Preliminary Analysis
The One Billion Coalition for Resilience Discussion Paper on Levels of Resilience
March 2015
Purpose of this document As an initial step, this document describes aspects of resilience based on publically available data This document presents our initial ideas about how resilience varies between countries. The purpose this is to enable the identification of data gaps required to understand the current levels of household and community resilience. This preliminary mapping uses publically available data and builds on the work of other institutions such as the Group URD, the Organisation for Economic Co-operation and Development (OECD), Rockefeller Foundation, and the United Nations Development Programme (UNDP), among others. The information here will be complemented with additional analysis and data collection over the coming months as we work with partners to co-create the One Billion Coalition. This includes working with the National Red Cross and Red Crescent Societies and our volunteer network to better describe local needs and working with our international partners to better define how the coalition will support resilience through for example, identifying potential models for building coalitions.
Preliminary Analysis
We do not consider this preliminary mapping exercise to be perfect or complete. As with any attempt to measure a complex concept such as resilience, we acknowledge that there are limitations to our approach. First, resilient communities require a combination of many different assets and this approach looks at each dimension in isolation. Second, this approach does not adequately consider local preferences or incorporate risks that are specific to different environments. Third, by relying on country-level indicators, subnational variance is masked.
Mapping Process Overview Develop initial mapping based on public data
Engage our partners to refine indicators
Supplemental data collection through IFRC National Societies and coalition partners
February to March
March to April
April to May
Identify indicators to describe resilience and gather publically available data
Update indicators to confirm that we capture relevant aspects
Collect additional information from IFRC National Societies and partners
We are actively looking for partners to join and improve this exercise
Source: Dalberg analysis
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One Billion Coalition for Resilience Ensuring collective responsibility, collective action and collective accountability by all, for all In November 2014, the IFRC introduced the “One Billion Coalition for Resilience,” an initiative designed to scale-up community and civic action on resilience. Within the next 10 years, the goal is to engage at least one billion people in every household around the world in active steps towards strengthening their resilience. This is the IFRC’s voluntary commitment toward the post-2015 framework for disaster risk reduction and Sustainable Development Goals. Our way forward calls for collaboration and partnership amongst a wide range of like-minded actors including public authorities, the private sector, schools and universities. The coalition will improve the flow of resources to programmes and initiatives on the ground and will bring greater learning through the sharing of knowledge, experience and ideas to address common problems.
Preliminary Analysis
The coalition will ensure communities are able to make choices that build their resilience that fit with local needs and can draw on local resources. It will be designed to help communities and households build resilience across a wide range of areas, including: first aid and preparedness training, strengthening local institutions and early warning systems, pandemic preparedness and improving access to health and water and sanitation. Focus will also be on supporting public authorities to adopt strong legal frameworks on disaster risk reduction.
Call to Action • We call upon all stakeholders to join us in this co-creation process; ensuring collective responsibility, collective action and collective accountability by all and for all, in enabling individuals, households and communities to become stronger and safer. • Through our network of 17 million volunteers and 189 National Societies reaching tens of millions of people through disaster preparedness, risk reduction, access to water and food, early warning, community health and livelihoods programmes, the IFRC is committed to making decisive actions and contributions from local to global, through this “One Billion Coalition for Resilience” initiative.
Source: International Federation of Red Cross and Red Crescent Societies
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Dimensions of resilience We propose considering six different dimensions of resilience Each dimension groups together indicators that describe resources and risks that can either contribute to or hinder community resilience. We selected these dimensions based on input from our partners, reflection about how the National Red Cross and Red Crescent Societies can contribute, and data availability. We offer them as an initial contribution to building a common language and welcome feedback and comments on how to improve the definition and measurement of these dimensions in the future.
Financial Capital
Human Capital
Natural Capital
Physical Capital
Social Capital
Governance Systems
Preliminary Analysis
The dimensions – five capitals and one broader context – describe the vulnerabilities and risks that contribute to or hinder community resilience. • Financial capital includes access to financial capital including stable revenue streams as well as international assistance following a disaster; it is a critical mechanism for absorbing the impact of sudden shock. • Human capital includes formal education and informal training in essential life skills, such as first aid and road safety; it allows people to survive unexpected events and rebuild their lives following catastrophe. • Natural capital is the level and quality of natural assets including: atmosphere, biodiversity, water, land and forest; it is vital for the provision of ecosystem services, such as crop pollination and clean water, which humans need to survive. • Physical capital is the provision of and access to: services, infrastructure and resources necessary for human survival; examples include: clean water, food, healthcare and shelter. • Social capital refers to the prevalence of social norms including violence and child employment as well as to the networks within each society which provide support to people; examples include: families, friends, volunteer networks and community groups. • Governance systems includes all of the laws, regulations and organisations on an international, national and local level that affect a society.
Source: Dalberg analysis
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Indicators of Resilience We propose the following initial indicators to measure and describe components of resilience Financial Capital
Means to Cover Basic Needs • Proportion of the population living for under $1.25 a day (World Bank) • Population coverage rate of social insurance programmes (World Bank) • Population which has an account at a formal financial institution (World Bank) • Proportion of the female population with an account at a formal financial institution(World Bank) Availability of International Assistance • Average aid received 2008-2014 (OECD)
Human Capital
Preliminary Analysis
Formal Education and Vocational Training • Literacy rate for adults (World Bank) • Primary school net attendance rate (UNICEF) • Proportion of secondary school pupils enrolled in vocational programmes (World Bank) Informal Training • Number of people who are informal recipients of health programmes (IFRC)
Natural Capital Environmental Conservation • Population exposure to air pollution (GGGI) • Total area of renewable internal freshwater resources per capita (World Bank) • Average carbon content in the topsoil (% of total weight) (FAO) • Combustible renewables and waste (% of total energy) (World Bank) • Global Environmental Facility benefits index for biodiversity (World Bank)
Physical Capital Access to Infrastructure • Proportion of the population with access to electricity (World Bank) • Proportion of the population with mobile phone subscriptions (World Bank) • Proportion of the population with access to improved sanitation facilities (World Bank) • Proportion of the population with access to a clean water source (World Bank) • Food production index (FAO) Access to Services • Health expenditure per capita (World Bank) • Nurses and midwives per capita (World Bank) Drivers of Vulnerability • Proportion of the population made homeless by natural disasters (CRED) • Proportion of the population which are undernourished (FAO)
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Proposed Indicators (cont.) Social Capital Principles and Values • Proportion of children in employment (World Bank) • Prevalence of sexual violence among 15-19 years olds (UNICEF) • Proportion of men who consider a husband to be justified in hitting or beating his wife (UNICEF) • Proportion of women who were first married or in union before the age of 18 (UNICEF) Links and Social Networks • Proportion of the population who are an active member of a community group (WVS) • Percent of the population volunteering for any kind of organization (IFRC) • Number of people volunteering for the National Red Cross and Red Crescent Societies (IFRC)
Governance Systems
Preliminary Analysis
Participation in politics • Percent of the population who vote in national elections (World Values Survey) • World Justice Project Overall Score (World Justice Project) Policy and Planning for Disasters • Priority given to disaster risk reduction within legislation (IFRC and UNDP) • Score on the Disaster Risk Reduction Progress Scale (World Bank)
Process for Aggregating Indicators Based on these indicators, we generated standardized scores for each country and dimension of resilience using publically available data. To calculate these scores we first normalized all of the indicator by calculating the percent rank of each country and indicator. Second, we aggregated the multiple indicators that make up a dimension by calculating the mean of the percent ranks. As a final step, we normalized these average scores for each country by calculating the percent rank again. Using these scores, we grouped countries into different quintiles to identify where specific aspects of resilience are more and less relevant. Importantly, classifying a country in the top quintile does not mean that all individuals and communities within the country are resilient. There is significant variation within countries that is not captured with this approach. Furthermore, it weighs all indicators within a dimension equally.
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Major Findings The need to enhance resilience is not confined to specific countries or regions • With the exception of social capital, less than 21% of the world’s population live in countries with the highest level of resilience. • Over 50% of people live in countries with the lowest levels of physical capital or governance systems. • Over 1.3 billion people live in countries in the lowest two quintiles of financial capital meaning that there are high levels of poverty and a lack of access to financial institutions. Countries in this category are predominantly concentrated in Sub-Saharan Africa and South East Asia. • Over 1.2 billion people live in countries in the lowest two quintiles of human capital meaning that they have low access to formal education and training in life skills. The concentration of these people is in Africa and Southern Asia.
