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WorldRiskReport 2018
Focus: Child Protection and Children's Rights
Imprint
Publisher of the WorldRiskReport 2018
Bündnis Entwicklung Hilft
and
Ruhr University Bochum– Institute for International Law
of Peace and Armed Conflict (IFHV)
Concept, implementation and editing
Peter Mucke, Bündnis Entwicklung Hilft, Project Leader
Lotte Kirch, Bündnis Entwicklung Hilft, Editor in Chief
Julia Walter, MediaCompany
Scientific lead
Prof. Dr. Katrin Radtke, IFHV
Authors
Prof. Dr. Hans-Joachim Heintze, IFHV
Lotte Kirch, Bündnis Entwicklung Hilft
Barbara Küppers, terre des hommes
Holger Mann, IFHV
Frank Mischo, Kindernothilfe
Peter Mucke, Bündnis Entwicklung Hilft
Tanja Pa zdzierny, Ki ndernothilfe
Ruben Prütz, Bündnis Entwicklung Hilft
Prof. Dr. Katrin Radtke, IFHV
Friederike Strube, terre des hommes
Daniel Weller, IFHV
In collaboration with
Rebekka Balser, Plan International
Christina Frickemeier, Plan International
Leopold Karmann, Bündnis Entwicklung Hilft
Dr. Matthias Lanzendörfer, Misereor
Oliver Neuschäfer, Christoffel-Blindenmission
Renée Rentke, Misereor
Rüdiger Schöch, Plan International
Graphic design and information graphics
Naldo Gruden, MediaCompany
ISBN 978-3-946785-06-4
The WorldRiskReport has been published annually
since 2011 by Bündnis Entwicklung Hilft
Responsible: Peter Mucke
Contents
Key Results ............................................................................................ page 6
1. The Situation of Children in Disasters ....................................................... page9
Peter Mucke
2. Focus: Child Protection and Children's Rights ........................................... page 15
2.1 The International Legal Protection of Children
in and after Disaster Situations ....................................................... page 15
Hans-Joachim Heintze
2.2 Most Disaster Victims are Children .................................................. page 26
Barbara Küppers, Frank Mischo, Tanja Pazdzierny, Friederike Strube
3. The WorldRiskIndex 2018 ...................................................................... page 35
Katrin Radtke, Holger Mann, Daniel Weller, Lotte Kirch, Ruben Prütz
4. Conclusions and Recommendations ....................................................... page 45
Bündnis Entwicklung Hilft
Appendix ............................................................................................... page 48
Bibliography ......................................................................................... page 54
In the summer of 2018, large parts of Europe
were groaning under an unusually hot spell.
Many places in Germany had no rain for weeks,
and the resulting drought caused considera-
ble harvest losses. Particularly among farmers
growing their own animal feed, the drought
led to bottlenecks and the premature selling
o of livestock to slaughterhouses at a signif-
icantly reduced price – a scenario that is also
familiar in typical drought regions such as the
Horn of Africa or the Sahel Zone. It was the
comparatively low vulnerability of the countries
aected by the drought that ultimately spared
Europe from disaster. This fact is also reect-
ed in the relatively low risk values of the coun-
tries concerned in the WorldRiskReport which,
compared to the previous years, has been calcu-
lated with a slightly modied concept.
The concept
Based on a mathematical concept, the World-
RiskIndex establishes a disaster risk value for
172 countries. This value provides an indication
of how high the risk is that a country will be
aected by a disaster due to an extreme natural
event in the future. The individual index values
are represented in the form of maps based on
a Geo-Information System (GIS), enabling the
comparison of countries with one another.
The model was developed in 2011 by scientists
from the Institute for Environment and Human
Security at the United Nations University in
Bonn and experts from Bündnis Entwicklung
Hilft and its member organizations (cf. Birk-
mann et al. 2011, Welle / Birkmann 2015). In
2017, the concept was revised and modied
slightly by scientists from Ruhr-University
Bochum and Bündnis Entwicklung Hilft sta in
order to take changing data situations and new
insights in risk analysis into account (cf. next
section).
The basic idea of the WorldRiskIndex is that
the occurrence of extreme natural events – e.g.
droughts, earthquakes, cyclones, etc. – is not
the only relevant factor to disaster risk, but that
societal factors are also responsible for wheth-
er a disaster develops in the context of extreme
natural events or not. Every society can either
directly or indirectly make preparations that
reduce the impact of natural hazards – for
example, with well-considered building regula-
tions, functioning emergency services, or mini-
mizing extreme poverty and inequality among
the population (Bündnis Entwicklung Hilft
2011).
