this goal
appears to be within reach.
We recommend, therefore, that a goal on ending
poverty is coupled with targets on tackling key
impoverishment factors, where natural disasters
are a significant component and that thesefactors become the cornerstones of internationaland national efforts to reduce poverty overall.
Accordingly, the post-2015 framework should

5

%NDNOTES
monitor progress beyond the $1.25 per day poverty thresholdto monitor higher thresholds, such as $4 per day, beyond
which the risk of falling into poverty would be greatly
reduced. Identifying such thresholds requires further research.
Within a development context focused on eradicating
poverty, international efforts to reduce disaster risk should
concentrate on the countries at greatest risk of disaster-induced
impoverishment and target specific sub-national trends. DRM
efforts should focus on saving livelihoods as well as lives,
giving equal weight to social protection and asset-building
approaches alongside early warning systems. Disaster resilience
efforts should also have clear strategies to reduce the poverty
and build the assets of those affected by disasters, engaging
people in long-term livelihood programmes. Beyond politicalcommitment, this will take upfront and recurrent international
investment in DRM until national revenues and individuals
can adequately take on the challenge of providing protection.
However, this is currently an underfunded area with just 40
cents in every $100 of official development assistance (ODA)
spent on reducing disaster risk. $9 in every $10 dollars spent
on disasters is spent after the disaster has struck. Over the last
20 years, the countries highlighted in this report as being atgreatest threat of disaster-induced impoverishment in 2030
have seen an average of just $2million of ODA spent on
reducing disaster risk each year.13 This needs to change, withmore money targeted to maximising disaster resilience andpoverty reduction at the same time.

!BOUTTHISREPORTThe report is structured in six sections. Section 1 outlines thelinks between disasters, poverty and impoverishment. Section
2 maps out the geography of poverty in 2030, while Section
3 highlights the projected geography of ‘natural’ hazards.
Section 4 examines the capacity of the countries at greatest
risk to reduce disaster risk and respond to disasters. Section 5
brings the analysis together to build a picture of both poverty
and hazard risk in 2030, together with today’s disaster risk
management and adaptive capacity14 highlighting possible
variations to the trends and providing in-depth country
analysis. Finally, Section 6 sets out possible policy responses
for future international agreements, development cooperation,
countries of concern and actions by the research community.

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