Preliminary Analysis
• Over 1.2 billion people live in countries in the lowest two quintiles of natural capital meaning there is low quality of the country’s natural assets, for example water and forest. Countries in this situation are predominantly found in North Africa, Europe, Central Asia and the Middle East. • Over 4.6 billion people live in countries in the lowest two quintiles of physical capital meaning that they lack access to basic services, infrastructure and resources. These people are concentrated in Sub-Saharan Africa and Southern Asia. • Over 2.6 billion people live in countries in the lowest two quintiles of social capital meaning there is a prevalence of social norms such as violence against women and child employment and/or weak social networks. The lowest levels of social capital are in Africa, Eastern Europe and countries with high populations such as China, Russia and Brazil. • Over 3.8 billion people live in countries in the lowest two quintiles of governance systems meaning that laws, regulations and organisations are negatively affecting society. Countries in this category are concentrated in Asia and Sub-Saharan Africa.
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Distribution of Resilience In general, less than 21% of the world’s population live in countries with the highest level of resilience
Preliminary Analysis
The chart below shows the percent of the world’s population found in countries within each quintile of the capitals. Quintiles with large percentages of the population tend to have more than 30 countries included in them and include countries with large populations (e.g., China and India). • Fifth Quintile (highest level of resilience): This quintile contains under 21% of the world’s population with the exception of human capital which contains 45% of the world’s population but includes Russia and China which have a large number of people who are literate. • Fourth Quintile: This quintile contains less than 20% of the world’s population with the exception of social and financial capital where more than 30% of the world’s population is found and also more than 30 countries in the quintile. • Third Quintile: This quintile contains less than 14% of the world’s population for physical capital, social capital and governance systems. However for human, natural and financial capital there are more than 30 countries in the quintile and between 28-48% of the world’s population. • Second Quintile: This quintile contains between 10-34% of the world’s population with the exception of physical and governance systems where a large number of countries with high populations (e.g., China and India) mean that nearly 50% of the world’s population is included. • First Quintile (lowest level of resilience): This quintile contains between 4-17% of the world’s population and for all capitals except natural capital contains a large proportion of the countries in Sub-Saharan Africa. Geographic distribution within each capital is further discussed below. Population-Weighted Distribution of Resilience, 2013 Percent of World Population Fifth Quintile (Highest Resilience) Fourth Quintile Third Quintile
Second Quintile
First Quintile (Lowest Resilience)
7% 18% 9%
13%
11%
21%
16% 14%
39%
32%
44%
19%
10%
10%
48%
16%
32%
47%
48% 28%
34% 17%
Physical Capital
10%
Governance Systems
15%
10%
13%
4%
4%
7%
5%
Social Capital
Financial Capital
Human Capital
Natural Capital
Source: See annex for list of data sources for indicators; Dalberg analysis.
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Distribution of Resilience and Income Low income countries typically have the least resilience, but there are significant exceptions Depending on the dimension, there are between one and four and half billion people living in countries with the lowest levels of resilience and between one and a half and four billion people living in countries with the highest levels of resilience.
Preliminary Analysis
• Among people who live in countries with high levels of resilience, more than 30% come from high income countries for most dimensions, with the exception of physical capital where it is nearly 70% of the population. This dramatic change reflects our expectations for physical capital: countries in the highest two quintiles of resilience have over 90% coverage of key services. • However, there are significant needs in high income countries. For financial, human, physical and governance systems, more than 45% of the population with the lowest levels of resilience are from high income non-OECD countries. This is likely to be because countries with large populations, such as Russia, are classified as high income non-OECD and are often in the bottom two quintiles. • For social capital, more than 60% of the population with the highest level of resilience are found in countries classified as lower middle or low income. This may be because of relatively high levels of volunteering and often low levels of negative social norms such a child labor. • Natural capital is more evenly distributed with people living in high income OECD countries representing 15% of people living in countries with the lowest levels of natural capital. This is likely to be because less industrialized countries, such as those in Sub-Saharan Africa tend to have a higher quality of natural assets such as forest and water. Population-Weighted Distribution of Population in Countries with Lowest and Highest Levels of Resilience, by Income Group, 2013 Percent of world population and number of people (millions) High income: OECD
Upper middle income
High income: nonOECD
Lower middle income
Highest Levels of Resilience (top two quintiles) 3,460 3,870 2,376
30%
27% 4% 26%
1,767 3,717 1,935
5%
57%
7% 21% 56% 0%
26%
62%
10% 53%
31%
2%
1%
32%
Lowest Levels of Resilience (bottom two quintiles) Financial Capital
0% 12%
Human Capital
1% 15%
Natural Capital
12% 22% 10% 0% 60% 4% 12%
Low income
28%
Physical Capital
17%
Social Capital
20%
Governance Systems 10%
1%
Source: See annex for list of data sources for indicators; Dalberg analysis.
0%
1,269
3% 0% 46% 5% 29% 6% 23% 15%
1,171
2% 2% 46%
30%
65%
34% 0%
49% 0% 7% 5%
4,588
3%
2,609
0%
3,831
66% 41%
4%
1,245
45%
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Financial Capital Over 1.3 billion people live in countries in the lowest two quintiles of financial capital Relative Levels of Financial Capital
Highest quintile
Lowest quintile
Preliminary Analysis
No Data People with access to sustainable and stable sources of income are more resilient. To create resilient communities, individuals and households must have the means to address their basic needs and have access to financial institutions to provide support following shocks. The lowest levels of financial capital are found in Sub-Saharan Africa and South East Asia, where there are high levels of poverty and limited access to financial institutions. For example, in the Democratic Republic of Congo nearly 88% of the population, or over 48 million people, lived under $1.25 (Purchasing Power Parity) a day in 2006. In 2011, over 96% of the population, or nearly 60 million people had no access to a formal financial institution. Importantly, country averages obscure disparities within countries. Millions of people who live in countries with high levels of resilience face considerable vulnerabilities and risks. In the United Kingdom, for example, 1% of the population, or over 600,000 people, live under $1.25 a day (Purchasing Power Parity) (2010 data) and nearly 3% of the population, or over 1.7 million people, did not have an account at a formal financial institution (2011 data). How does the IFRC contribute today? The IFRC provides financial aid in response to emergencies either through funding direct emergency assistance to people including via blankets, food and clean water; as well as though direct cash assistance and livelihoods programmes. For example, in 2013, emergency assistance was provided to people in Kazakhstan when winter temperatures reached -46oC; in Sudan in response to conflict, natural disasters, epidemic outbreaks and chronic food insecurity; in Syria and surrounding countries in response to the ongoing crisis; and in the Philippines after Typhoon Haiyan. In Jordan for example, a cash programme was launched to help Syrian families registered as refugees which provides money on a monthly basis to families to enable them to cover their most basic needs including rent and household items. Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; Dalberg analysis.
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Human Capital Over 1.2 billion people live in countries in the lowest two quintiles of human capital Relative Levels of Human Capital
Highest quintile
Lowest quintile
Preliminary Analysis
No Data Formal education and informal education programmes are vital contributors to resilience. In addition to skills that people require on a daily basis, such as literacy; vocational training and targeted programmes around first aid and road safety help individuals, households and communities respond to shocks. With the exception of Africa and Southern Asia, most of the world has high levels of human capital, or a high percentage of the population with access to formal education and training in essential life skills. Nevertheless, there is a great need to improve levels of human capital even in countries which came out with the highest levels of human capital. While 96.6% of primary school age children attend school and 95.1% of adults are literate in China, we still need to enhance life skills around key issues such as road safety and first aid (2010 data). In 2010 there were an estimated 300,000 road traffic deaths (20.5 per 100,000 population) in China. An example of low levels of human capital can be seen with the country of Niger in SubSaharan Africa where in 2012, 84% of the population were illiterate, this is the equivalent of over 14.5 million people. How does the IFRC contribute today? The IFRC supports awareness activities on disaster preparedness and life saving skills including first aid and road safety; through events such as World First Aid Day, publications such as the Disaster Resilience Journal and the provision of education through its volunteer network. For example, in the town of Aliputos in the Philippines no lives were lost in Typhoon Haiyan despite all houses being damaged due to the awareness raising efforts of the local National Red Cross Society branch. Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; WHO Global Status Report on Road Safety (2013); Dalberg analysis.