Katrin Radtke,
Professor at the IFHV,
Holger Mann and
Daniel Weller,
Research Assistants at the
IFHV,
Lotte Kirch and
Ruben Prütz,
Staff members of Bündnis
Entwicklung Hilft
3 The
WorldRiskIndex 2018
The WorldRiskIndex states the disaster risk for 172 of the world’s countries.
The Index considers exposure to extreme natural events such as earth-
quakes or cyclones, and calculates a society’s capacity to respond to such
events. Vanuatu, Tonga, and the Philippines top the WorldRiskIndex list as
the countries with the highest disaster risk. Overall, Oceania has the highest
WorldRiskIndex values, followed by Africa, America, Asia, and Europe. The
overwhelming majority of the most vulnerable countries are in Africa. Nine
of the 15 countries bearing the highest risk worldwide are island states,
due, above all, to their high level of exposure. Island states are particularly
aected by sea-level rise, a consequence of global warming.
35
WorldRiskReport 2018
In order to understand the interaction between
natural events and social inuencing factors,
the Index is divided into two dimensions: expo-
sure and vulnerability. Exposure covers threats
due to extreme natual events, while vulner-
ability encompasses the societal sphere. The
WorldRiskIndex is the product of these two
dimensions.
Exposure means that a certain protected entity
(population, buildings, environmental areas) is
exposed to the impacts of one or more natural
events (earthquakes, cyclones, oods, droughts,
and sea-level rise).
Vulnerability consists of the following compo-
nents: susceptibility, lack of coping capaci-
ties, and lack of adaptive capacities (Bündnis
Entwicklung Hilft 2011), and relates to social,
physical, economic, and environmental factors
which make people or systems susceptible to
the impacts of natural hazards, the adverse
eects of climate change, or other transforma-
tion processes. Moreover, vulnerability covers
the abilities of people or systems to cope with
the negative impacts of natural hazards and
develop adaptation strategies. The way in which
vulnerability is used here refers to societies in a
more comprehensive sense.
A total of 27 indicators feed into the Index
that are calculated on the basis of data that is
available and publicly accessible worldwide.
The modular structure of the Index is shown in
gure 5.
The dierent components of vulnerability are
described in detail in the following:
Susceptibility is understood here as the like-
lihood of suering from harm in an extreme
natural event. Susceptibility describes the
structural characteristics and framework condi-
tions of a society.
Coping comprises various abilities of societies
to be able to minimize negative impacts of natu-
ral hazards and climate change through direct
action and the resources available. Coping
capacities encompass measures and abilities
that are immediately available to reduce harm
and damages in the occurrence of an event.
To calculate the WorldRiskIndex, the opposite
value, i.e. the lack of coping capacities, which is
the value 1 minus the coping capacities, is used.
Adaptation, unlike coping, is understood as a
long-term process that also includes structur-
al changes (Lavell et al. 2012; Birkmann et al.
2010) as well as measures and strategies deal-
ing with and attempting to address the negative
impacts of natural hazards and climate change
in the future. As with coping capacities, the lack
of adaptive capacities, resulting from the value
1 minus the adaptive capacities, is included in
the WorldRiskIndex.
Conceptual innovations and data 2018
In 2017 and 2018, the WorldRiskIndex was
revised on the basis of new insights. The basic
concept and the modular structure of the Index
have been retained, and changes have only
been made at the level of the indicators. The
modications are only in regards to exposure
and vulnerability, and enable more precise
and up-to-date statements to be made on the
risk values. The nal section explains how the
changes aect the comparability of individual
WorldRiskIndex volumes.
In the exposure component, the data set on the
number of total inhabitants of a country (which
up until now has been from the World Bank)
has been replaced by a data set (LandScan)
that is more accurate regarding the WorldRisk-
Index. One of the features of the new data set
is that it works with satellite images in order
to take the building density of regions into
account. Therefore, it can give more accurate
information on population distribution in indi-
vidual regions. In the WorldRiskIndex 2018,
this data set is also used to calculate the share
of people who are aected by sea-level rise in
a country (in past volumes, GRUMP 2010).
Particularly in coastal regions, this new base
has resulted in altered shares of the population
being exposed to sea-level rise and explains the
signicant changes in the risk values of some
of the countries. Thus, all population data sets
now originate from the same source, forming a
more consistent base for calculations as well as
greater precision. The population statistics used
in working out sea-level rise are from 2016. All
WorldRiskReport 2018
36
other forms of exposure have been calculated
on the basis of population statistics from 2010,
since this is modeled data from the “PREVIEW
Global Risk Data Platform” from the United
Nations Environment Programme (UNEP) and
more current data from UNEP was unavailable
at the time of calculation.