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Natural Capital Over 1.2 billion people live in countries in the lowest two quintiles of natural capital Relative Levels of Natural Capital
Highest quintile
Lowest quintile
Preliminary Analysis
No Data Conserving and enhancing natural capital stocks on a global, national and local level is fundamental for communities around the world to increase their resilience. South America, Sub-Saharan Africa, North America and Oceania have the highest quality of natural assets such as land, water supply and forest cover. Brazil is the only country in the world with a perfect score on the Biodiversity Index, this means that it has the maximum biodiversity potential based on the species that exist, their threat status and the diversity of habitats in the country. Brazil also has a low level of air pollution with an average of 5.1 micrograms emitted per capita in 2012. In addition Brazil has high levels of renewable internal freshwater resources with over 28 thousand cubic meters per person in 2013. Nevertheless, Brazil’s natural capital faces considerable threats. The forest area in Brazil declined by 0.5% per year between 2000 and 2012, the equivalent of over 300,000 square kilometers, an area the size of Italy. Countries with the lowest levels of natural capital – primarily in North Africa, Europe and the Middle East – face even greater challenges. Kuwait, for example, had the lowest score on the biodiversity index in the Middle East (2008), emitted 18.9 micrograms of pollution per capita (2012), and had zero cubic meters of water per capita (2013). How does the IFRC contribute today? The IFRC works with other international organisations and countries around the world to conserve and enhance natural capital stocks through cross cutting disaster risk reduction and adaption programmes. In Vietnam the National Red Cross Society has invested in mangrove forest regeneration since 1994 to provide natural protection to communities from typhoons and storms. Also the IFRC seeks to address climate change and its impact by partnering with organisations such as the World Meteorological Organization and local meteorological offices to make climate information relevant to end users. Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; Deforestation data from World Bank Data Bank; Dalberg analysis.
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Physical Capital Over 4.6 billion people live in countries in the lowest two quintiles of physical capital Relative Levels of Physical Capital
Highest quintile
Lowest quintile
Preliminary Analysis
No Data People need consistent access to basic services and resources on a daily basis in order to survive. There is a key role to be played by international and local organization to ensure that the most vulnerable are provided for after shocks. The access to and provision of basic services, infrastructure and resources, for example water, food and healthcare, are at the lowest levels in Sub-Saharan Africa and Southern Asia, and the highest levels in Oceania, Europe and North America. Countries with the lowest levels of physical capital have very low levels of access to sanitation and electricity as demonstrated by Chad where, in 2012, 97% of the population, or over 12 million people, had no access to electricity and nearly 11 million people had no access to sanitation. This is contrasted to the countries in the two highest quintiles of physical capital which have over 90% of the population with access to sanitation and electricity. How does the IFRC contribute today? The IFRC provides humanitarian aid and assistance to vulnerable people after shocks through the global network of National Red Cross and Red Crescent Societies. For example in 2013, the IFRC restocked clinics in Syria and the Kenyan Red Cross Society provided medical assistance and psychosocial support to the victims of the Westgate Shopping Mall attack in Nairobi. Another example is the Global Water and Sanitation Partnership through which the IFRC provides sustainable water and sanitation solutions to communities around the world, for example the IFRC with the Norwegian Red Cross has installed a water and sanitation disaster response kit in the Adjumani District of Uganda to enable the support of 5000 South Sudanese refugees with safe drinking water and basic sanitation facilities.
Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; Dalberg analysis.
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Social Capital Over 2.6 billion people live in countries in the lowest two quintiles of social capital Relative Levels of Social Capital
Highest quintile
Lowest quintile
Preliminary Analysis
No Data Social capital includes social norms and the existence of networks in society. To be resilient communities need to foster strong connections and networks which in some circumstances require resourcing or support to function effectively. The lowest levels of social capital are in West and South Africa and Eastern Europe with the highest levels in North America, Western Europe, Central Asia and Oceania. Countries with the lowest levels of social capital have a small percentage of the population who volunteer for any kind of organisation (2012 data). For example in Latvia only 9% of the population volunteer and in Burkina Faso only 8% do so. This is contrasted to a country with the highest levels of social capital, for example Canada which had over 40% of the population volunteering. However in countries with low levels of social capital in West and Southern Africa, in addition to low levels of volunteering, there is also a high prevalence of negative social norms such as violence against women and child labor. For example, in 2010 Burkina Faso had over 50% of children employed, or 3.6 million children if this is assumed to be children under 14. How does the IFRC contribute today? The IFRC and National Red Cross and Red Crescent Societies play a convening role of connecting the most vulnerable people with resources, organisations and authorities at a local and global level. For example, more than 17 million volunteers worldwide are used to provide resources and direct support to vulnerable people. One example of this is in April 2013 when the National Red Cross Society of China mobilized 400 staff and volunteers to assist those affected by a 7.0magnitude earthquake which hit Lushan County in Sichuan Province, China. The IFRC also connects people through social engagement through platforms such as “Your Voice�, a dedicated space for people to express their hopes and aspirations for the future on a local, national and global scale. Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; Dalberg analysis.
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Governance Systems Over 3.8 billion people live in countries in the lowest two quintiles of governance systems Relative Levels of Governance Systems
Highest quintile
Lowest quintile
Preliminary Analysis
No Data Governance systems include all the laws, regulations and organisations affecting a society. The quality and enforcement of the laws, regulations and institutions affect the safety and wellbeing of people and so therefore their resilience. International standards and support to countries to have effective laws is vital for improving resilience. The lowest levels of governance systems are in Asia and Sub-Saharan Africa (where data exists) with the highest levels in North America, Europe, Oceania and South America. The Rule of Law Index from the World Justice Project measures how the rule of law is experienced in everyday life around the world. For example in 2014, Russia was ranked 80/99 on the Rule of Law Index as it got an overall score of 0.45 (scores range from the lowest score of 0.3 to the highest score of 1) and received a low score for criminal justice, constraints on government power and levels of corruption. How does the IFRC contribute today? The IFRC and National Red Cross and Red Crescent Societies work with other international organisations and with governments around the world to improve disaster related legislation and to help governing bodies to reduce risk and strengthen disaster preparedness and response. For example, in 2014 the IFRC and UNDP together launched a comparative study on effective law and regulation for disaster risk reduction and discovered that many legal gaps remain especially in sectors outside emergency management. As a result of this the IFRC and UNDP have developed a Checklist on Law and Disaster Risk Reduction to provide practical guidance to countries wishing to strengthen their laws and regulations, in accordance with the Post-2015 Framework for Disaster Risk Reduction. The IFRC is also providing direct support to governing bodies through activities including assessing and mapping urban risk and monitoring the implementation of community-based disaster risk reduction measures. Note: Levels of resilience for each country were determined by calculating the average percentile rank for the indicators that make up a capital. Source: See annex for list of data sources for indicators; IFRC website; IFRC 2013 Annual Report; Disaster Resilience Journal; Your Voice website; World Justice Project;Dalberg analysis.
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Looking forward – Tailoring Resilience to Local Contexts Resilience needs vary from place to place and from individual to individual; one-size fits all approaches cannot work. Instead, the One Billion Coalition will offer a menu of options for initial actions toward resilience and work closely with both local and international partners. The One Billion Coalition Change Model outlines how we anticipating working together with our partners to enable one billion households to take active steps towards safety and resilience by 2025. • Supporting services can be provided by a range of organisations and institutions. Each actor brings their specific strengths and capabilities and all are needed to meet the goal. We proposed the activities below as ideas of how international and local organizations can contribute. • We will engage with individuals, households and communities across many different activities. Communities will determine what activities can contribute to building resilience and how we can contribute. • The “links to action” show that there are six different dimensions which contribute to the resilience of a household (see page 4 for further information).
Preliminary Analysis
One Billion Coalition Change Model Goal
One billion households taking actions toward safety and resilience by 2025
Links to action
Financial Capital
Household and community engagement (indicative examples)
Supporting services Global coalition
Human Capital
Support Provide First family Aid training disaster plans Enable business continuity planning
Social Capital
Combat noncommunicable disease
Improve Support school safety road education safety
Household and small business level
Situation Assessments and Data Collection National Societies National governments
Awareness Raising and Advocacy
Physical Capital
Natural Capital
Governance Systems
Map Strengthen civic capacities engagement
Tap local and external resources
Facilitate collectivedecision making
Create local solutions to promote health & safety
Organize local campaigns
Community-level Peer Learning and Training
United Nations Local governments
Civil society
Financing and Creating Incentives Academia
Business community
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Building an effective coalition We need partners to join us to scale-up community and civic action on resilience
If you are interested in joining the One Billion Coalition for Resilience or would like more information, please email us at Onebillioncoalition@ifrc.org.