Five indicators in the area of vulnerability were
replaced by new ones. The other indicators have
been updated.
In the component of susceptibility, four of the
seven indicators have been updated:
C Share of undernourished population
D Dependency ratio
F Gross domestic product (in purchasing pari-
ties) per capita
G Gini Index.
Three indicators have been replaced because
they were no longer available in the previous
form:
A Share of the population without access to
improved sanitation has been replaced by
share of the population without access to
basic sanitation services
B Share of the population without access to an
improved water source has been replaced
by share of the population without access to
basic drinking water services
E Share of the population living on less than
1.25 US dollars a day has been replaced by
the share of the population living on less
than 1.90 US dollars a day.
The modications of the indicators are based
on changes resulting from the measurement of
Sustainable Development Goals.
In the area coping capacities, four of the ve
indicators have been updated:
A Corruption Perception Index
B Fragile States Index
C Number of physicians per 1,000 inhabitants
D Number of hospital beds per 10,000
inhabitants
The component adaptive capacities now only
consists of ten indicators, all of which have been
updated. Two indicators were replaced:
C Share of female students in education
institutions
D Share of female representatives in the
National Parliament
The new indicator chosen is the:
C Gender Inequality Index
The new indicator, the Gender Inequality Index,
is a value based on the following variables: the
maternal mortality rate, the adolescent birth
rate, the share of seats in the national parlia-
ment held by women, the share of women and
men with at least some secondary education,
and the labor force participation rate of males
and females.
37
WorldRiskReport 2018
Calculation of the WorldRiskIndex
Figure 5: Calculation of the WorldRiskIndex
Susceptibility
Public infrastructure
0.29 ×
Share of the population
without access to basic
sanitation services
× 0.5
Share of the population
without access to basic
drinking water services
× 0.5
Housing conditions*
Share of the population living in
slums; proportion of semi-solid
and fragile dwellings
0.1 ×
Nutrition
Share of the population that is
undernourished
Poverty and
dependencies
0.29 ×
Dependency ratio (share of
under 15- and over 65-year-
olds in relation to working
population)
× 0.50
Extreme poverty
population living with
USD 1.90 per day or less
(purchasing power parity)
× 0.50
Economic capacity and
income distribution
0.29 ×
Gross domestic
product per capita
(purchasing power parity) × 0.50
Gini index × 0.50
Exposure
Earthquakes
1.00 × Storms
Floods
+
0.50 × Droughts
Sea-level rise
÷
Population of the country
Population exposed to
Exposure
WorldRiskIndex = Exposure × Vulnerability
WorldRiskReport 2018
38
Coping
Government and authorities
0.45 ×
Corruption Perception
Index × 0.50
Fragile States Index × 0.50
Disaster preparedness and
early warning*
National disaster risk management
policy according to report to the
United Nations
Medical services
0.45 ×
Number of
physicians per 10,000
inhabitants × 0.50
Number of hospital
beds per 1,000
inhabitants
× 0.50
Social networks*
Neighbors, family, and self-help
0.10 ×
Material coverage
Insurance (life insurances
excluded)
Adaptation
Education and research
0.25 ×
Adult literacy rate × 0.50
Combined gross
school enrollment × 0.50
0.25 ×Gender equality
Gender Inequality Index
Environmental status /
Ecosystem protection
0.25 ×
Water resources
Biodiversity and
habitat protection
× 0.25
× 0.25
Forest management
Agricultural
management
× 0.25
× 0.25
Adaptation strategies*
Projects and strategies to
adapt to natural hazards and
climate change
Investitionen
0.25 ×
Public health
expenditure
Life expectancy at birth
× 0.33
× 0.33
Private health
expenditure × 0.33
Vulnerability
Vulnerability = ⅓ ×
(
Susceptibility +
(
1– Coping
)
+
(
1– Adaptation
))
* Not incorporated because of insufficient
availability of indicators.
Values of exposure and vulnerability, as well
as the WorldRiskIndex are given in percent.
39
WorldRiskReport 2018
Results of the WorldRiskIndex 2018
Risk
Vanuatu continues to be the country with
the highest disaster risk in the WorldRiskIn-
dex 2018. With Tonga, the Philippines, the
Solomon Islands, Papua New Guinea, Brunei
Darussalam, Fiji, Timor-Leste, and Kiribati, a
total of nine island nations are among the 15
countries with the highest risk.