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Preliminary Analysis
We envision a demand-driven, community-led approach that builds on local networks and considers multi-sector contributions to enhancing resilience. The One Billion Coalition will engage a wide set of partners. We invite individuals, families and communities, civil society organisations and National Red Cross and Red Crescent Societies, local, national, and international authorities, and the business community to join us to take active steps to enhance individual, household, and community resilience. We are committed for example to identifying and collecting better data. This includes information at a subnational level as well as new indicators that describe the situation for local communities. As an immediate next step, we hope to complement the information collected from public sources with additional data collection through the National Red Cross and Red Crescent Societies and our volunteer networks. By considering both global indicators and more localized information collected from our communities, we will continue to identify and support local needs through engagement activities. In addition to collecting better information, we want to work alongside our partners to strengthen each dimension as a building block to enhancing resilience. • To strengthen financial capital, the coalition needs partners to help individuals and communities generate the means to be self-sustaining and have access to financial services. • To strengthen human capital, the coalition needs partners who support formal education programmes, vocational training, and informal training on topics such as first aid and life savings skills. • To strengthen natural capital, the coalition needs partners who can help communities mitigate and adapt to the effects of climate change, by helping maintain biodiversity, promote sustainable land use, and invest in low-carbon energy. • To strengthen physical capital, the coalition needs partners who can help communities build the infrastructure and accrue the resources to live healthy lives and enhance their capacities to respond to disasters. • To strengthen social capital, the coalition needs partners who can help communities increase food production, improve water and sanitation, strengthen health systems, and increase access to critical infrastructure, such as electricity and mobile networks. • To strengthen governance systems, the coalition needs partners who can work with governments and civil society to strengthen legal frameworks and promote fair enforcement of laws to support safer and healthier communities
Annex 1: Preliminary Data
Indicator Data (1 of 10) Human capital
Afghanistan
0.5%
9.0%
2.6% 2,174
Natural capital
Score on the GEF benefits index for biodiversity
Average carbon content in the topsoil (% total weight)
Combustible renewables and waste (% of total energy)
Environmental Conservation
Renewable water available within a country per capita (cubic meters)
# of people who are indirect health recipients of IFRC programmes ('000s)
Informal training
# vocational pupils at secondary school ('000s)
% adult population who are literate
% children of primary school age attending school
Aid
Average financial aid received 2008-2014 (millions)
% female population with an account at a formal financial institution
% population which has an account at a formal financial institution
% social insurance coverage
% of population living under $1.25
Means to cover basic needs
Formal education and vocational training
Level of air pollution (Micrograms per capita)
Financial capital
56.8%
31.7%
23
3,800
13.2
1,543
0.9%
Albania
0.5% 45.9% 28.3% 22.7%
122
90.5%
96.8%
19
8.0
7.7
9,699
1.2%
9.6%
0.2
Algeria
33.3% 20.4%
170
96.5%
72.6%
381
3.2
287
0.8%
0.0%
2.9
39.2% 38.9%
234
79.3%
70.6%
400
1.0
6,893
0.7% 58.2%
Argentina
1.4% 29.2% 33.1% 31.8%
311
98.6%
97.9%
254.5
12.9
7,045
1.5%
3.8%
Armenia
1.8% 51.3% 17.5% 18.1%
116
97.1%
99.6%
Australia
1.4%
99.1% 98.6%
Austria
0.3%
97.1% 96.6%
Azerbaijan
0.3% 45.0% 14.9% 14.3%
43.4%
37
73.2%
99.8%
22
5.4
2,304
1.6%
0.3%
0.2
3.2
21,270
0.6%
3.0%
87.7
14.0
6,491
1.6% 20.5%
0.3
11.1
862
1.2%
0.8
4.4
53
0.4% 0.3%
180
15
Bahamas, The Bahrain Bangladesh
43.3%
64.5% 48.8%
5.4
86.4%
94.6%
6.2
14.5
3
1.5% 39.6% 34.9%
725
79.2%
58.8%
428
29.6
0.1
Barbados
3.3
Belarus
0.0% 42.4% 58.6% 58.1%
Belgium
0.5%
Belize
144
91.7%
99.6%
96.3% 97.2% 28.2%
183
76.4%
28.7%
35
95.2%
52.8%
0.0
1.9% 28.2%
1.4
3.0
281
1.6%
0.4
107
13.0
3,930
5.1%
5.9%
0.0
309
15.6
1,072
1.3%
9.2%
0.0
3.4
45,978
1.6%
1.7
8.6
998
0.8% 56.2%
0.2
22.2
103,456
6.9
28,441
12.3
9,271
1.3%
2.6%
0.4
5.8
1,187
0.6% 22.3%
1.4
5.1
28,254
1.7
Bhutan
2.4%
1.4%
Bolivia
8.0%
6.1% 28.0% 25.1%
244
96.9%
94.5%
50
0.0% 46.3% 56.2% 47.7%
248
97.6%
98.2%
122
13.4% 13.7% 30.3% 28.4%
221
86.9%
86.7%
8.9
3.8% 31.9% 55.9% 51.0% 1,284
94.8%
91.3%
1,497
Brazil Brunei Darussalam Bulgaria
1.9% 48.1% 52.8% 55.5%
Burkina Faso
44.5%
Burundi
81.3%
Cabo Verde
13.7%
6.0%
Cambodia
10.1%
2.6%
3.7%
218
Cameroon
27.6%
2.8% 14.8% 10.9%
677
0.3%
95.8% 97.2%
Canada
13.4% 10.8%
106
7.2%
5.9%
5.9
25 -
95.4%
6.0
98.4%
143
199
34
1.2%
1.1
1.0% 24.6%
12.5
1.2% 28.9% 100.0
9.2
20,345
10.2%
0.0%
0.1
13.6
2,891
1.3%
5.1%
0.8
5.0
738
0.8%
0.3
10.4
990
1.0%
0.3
601
1.3%
2.4
368
52.0%
28.7%
27
225
84.6%
86.9%
17
85.3%
1.7
86.1%
73.9%
21
9.6
7,968
1.0% 71.0%
3.5
84.9%
71.3%
360
6.7
12,267
1.1% 67.6%
12.5
0.0%
99.0%
6.9
81,062
4.3%
21.5
115 3.7%
3.6
671
51.6%
Botswana
9.8%
94.4%
0.8% 0.0%
Benin
Bosnia and Herzegovina
10.5%
6.7
17.7
825 279.3 69
8.3
673
Central African Republic
62.8%
3.3%
3.4%
106
73.3%
36.8%
3.9
7.6
30,543
0.9%
Chad
36.5%
9.0%
6.8%
223
51.8%
37.3%
6.9
5.3
1,170
0.9%
4.6%
1.5 2.2
Channel Islands
-
Chile
0.8% 41.3% 42.2% 41.0%
91
90.8%
98.6%
325
5.8
50,228
2.2% 19.0%
15.3
China
6.3%
63.8% 60.0% 1,484
96.6%
95.1%
19,696
48.0
2,072
7.9%
66.6
Colombia
5.6% 96.4% 30.4% 25.4% 1,049
91.1%
93.6%
319
4.5
46,977
3.8% 11.5%
51.5
22
31.2%
75.9%
0.4
2.2
1,633
11.5
13,331
1.1% 93.1%
19.9
6.2
49,914
1.5% 46.9%
3.6
5.2
23,193
3.3% 15.8%
9.7
5.0
3,782
0.9% 77.6%
3.4
Comoros
46.1%
1.9% 21.7% 17.9%
Congo, Dem. Rep.
87.7%
1.7%
3.7%
2.8% 1,049
74.8%
61.2%
733
Congo, Rep.