In regards to continents, all in all, Oceania
(16.58) has the highest median of WorldRisk-
Index values, followed by Africa (8.31), Amer-
ica (7.11), Asia (6.11), and Europe (3.10). In
Africa, the hotspots are in Mauritius (rank 16),
Djibouti (rank 18), and Guinea Bisseau
(rank 19), while in Asia, in addition to the
island nations already mentioned, Bangladesh
(rank 9) and Cambodia (rank 12) also perform
very poorly. On the American continent,
Guyana (rank 5), Guatemala (rank 7), Costa
Rica (rank 11), and El Salvador (rank 14) have
the highest risk. Some European countries
are also in the “high risk” class. The risk of an
extreme natural event turning into a disaster
is especially high in Albania (rank 45) and the
Netherlands (rank 65). These two countries
are followed by Serbia, which falls into the
medium risk group, at rank 77.
Exposure and risk
When looking at the individual components
of the WorldRiskIndex, conclusions can then
be drawn more precisely regarding the causes
of risks. Seven of the island nations (Vanua-
tu, Tonga, Brunei Darussalam, the Philip-
pines, the Solomon Islands, Fiji, and Papua
New Guinea) and four further countries (Costa
Rica, Guyana, Guatemala, and El Salvador)
with very high risks are also among those
15 countries that are particularly exposed.
The island nations are particularly aected
by sea-level rise, as well as by cyclones and
earthquakes. Four further top risk countries
are among ranks 16-19 regarding exposure,
meaning that they are also highly endangered
by natural events. However, Japan, the Neth-
erlands, and Chile, which rank at 5, 13 and 14
respectively in terms of exposure, show that
even a very high exposure does not necessarily
imply a very high risk. Owing to their location
close to the edges of tectonic plates, Japan and
Chile are threatened in particular by earth-
quakes, while the Netherlands are particularly
aected by sea-level rise. Nevertheless, these
countries are at ranks 29, 65, and 28 in the
WorldRiskIndex.
Vulnerability and risk
The reason for the relatively good positions
of Japan, the Netherlands, and Chile in the
WorldRiskIndex is their low level of vulnera-
bility. Here, the three countries have very good
values. Japan and the Netherlands are among
the ten countries with the lowest vulnera-
bility worldwide. Chile is at least among the
50 countries with the lowest vulnerability. The
countries which have a very high risk do not
lead the list in terms of vulnerability. But they
are still so vulnerable that they cannot su-
ciently minimize the risks that may arise from
natural events. Coming in at number 20 in the
vulnerability ranking, Papua New Guinea has
the highest vulnerability among the high-risk
countries, followed by the Solomon Islands at
rank 39, Timor-Leste at rank 41, Cambodia at
rank 42, and Kiribati and Vanuatu at ranks
44 and 45. As the World Map of Vulnerability
shows in the appendix, the hotspots of vulner-
ability are in the Sahel Zone and the tropical
regions of Africa. A total of 13 out of the 15
most vulnerable countries are in Africa. The
Central African Republic, Chad, Niger, Eritrea,
and Guinea Bissau are particularly vulnerable.
Only two countries outside Africa, Haiti and
Yemen, are comparably vulnerable.
Susceptibility
The African continent is not only the hot-spot
in terms of vulnerability in general, but also in
terms of susceptibility, a component of vulner-
ability. Susceptibility is particularly high in the
Central African Republic, Eritrea, Madagas-
car, Mozambique, and Chad. Here, dierent
patterns emerge. Whereas, for example, Chad
WorldRiskReport 2018
40
has extremely poor values for the indicators
“basic sanitation services,” “basic drinking
water services,” “undernourishment,” and
particularly in regards to the “dependency
ratio,” the country does comparatively well
in terms of “extreme poverty,” “per capita
gross domestic income,” and the indicator
on “inequality” (valued with the Gini Index),
and fares better than the bottom ten per cent.
Nevertheless, Chad ranks fth in terms of
susceptibility. The situation is the other way
around in Malawi. This country does compar-
atively well in several indicators (basic sani-
tation services, basic drinking water services,
undernourishment, and inequality), and here,
it does not belong to the bottom ten per cent
of the countries in the WorldRiskIndex. In the
indicators “extreme poverty,” “dependency
ratio,” and “gross domestic product per capi-
ta,” however, the country fares so badly that it
is in rank 11 in terms of susceptibility. Other
countries, such as the Central African Repub-
lic, Eritrea, and Madagascar have very poor
values in almost all indicators.
Lack of coping capacities
The lack of coping capacities is less clearly
concentrated on the African continent. With
Afghanistan, Haiti, Iraq, and Syria, other
countries are also represented among the top
15 that belong to Asia or America. Yemen,
Afghanistan, Chad, the Central African Repub-
lic, and Haiti show the greatest lack of coping
capacities. In this group, it is notable that all
countries, with the exception of Haiti, have
all either been involved in a civil war or are
post-civil war countries. Especially in the
indicators “Corruption Perception Index”
and “Fragile States Index,” these countries
also perform poorly. Healthcare appears to
perform better. Here, at least, Syria and Iraq
are in the middle eld in terms of physicians
per inhabitants and the number of hospi-
tal beds. Although Yemen generally has poor
values, it does not belong to the bottom 20 per
cent of the countries in the WorldRiskIndex in
regards to these two indicators. However, the
fact that these countries provide more hospital
beds and physicians per inhabitant does not
necessarily mean that in this case, healthcare
meets the high demand resulting from civil
war. It is also quite possible that the values will
signicantly change in the course of the next
assessment owing to the civil war.
Lack of adaptive capacities
The countries with the lowest adaptive capaci-
ties are Niger, Yemen, Liberia, Chad, and Mali.
Alongside numerous countries in sub-Saharan
Africa, various countries in South and South-
east Asia also show a high to very high lack
of adaptive capacities. Niger’s especially poor
results are, above all, due to the low literacy
rate and low level of educational participation.
Also in terms of gender equality, public health
expenditure, and life expectancy, the country is
among the bottom ten per cent of the countries
in the WorldRiskIndex. However, in regards to
biodiversity (rank 55), forest (rank 123), and
agricultural management (rank 131), Niger
fares better in comparison. This also applies to
the majority of the other 15 countries with the
lowest adaptive capacities. Here, especially in
the indicator on agriculture, only Haiti belongs
to the ten per cent of countries with the poor-
est value. All other countries have much better
values. For example, Mali, at rank 79, and
Chad, at rank 93 in regards to the indicator
of agricultural management, belong to the
middle eld.
Options and limitations of the Index
Generally, working with indices always has
advantages and disadvantages. The fact that
the WorldRiskIndex oers the possibility to
reduce an extremely complex state of aairs to
a single value allows decision-makers to orient
themselves swiftly and also makes the Index
a valuable tool in public relations activities.
At the same time, however, owing to the high
level of abstraction, the complexity of disas-
ters is eclipsed. Thus, valuable information for
practitioners can also be lost.
A further problem results from the availa-
bility of data, as corresponding, up-to-date
sets of data do not exist for all 193 countries.
Owing to an increased amount of missing
data, the countries Andorra, Antigua and
Barbuda, the Democratic Republic of Congo,
Dominica, North Korea, Liechtenstein, the
41
WorldRiskReport 2018
How exposure and vulnerability interact
The WorldRiskIndex (WRI) is the product of the
exposure and vulnerability of a society towards natural
hazards. Every dot represents a country. The color of
the dot indicates the class (very high / high/ medium /
low / very low) the country belongs to. The country with
the highest / lowest value in the WorldRiskIndex 2018 is
highlighted for every world region.
Figure 6: WorldRiskIndex by geographical location
Exposure
very low 1.02– 9.53
low 9.54– 11.70
medium 11.71– 14.50
high 14.51– 17.73
very high 17.74– 86.46
very low 20.97– 32.01
low 32.02– 40.77
medium 40.78– 48.60
high 48.61– 63.00
very high 63.01– 76.47
Vulnerability
020 40 60 80
0
20
40
60
80
Qatar
WRI 0.36
1.02
35.48
Mauritius
WRI 14.27
37.22
38.35
Vulnerability
Exposure
Africa
020 40 60
80
0
20
40
60
80
Grenada
WRI 1.39
3.27
42.70
Guyana
WRI 23.23
45.56
50.98
Vulnerability
Exposure
America
020 40 60 80
0
20
40
60
80
Australia
WRI 4.41
17.81
24.77
Vanuatu
WRI 50.28
86.46
58.15
Vulnerability
Exposure
Oceania
020 40 60
80
0
20
40
60
80
Malta
WRI 0.57
1.84
31.02
Albania
WRI 9.22
22.83
40.38
Vulnerability
Exposure
Europe
020 40 60 80
0
20
40
60
80
Israel
WRI 2.20
6.76
32.55
Philippines
WRI 25.14
49.94
50.33
Vulnerability
Asia
Exposure
WorldRiskReport 2018
42
Maldives, Monaco, Montenegro, Nauru, the
Federated States of Micronesia, the Marshall
Islands, Palau, St. Kitts and Nevis, St. Lucia,
St. Vincent and the Grenadines, San Mari-
no, São Tomé und Principe, Somalia, South
Sudan, and Tuvalu could not be considered in
the WorldRiskIndex. This also applies to the
territories not fully recognized inter nationally:
Kosovo, Palestine, and Taiwan. The data on
the Vatican State was assigned to Italy, and
data of overseas territories, as far as possible,
to the respective country (e.g. the population
statistics of French Guyana have been added to
those of France). Since not all of the data sets
clearly indicated how these assignments were
made, inaccuracies cannot be entirely ruled
out in this matter.