32.8%
8.9%
9.0%
6.8%
422
91.7%
79.3%
34
1.4% 19.1% 50.4% 40.7%
158
96.1%
97.4%
73
714
68.1%
41.0%
Costa Rica Cote d'Ivoire
Preliminary Analysis
Angola
3.4
35.0%
290
17
1.6%
2.3
19
Indicator Data (2 of 10)
64%
41%
51
0.07
0.70
122.9
96%
100%
228
3.99
1.16
135.8
25%
95%
84%
99%
279
1.95
1.02
142.4
<5.0%
60%
54%
35%
190
1.66
0.62
150.2
18%
Argentina
97%
99%
88%
995
0.48
1.59
106.2
<5.0%
Armenia
91%
100%
100%
150
4.91
1.12
128.7
6%
Australia
100%
100%
100%
6,140
10.65
1.07
118.1
Austria
100%
100%
100%
5,407
7.91
1.56
104.4
Azerbaijan
82%
80%
100%
398
6.69
1.08
139.2
<5.0%
Bahamas, The
92%
98%
88%
1,647
4.14
0.76
131.5
<5.0%
Bahrain
99%
100%
94%
895
2.41
1.66
168.7
Bangladesh
57%
85%
55%
26
0.22
0.67
104.5
17%
Barbados
92%
100%
88%
938
4.86
1.08
96.8
<5.0%
94%
100%
100%
339
10.53
1.19
124.1
100%
100%
100%
4,711
15.78
1.11
83.2
91%
99%
88%
259
1.96
0.53
93.5
7% 10%
14%
76%
28%
33
0.77
0.93
139.3
98%
72%
90
0.98
0.72
110.6
Bolivia
46%
88%
80%
149
1.01
0.98
123.1
Bosnia and Herzegovina
95%
100%
100%
447
5.17
0.91
105.5
20%
64%
97%
43%
384
2.84
1.61
142.7
27%
98%
99%
1,056
7.60
1.35
125.8
<5.0% <5.0%
0%
0%
73%
939
7.73
1.12
135.8
100%
100%
516
4.68
1.45
107.5
Burkina Faso
19%
82%
13%
38
0.57
0.66
127.9
Burundi
48%
75%
5%
20
0.19
0.25
98.8
Cabo Verde
65%
89%
67%
144
0.45
1.00
138.1
21%
58.3%
37%
71%
31%
51
0.93
1.34
176.7
16%
45%
74%
49%
59
0.44
0.70
152.3
11%
World Justice Project Overal Score (2014)
% of the adult population who are a member of a group in the community
% population volunteering for any kind of organisation
% of children in employment
% of women 20-24 who were first married or in union before the age of 18
% of men who consider a husband to be justified in hitting or beating his wife
% of women 15-19 who have ever experienced sexual violence
0.4%
0.1
8%
30.1%
3.6
7.2%
12.2%
2.8%
27%
12.9%
4.6
17%
9.1%
84%
9.9%
3.5
8%
1.2%
75%
35.0
34%
12.4%
90%
60.0
28%
10.2
28%
5.2%
4.0
3.5
2.0
1.8%
39%
8.4%
48%
0.50
3.3 3.0
0.80
2.0
0.82
2.0
4.0
0.1 10,914
64.9%
16.2%
486.2
13%
0.39
4.0
0.7 4.2%
3.2%
2.3%
25.9% 14.8% 199
31.9%
4.0
21.5
30%
24.3
25%
7.3%
54%
0.51 0.76
0.5 74.4%
11.8
12%
25.8% 5.0%
1,086
21.7%
20.2%
0.6
24%
0.39
3.5%
10.6%
70.0
4%
0.55
1.2
19%
35.6%
4.2%
15.0
13%
20.0
7%
0.53
8%
0.51
2.3
0.67 4.7%
83%
0.54
3.0 3.0
4.5 2.8
1,203
10%
Cambodia
502
100%
100%
100%
5,741
9.29
0.78
106.4
Central African Republic
22%
68%
9%
18
0.26
0.29
119.6
Chad
12%
51%
4%
25
0.19
0.36
132.4
0%
0%
100%
Chile
99%
99%
100%
1,103
0.14
1.34
114.0
China
65%
92%
100%
322
1.85
0.89
126.2
11% 446,611 11%
Channel Islands
0.49
89
Cameroon Canada
19.9%
6.0%
81% 100%
0.34
10%
1,739
28
Botswana
Bulgaria
17%
2.5
1.8%
2,855
Brazil Brunei Darussalam
19.3
5.5%
0.7
Belarus
47%
9.3%
9.6%
2,500
Belgium Benin
932
40.4%
34.1%
51.6%
50.3%
2.8
44.3%
20.4%
31.9%
450.0
16.3%
18.0%
3.3 3.5
0.3%
22.4%
18.4%
34.5%
18.4
9%
0.40
22.4%
38.7%
38.4%
62.0%
15.5
13%
0.39
20.0
42%
0.78
75.2%
67.9%
37.2%
9.2
68.1%
60.4%
3.7
12%
4.1
13%
8.3%
74%
0.68
2,048.7
4%
4.8%
6%
0.45
37.2
24%
8.4%
67%
0.49
8.5
18%
144 38% 35%
3.5
4.3
<5.0%
Colombia
80%
91%
97%
530
0.62
1.04
111.8
Comoros
35%
95%
48%
38
0.74
0.47
111.5
Congo, Dem. Rep.
31%
47%
15%
15
0.53
0.44
108.7
Congo, Rep.
15%
75%
37%
100
0.82
1.05
132.4
<5.0%
11,038 1,336
4.1% 3.3% 4.7%
639
Costa Rica
94%
97%
99%
951
0.77
1.46
118.1
6%
22%
80%
59%
88
0.48
0.95
118.4
15%
39.4%
20.5%
96.4
11%
61.8%
32.6%
30.1%
8.0
10%
21.2%
2.5%
6.5
27%
42.0%
33.2%
36.5%
12.8
316 4.7%
7.2%
31.6%
20.8%
32%
Cote d'Ivoire
23.0% 17.3%
2.8 3.0 3.8 1.8
4.5 0.46
2.5
20
Preliminary Analysis
Algeria
Bhutan
# of people made homeless by a disaster between 2008-2014
36.4%
Angola
Belize
1,475
Links and social networks
Score on the disaster risk reduction progress scale
29% 91%
Principles and values
Priority given to disaster risk reduction within legislation score
Afghanistan Albania
Prevalence of undernourishment
Food production index (2012) (2004-2006 = 100)
# mobile subscriptions per capita
# nurses and midwives per 1000 people
Resources
Health expenditure per year per capita
% population access with access to electricity
% of the population with access to a clean water source
% of the population with access to sanitation
Services
Governance Structures Policy and Partici-pation in planning for politics disasters % of the population who always vote in national elections
Social capital
# people volunteering for the RC/RC ('000s)
Physical capital
Indicator Data (3 of 10) Financial capital
Environmental Conservation
0.6
13.2%
12.5
98.7%
4.2
11.1
684
1.0%
2.0%
0.5
15.1
1,250
1.3%
7.0%
0.1
21.3%
0.2
8.9%
6.0 29.3
# vocational pupils at secondary school ('000s)
Curacao
0.0%
Czech Republic
85.2% 83.1% 0.0%
80.7% 80.5%
Denmark
0.7%
99.7% 99.5%
Djibouti
18.8%
12.3%
8.8%
62
5.1%
38.2% 37.4%
141
36.7% 33.2%
69.5%
180
142
3,378
9.9
1,069
1.4%
2.3
10.0
344
0.5%
42
5.2
2,019
1.0%
6.4
28,111
2.1%
5.4%
22
0.4%
2.1%
2.9
17.4%
0.9
Dominican Republic
2.3%
Ecuador
4.0%
9.5%
139
96.5%
93.3%
324
Egypt, Arab Rep.
1.7%
21.3%
6.5%
616
87.9%
73.9%
1,560
El Salvador
2.5%
25.8% 13.8% 10.1%
265
85.5%
113
7.1
2,465
1.8%
9.7%
90.9%
300
-
177
0.5
Equatorial Guinea
28
60.5%
94.5%
1.5
5.0
34,345
1.0%
Eritrea
41
56.7%
70.5%
2.5
8.4
442
0.6%
78.2%
0.8
99.9%
16
7.0
9,595
7.1%
13.9%
0.1
39.0%
314
92.9%
8.4
11.0% 25.2%
0.2
Estonia
1.0%
Ethiopia
96.8% 97.3%
36.8%
1.0%
1,446
Fiji
5.9%
5.3%
20
Finland
0.0%
France
0.3%
64.9%
6.5
1,296
0.9%
1.4
1,930
0.9
32,404
1.5%
99.7% 99.8%
134
5.5
19,671
97.0% 96.6%
1,166
10.7
French Polynesia Gabon
98,103
1.0%
5.7%
5.3
57.7%
3.0
8.9%
0.6 0.6
4.6
87.1%
82.3%
Gambia, The
33.6%
42
62.6%
52.0%
12
4.7
1,622
0.9%
Georgia
14.1% 53.4% 33.0% 34.9%
390
95.7%
99.7%
5.0
10.7
12,984
1.1%
1,396
13.3
1,327
3.0%
8.9%
485
73.0%
71.5%
61
8.2
1,170
0.9%
57.0%
1.9
77.9% 75.7% 2,278
97.4%
115
11.6
5,257
1.1%
5.2%
2.8
22.3% 15.6%
78.3%
313
6.1
7,060
2.1%
62.2%
5.1
19,242
1.3%
2.3 0.6
Greece
0.3%
98.1% 98.7%
28.6% 27.3% 29.4% 27.1% 1.4%
5.5
0.0%
3.9
53
Germany
7.6
1.4%
1.5
13.4% 18.9% 17.2%
Ghana
6.1%
3,029 38,408
36
Preliminary Analysis
Cyprus
Score on the GEF benefits index for biodiversity
5.6%
1.2%
Combustible renewables and waste (% of total energy)
1.3%
3,384
Average carbon content in the topsoil (% total weight)
8,865
3.5
137
Renewable water available within a country per capita (cubic meters)
13.5
210
Level of air pollution (Micrograms per capita)
145
99.8%
# of people who are indirect health recipients of IFRC programmes ('000s)
99.1%
58
% adult population who are literate
143
Cuba
% children of primary school age attending school
52.4% 88.4% 87.2%
% population which has an account at a formal financial institution
Average financial aid received 2008-2014 (millions)
0.0%
Aid
Natural capital Informal training
% female population with an account at a formal financial institution
Croatia
% social insurance coverage
% of population living under $1.25
Means to cover basic needs
Human capital Formal education and vocational training
0.1
Guam
0.2
Guatemala
13.7%
Guinea
40.9%
Guinea-Bissau
48.9%
8.4%
3.7%
2.9%
Guyana
392 133
57.8%
25.3%
22
60
67.4%
56.7%
1.0
4.5
9,388
1.1%
4.5
2.5
301,396
3.5%
6.6
1,261
0.9%
77.7%
5.4
11,196
1.4%
43.7%
22
94.9%
85.0%
Haiti
61.7%
22.0% 21.1%
666
77.2%
48.7%
Honduras
16.5% 23.7% 20.5% 14.9%
166
92.7%
85.4%
Hong Kong SAR, China
88.7% 89.1%
Hungary
0.1%
Iceland
0.0%
57.1% 72.7% 73.1%
333 6.3
781
99.4%
69
India
23.6% 10.5% 35.2% 26.5% 2,081
Indonesia
16.2%
1.5%
317
139 7.6
83.5%
62.8%
829
320
8.0
3.0 5.2 7.2
0.4%
0.2
15.6
606
2.4%
7.6%
3.0
526,313
2.4%
0.0%
0.7
32.0
1,155
0.9%
24.7%
39.9 81.0
19.6% 19.2% 1,953
94.5%
92.8%
4,019.2
9.2
8,080
5.2%
25.4%
73.7% 61.9%
77
96.7%
84.3%
813
3.2
11.3
1,659
1.0%
0.1%
7.3
4,026
90.4%
79.0%
71
6.1
16.7
1,053
0.6%
0.1%
1.6
55
8.2
5.0
10,663
5.5%
3.2%
0.6
97.8%
137
13.2
93
1.0%
0.1%
0.8
Iran, Islamic Rep.
1.5%
Iraq
3.9%
27.9% 10.6%
Ireland
0.4%
93.9%
Israel
0.4%
90.5% 92.4%
7.5%
92.2% 1,435
21
Indicator Data (4 of 10)
Croatia
98%
99%
100%
908
5.27
1.15
95.8
Cuba
93%
94%
100%
558
9.05
0.18
99.7
0%
0%
88%
Cyprus
100%
100%
100%
1,949
4.46
0.95
84.0
Czech Republic
100%
100%
100%
1,432
8.43
1.31
86.3
Denmark
100%
100%
100%
6,304
16.09
1.27
104.4
Curacao
1.28
30 <5.0%
25.5
136
40.4%
6%
27%
2.5
14%
6.0%
0.67
28.5
20%
0.88
61%
92%
50%
129
0.80
0.28
134.5
19%
24
81%
98%
310
1.33
0.88
134.9
15%
243
7.5%
40.8%
14.1%
14.0
35%
Ecuador
83%
86%
97%
361
1.98
1.11
119.2
11%
360
6.0%
22.2%
3.2%
5.9
15%
5.2%
16.6%
2.9%
10.0
7%
2.3%
65
6.5%
25.4%
7.0%
2.1
18%
Egypt, Arab Rep.
96%
99%
100%
152
3.52
1.22
118.3
<5.0%
El Salvador
71%
90%
92%
254
0.41
1.36
116.6
14%
Equatorial Guinea
89%
51%
29%
1,138
0.54
0.67
117.1
17.0%
Eritrea
13%
60%
33%
15
0.58
0.06
111.3
Estonia
95%
99%
100%
1,010
6.46
1.60
125.5
Ethiopia
24%
52%
23%
18
0.24
0.27
143.1
35%
Fiji
87%
96%
56%
177
2.24
1.01
82.7
<5.0%
Finland
100%
100%
100%
4,232
10.83
1.72
93.0
France
100%
100%
100%
4,690
9.30
0.98
100.1
477
97%
100%
56%
0.86
108.0
11
Gabon
41%
92%
82%
397
5.02
2.15
120.0
<5.0%
Gambia, The
60%
90%
31%
26
0.57
1.00
107.2
6% 10%
Georgia
93%
99%
100%
333
0.15
1.15
72.0
Germany
100%
100%
100%
4,683
11.49
1.19
106.0
5.4%
5.4
35
51.9%
29.5%
44.6%
40.7%
44.9%
41.0%
Ghana
14%
87%
61%
83
0.93
1.08
137.7
99%
100%
100%
2,044
0.24
1.17
86.5
<5.0%
Guam
90%
100%
56%
Guatemala
80%
94%
82%
226
0.90
1.40
135.8
14%
Guinea
19%
75%
20%
32
0.04
0.63
122.3
18%
2.8
0.3
46%
0.47
3.0
3.0
0.45
2.0
4.8
0.45 0.48
3.3
0.0
26.1%
0.4
18%
45.1
11%
5.5%
43%
0.42
0.76
26.1
27%
0.84
53.9
25%
0.74
12%
0.0
0.0
13.9%
39.7%
42
21.9%
24.0%
2.5
36.4%
35.9%
3.2
14.0%
31.8%
527
Greece
75%
337
16.5%
25.7%
20.7%
48.9%
276
2.8
15.0
18%
398.0
27%
12.5%
69%
56.0
21%
12.9%
72%
24.8
4%
0.59 0.44
3.5
0.60
2.8
0.80
4.3
0.57
3.3
98.3 851
3.0%
30.3%
19.2%
1.0
40%
66.2%
51.7%
44.9%
5.0
18%
22.0%
50.5%
1.4
19.3%
23.0%
Guinea-Bissau
20%
74%
57%
30
0.55
0.74
137.6
18%
Guyana
84%
98%
78%
235
0.53
0.69
113.5
10%
0.69
107.6
52% 578,061
9.8%
14.9%
17.5%
37.8%
15.0
36%
1.08
0.96
118.5
12%
6.1%
9.9%
33.6%
7.8%
2.0
28%
2.39
57.8
<5.0%
Haiti
24%
62%
34%
53
Honduras
80%
90%
81%
195
0%
0%
100%
Hungary
100%
100%
100%
987
6.39
1.16
77.6
Iceland
100%
100%
100%
3,872
15.59
1.08
114.6
317
India
36%
93%
75%
61
1.71
0.71
130.0
15%
7,857
Indonesia
59%
85%
94%
108
1.38
1.22
133.1
9%
11,435
4.5%
10%
4.6
25%
42.1%
47.4%
2.5%
2,500.0
18%
17.0%
3.7%
1,422.9
30%
Iran, Islamic Rep.