Complete data is available for many of the
countries contained in the Index. For the
countries with only a small amount of miss-
ing data, plausible values have been estimat-
ed as a substitute with the aid of statistical
methods (see data sheet). The replacements
used contain uncertainties in interpreta-
tion. Owing to some of the indicators having
been replaced, a comparison of the individu-
al WorldRiskReport volumes is only possible
for those parts in which no changes have been
made. In order to be able to draw comparisons
between the years, the previous values of the
indicators that have been replaced would have
to be incorporated in the calculation of the
indices from previous years.
Another problem that needs to be considered
results from applying the quantile method, in
which the countries of the WorldRiskIndex are
divided into ve classes and assigned a corre-
sponding color code. These classes always
contain exactly 20 per cent of the countries
considered in the WorldRiskIndex. The level of
disaster risk can then be recognized on maps
at a glance. However, the classes the countries
belong to may change without fundamental
changes in their values because the values of
other countries have changed, causing a corre-
sponding shift in the class borders.
Conclusion
All in all, the WorldRiskIndex 2018 conrms
the most important results of the previous
years. Disaster risks are unevenly distribut-
ed, and they mostly aect island nations and
countries with low and medium income in
Oceania, Asia, and Central America.
The Index shows that it is possible to reduce
disaster risks by eliminating susceptibility and
developing good coping and adaptive capaci-
ties. Two highly exposed countries, Japan and
the Netherlands, have achieved this particu-
larly eectively. At the same time, they gure
among the world’s 20 richest countries.
The WorldRiskIndex 2018 also unequivocally
de mon strates that island nations such as Vanu-
atu, Tonga, and the Solomon Islands are unable
to reduce the disaster risk without external
support. Even if they were capable of reducing
their vulnerability to a considerable degree,
their risk value would remain in the high or very
high area owing to their very high exposure. For
these countries, changes regarding their expo-
sure are also essential. Theoretically, sea-lev-
el rise, storms, and oods in particular, all of
which especially aect island nations, could
be reduced, since they are inuenced by glob-
al warming. However, the political will among
many industrial nations to implement the
measures required to achieve the aims of the
Paris Agreement is still not suciently recog-
nizable. Thus, the countries threatened by natu-
ral hazards have fallen into a trap from which
they cannot break free on their own.
43
WorldRiskReport 2018
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Bibliography
Photo credits:
Cover picture: A boy playing in the floodwaters after the
River Kampar burst its banks in Buluhcina, Indonesia ©
Afrianto Silalahi / Barcroft Images
Page 8: A boy learning first aid techniques at the Children’s
Disaster Preparedness Camp in Daram, Philippines © Plan
International
Page 11: Children rehearsing circus tricks in the facilities of
the Serua Organization, Rio de Janeiro, Brazil © Thomas
Lohnes / Brot für die Welt
Page 14: Children showing pictures they have painted of
their dream school, Ramechhap region, Nepal © Sonja
Eberle / Welthungerhilfe
Page 20: Plan International staff guiding children taking
part in an activity at the Child Protection Center, Manabí,
Ecuador © Gonzalo del Valle
Page 24: Qiang Summer Camp, China © Misereor
Page 32: Students and teachers attending a school drill,
Shreepur, Bangladesh © Fahad Kaizer / CBM
Page 34: People near a watering place in the village of
the Rendille / Samburu in Kenya who are about to receive
fresh drinking water from a water tanker. © Christof
Krackhardt / Brot für die Welt
Page 44: Girl at a relief shelter in the province of Manabí,
Ecuador © Fabricio Morales / Plan International
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