89%
96%
98%
490
1.41
0.84
112.4
<5.0%
4,986
16.7%
85%
85%
98%
226
1.38
0.96
114.7
24%
240
24.3%
Ireland
99%
100%
100%
3,708
15.67
1.03
96.7
100%
100%
100%
2,289
4.93
1.23
111.2
3,050
40.3
18.3%
Iraq
3.8 28%
0.76 0.61
24.4%
48%
0.48
2.0
0.52
2,491.0 6.4%
3.3 1.0
14.9% 652
3.0
3.3 3.3
0.44
4.3
11%
5.3
37%
2.7%
59%
2.0
21%
22
Preliminary Analysis
112
82%
Israel
Score on the disaster risk reduction progress scale
4.5
<5.0%
Djibouti
Hong Kong SAR, China
Priority given to disaster risk reduction within legislation score
0.57
44.3
Dominican Republic
French Polynesia
World Justice Project Overal Score (2014)
% of the adult population who are a member of a group in the community
% population volunteering for any kind of organisation
Links and social networks
% of children in employment
% of women 20-24 who were first married or in union before the age of 18
% of men who consider a husband to be justified in hitting or beating his wife
% of women 15-19 who have ever experienced sexual violence
Principles and values
# of people made homeless by a disaster between 2008-2014
Prevalence of undernourishment
Food production index (2012) (2004-2006 = 100)
# mobile subscriptions per capita
# nurses and midwives per 1000 people
Resources
Health expenditure per year per capita
% population access with access to electricity
% of the population with access to a clean water source
% of the population with access to sanitation
Services
Governance Structures Policy and planning for disasters
Partici-pation in politics % of the population who always vote in national elections
Social capital
# people volunteering for the RC/RC ('000s)
Physical capital
Indicator Data (5 of 10)
1.4%
0.2% 12.1% 71.0% 67.1%
Japan
0.4%
99.0%
1,705
13.3
3,050
1.1%
87.5%
-
5.2
3,464
1.7% 17.2%
11.7
3,377
2.3%
96.4% 96.8%
848
6.7% 2.3%
Score on the GEF benefits index for biodiversity
Combustible renewables and waste (% of total energy)
Average carbon content in the topsoil (% total weight)
Environmental Conservation
Level of air pollution (Micrograms per capita)
# of people who are indirect health recipients of IFRC programmes ('000s)
98.0%
Informal training
# vocational pupils at secondary school ('000s)
156
71.0% 64.3%
% adult population who are literate
% children of primary school age attending school
Italy Jamaica
Aid
Average financial aid received 2008-2014 (millions)
% female population with an account at a formal financial institution
% population which has an account at a formal financial institution
% social insurance coverage
% of population living under $1.25
Means to cover basic needs
Natural capital
Human capital Formal education and vocational training
Renewable water available within a country per capita (cubic meters)
Financial capital
3.8 4.4 36.0
0.1% 59.8% 25.5% 17.4%
349
98.1%
97.9%
25
0.1% 29.2% 42.1% 43.7%
396
99.3%
99.7%
110
35
629
86.7%
72.2%
16
1,749
4.6
467
113
20.1
2,691
1.6%
5.6%
0.7
375
7.9
1,291
1.3%
1.6%
1.7
0.0%
9.6%
-
95.5%
4.7
18.9
-
0.4%
0.0%
0.1
1.2%
0.1%
1.1
Kenya
43.4%
1.9% 42.3% 39.2%
Korea, Dem. Rep.
67
Korea, Rep.
93.0% 93.1%
Kosovo
35.2% 44.3% 31.5%
Kuwait
86.8% 79.6%
Kyrgyz Republic Lao PDR Latvia
99.1% 100.0%
5.1% 36.8% 30.3%
3.8%
0.5 84.9%
72.7%
4.2
21.1
28,125
99.9%
32
8.9
8,314
3.0% 28.0%
0.0
89.6%
56
14.1
1,074
1.2%
0.2
6.6
2,521
1.3%
5.3
46,576
1.1%
9.5
113
0.5%
11.8
5,264
2.4% 13.3%
0.0
12.6
1,841
1.1%
3.5%
-
2,563
1.1%
6.1%
14,700
1.1%
152
53.7% 37.0% 25.9%
280
98.3%
18.5% 16.9%
65
89.2%
75.8%
6.7
0.7% 18.8% 14.7%
562
34.3%
42.9%
18
89.9%
178
99.8%
34
Libya
6.4 0.8% 45.4% 73.8% 76.1% 94.6% 95.3% 0.3% 43.6% 73.7% 71.5%
95.6%
1.6
98.3%
97.5%
56
61
28
1.5
87.7%
5.8%
4.6%
312
69.4%
64.5%
Malawi
72.2%
0.7% 16.5% 16.9%
331
85.3%
61.3%
-
Malaysia
0.0%
6.8% 66.2% 63.1%
83
93.1%
178
1.5%
4.7%
50.6%
1.3%
Malta Mauritania
1.0%
5.0 2.0%
0.3 2.6 1.3%
1.6
-
99
2.2 5.0
986
1.3%
10.6
19,517
3.5%
0.2 29.2 3.5
4.6%
13.9
20
94.2%
98.4%
1.1
87
0.0%
330
57.5%
33.6%
94
4.1
3,921
0.7%
92.4%
2.1
6.4
119
0.9%
45.5%
3.2
3.8
103
0.9%
89.2%
11
1.5
2,122
1.9%
94.2%
2,019
10.2
3,343
3.0%
4.4%
68.7 0.0
95.3% 94.1%
1.5 5.3%
0.0
9.2% 17.5% 12.1%
132
0.4% 12.3% 80.1% 74.7%
76
Mexico
1.0% 82.7% 27.4% 22.0% 1,731
Moldova
0.2% 41.1% 18.1% 17.2%
85
98.7%
99.1%
33
14.0
281
2.1%
2.5%
Mongolia
40.5% 77.7% 82.4%
116
95.7%
98.3%
42
5.1
12,258
1.2%
4.1%
50.4% 48.9%
43
97.5%
98.4%
21
12.1
-
0.0% 19.6%
-
2.6% 27.9% 39.1% 26.7%
532
89.4%
67.1%
155
7.3
879
0.8%
3.5
643
77.1%
50.6%
32
3.8
3,883
0.8% 79.2%
7.2
179
90.2%
92.6%
14.1
18,832
1.3% 75.5%
10.0
87
87.0%
76.5%
5.2
289
93.8%
57.4%
Morocco Mozambique
0.2% 60.7%
1.7% 39.9% 35.5%
Myanmar Namibia
23.5%
Nepal
23.7%
9.1% 25.3% 21.2%
0.4%
98.7% 98.4%
Netherlands New Caledonia New Zealand
61.0%
1.4
Mauritius
Montenegro
23.4%
3.3
101
Madagascar
6.9%
109
13
Macao SAR, China
8.2%
8.8
8,555
56.2%
Maldives
0.9% 72.4%
7.8
83.8%
Mali
5.1
61
141
5.5%
0.4
0.1%
99.2%
Lesotho
Macedonia, FYR
0.1%
1.0%
98.5%
Liberia Lithuania
1.0%
3,777
95
1.7% 26.8% 26.2%
Luxembourg
106
7.4
3.9%
1.1% 46.0% 89.7% 92.0%
Lebanon
12.7
96.9%
-
1.0
25
324
1.3 3.3
2.8%
4.2
5.9
2,674
0.3% 13.3%
15
30.5
7,130
1.3% 84.1%
2.1
747
14.1
655
6.4%
4.7%
0.2
70
2.1
73,141
6.5%
20.2
96.5% 99.4% 99.4%
Preliminary Analysis
Jordan Kazakhstan
1.4% 1.9%
8.5
23
Indicator Data (6 of 10)
1,651 8%
26
149.2 11.3%
9.8%
8.4%
1.0%
Japan
100%
100%
100%
4,752
11.49
1.15
101.7
Jordan
98%
96%
99%
388
4.05
1.42
127.6
<5.0%
Kazakhstan
98%
93%
100%
521
8.25
1.81
112.8
<5.0%
738
0.8%
16.7%
6.1%
3.6%
Kenya
30%
62%
23%
45
0.79
0.71
148.2
24%
414
11.3%
44.0%
26.4%
37.7%
Korea, Dem. Rep.
82%
98%
26%
4.12
0.10
93.7
38%
1,034
102.6
5.01
1.11
102.7
<5.0%
3,542
126.1
Korea, Rep.
100%
98%
93%
Kosovo
0%
0%
100%
Kuwait
1,703
88,498
99%
94%
1,428
4.55
1.90
166.6
<5.0%
76
92%
88%
100%
84
6.12
1.21
107.6
6%
355
Lao PDR
65%
72%
66%
40
0.88
0.66
151.5
22%
168
Latvia
79%
98%
100%
792
4.73
1.37
139.0
0.1%
Lebanon
98%
100%
100%
675
2.72
0.81
101.6
<5.0%
30%
81%
17%
138
0.62
0.86
98.6
12%
Liberia
17%
75%
4%
65
0.27
0.60
125.4
30%
Libya
97%
54%
100%
578
6.80
1.65
112.2
Lithuania
94%
96%
100%
859
7.17
1.51
119.4
100%
100%
100%
7,452
12.47
0%
0%
93%
0.78
49%
0.57
4.8
29%
5.7%
51%
72.1
28%
Priority given to disaster risk reduction within legislation score
Score on the disaster risk reduction progress scale
3.5 3.8
4.0
4.5
1.0
4.0
0.47 0.43
9.8%
55% 0.77
7.8%
36.6%
2.0
25%
49.1%
35.4%
8.6%
3.3
20%
1.4
9%
7.5
8%
6.1% 13.1%
48.4%
18.8%
2.6%
0.9
30.2%
37.9%
18.4%
3.5
73
1.49
93.9
3.04
88.0
<5.0%
Macedonia, FYR
91%
99%
99%
327
0.61
1.06
113.2
<5.0%
Madagascar
14%
50%
14%
18
0.32
0.36
120.2
31%
1,884
Malawi
10%
85%
9%
25
0.28
0.32
173.8
22%
231
Malaysia
96%
100%
99%
410
3.28
1.45
125.5
<5.0%
33
17.8%
3.0
37%
1.2
12%
15.0
30% 7%
0.58 0.45
12.9%
49.6%
25.1%
14.3%
30.0
30%
30.0
19%
5.04
1.81
88.2
6%
0.43
1.29
160.1
<5.0%
202
55.0%
23.0%
6.4
Malta
100%
100%
100%
1,835
7.09
1.30
90.4
0.1
24%
27%
50%
18%
52
0.67
1.03
120.4
7%
88
34.3%
21.3%
0.6
12%
22.9%
6.8%
42.9
444
3.73
1.23
95.9
<5.0%
82
2.53
0.86
112.5
<5.0%
983
Moldova
87%
97%
99%
239
6.49
1.06
75.8
Mongolia
56%
85%
86%
232
3.50
1.24
131.7
Montenegro
90%
98%
100%
493
5.25
1.60
89.8
30 22%
6.9%
75%
84%
99%
190
0.89
1.29
122.4
<5.0%
399
21%
49%
15%
37
0.41
0.48
160.5
28%
128
Myanmar
77%
86%
49%
20
1.00
0.13
138.9
17%
20,577
Namibia
32%
92%
44%
473
2.78
1.10
92.1
37%
518
Nepal
37%
88%
76%
36
0.46
0.71
130.8
13%
499
Netherlands
100%
100%
100%
5,737
8.38
1.14
112.6
New Caledonia
100%
99%
56%
0.94
100.9
0%
100%
100%
3,292
10.87
1.06
114.3
41%
0.51
1.8 3.8
0.1
2.3 6%
9.3%
3.5 25%
9.2%
67%
0.45
18.9%
29.0%
1.8
19%
0.45
8.8%
4.7%
16.0%
15.0
29%
0.51
1.8
8% 7%
4.8% 15.9%
4.5%
40.0
19.9%
48.2%
27.4%
5.6
40.8%
8.6%
21.5%
40.7%
8.1
5.0%
14%
4.3 2.8 3.0 4.0
0.41
20.7
26%
0.50
117
32.3
37%
12.1%
73%
0.83
1,560
15.4
40%
12.1%
79%
0.83
4.5 40.6%
5.0
0.51
43%
11.3%
3.8
0.58
13.3%
32
Morocco
6.2%
3.3 2.0
0.4
7
Mozambique
3.9%
3.0
45%
27%
42
618
6.6%
7.2
558
99%
0.51
6.8
17%
100%
36%
19.8%
100%
95%
10.5%
26.0%
99%
100%
2.3
6.9%
67%
91%
2.0
41.2%
99%
85%
66%
46.3%
22%
Mauritius
33%
8.8%
2.5
Maldives
Mexico
9.2%
0.42
Mali
New Zealand
World Justice Project Overal Score (2014)
58%
4.8%
50.4%
29
Lesotho
Mauritania
% of the adult population who are a member of a group in the community
4.7% 6%
0.3
3.0
<5.0%
100%
Macao SAR, China
0.63 0.53
2,203.9
65
Kyrgyz Republic
Luxembourg
25%
9.0
4.0 1.0
2.8
3.0
3.8
24
Preliminary Analysis
7.9%
% population volunteering for any kind of organisation
Links and social networks
% of children in employment
104.0
% of women 20-24 who were first married or in union before the age of 18
87.5
1.00
% of men who consider a husband to be justified in hitting or beating his wife
1.59
1.09
% of women 15-19 who have ever experienced sexual violence
0.29
318
Principles and values
# of people made homeless by a disaster between 2008-2014
3,032
92%
Prevalence of undernourishment
100%
93%
Food production index (2012) (2004-2006 = 100)
100%
# mobile subscriptions per capita
Health expenditure per year per capita
0%
# nurses and midwives per 1000 people
% population access with access to electricity
Resources
80%
% of the population with access to sanitation
Italy Jamaica
% of the population with access to a clean water source
Services
Governance Structures Policy and planning for disasters
Partici-pation in politics % of the population who always vote in national elections
Social capital
# people volunteering for the RC/RC ('000s)
Physical capital
Indicator Data (7 of 10) Financial capital
5.5
196
Nigeria
62.0%
4.1% 29.7% 26.0%
693
59.1%
51.1%
8.2
1,273
Norway
0.7%
4.5
75,135
1.7%
6.4%
1.3
29.4
385
0.5%
0.0%
3.7
1.4
302
0.9% 34.6%
4.9
3.2
35,350
1.8% 11.5%
10.9
2.2%
25.4
Oman Pakistan Panama
73.6% 63.5% 12.7%
7.8% 10.3%
3.0% 1,384
4.0% 42.2% 24.9% 23.3%
Papua New Guinea
58
# vocational pupils at secondary school ('000s)
86.9% 63.8%
89
54.7%
376
94.1%
49
195
1.8% 40.8%
3.3
0.6%
0.9
0.8% 82.2%
6.0
1.0%
84
62.9%
29.3
5.1
109,407
Paraguay
3.0%
9.2% 21.7% 22.7%
78
87.9%
93.9%
60
8.0
17,200
1.0% 45.8%
2.8
Peru
2.9% 15.3% 20.5% 17.6%
433
97.4%
93.8%
31
6.7
54,024
1.6% 15.0%
33.4
7.5% 26.6% 33.7%
461
88.2%
4,868
1.3% 17.1%
32.3
0.0% 48.4% 70.2% 68.3%
800
99.7%
766
6.7
1,391
3.4%
8.9%
0.5
81.2% 77.8% 1,425
94.5%
185
4.0
3,633
1.5% 14.7%
5.5
65.9% 61.6%
96.7%
Philippines Poland
19.0%
Portugal Puerto Rico Romania
0.0% 46.2% 44.6% 41.1%
Russian Federation
0.0% 42.0% 48.2% 47.7% 63.0%
0.8% 32.8% 28.2%
Samoa Sao Tome and Principe
43.5%
Saudi Arabia Senegal Serbia Sierra Leone
46.4% 15.2% 34.1% 19.1%
1.6%
26
0.5%
98.6%
558
9.8
2,119
1,576
9.3
30,056
58
3.8
807
8.3%
0.9
9.1
-
2.3%
1.6
196
1.7% 10.3%
0.1
99.7%
3.9%
344
91.7%
65.9%
19
88.5%
98.9%
29
93.6%
69.5%
0.6
11.9
11,296
2.8%
94.4%
104
4.5
83
0.7%
3.4
4.0 0.0% 1.0%
0.7 34.1
2.7 0.0%
3.2
61.6%
52.1%
38
14.0
1,825
0.8% 45.8%
1.0
379
98.7%
98.2%
215
0.9
1,174
0.0%
6.4%
0.2
189
74.3%
44.5%
21
5.2
26,264
1.2%
96.4%
27
15.1
111
0.6%
2.8%
0.1
174
13.7
2,327
1.3%
5.3%
0.1
48
2.1
9,061
1.7%
8.8%
0.2
8.8% 15.3% 12.8% 98.2% 98.2%
Slovak Republic
0.3%
79.6% 78.9%
0.0%
97.1% 98.1%
Solomon Islands
1.6%
99.7%
490
1.3
111
65.4%
5.5
79,646
1.4%
31.0% 27.3%
301
23.0%
6.2
572
0.5%
9.4% 22.1% 53.6% 51.0%
443
0.6% 10.3%
Somalia South Sudan 2.3%
93.3% 91.7%
Sri Lanka
4.1%
6.2% 68.5% 67.2%
St. Lucia 19.8%
6.9%
348
4.4 6.1
93.7%
247
19.9
846
97.9%
583
9.2
2,384
1.3%
91.2%
148
13.1
2,578
0.9% 47.4%
7.9
0.2
3.1
-
1.6%
1.4
26.2%
Spain
2,302
20.7 -
6.0%
6.8
6.1
99.5%
4.4% 1,123
75.0%
61.3%
28
5.2
81
0.7% 67.1%
5.1
56
95.4%
94.7%
24
2.8
183,579
3.4%
2.7
23
96.5%
83.1%
6.2
2,113
1.7%
0.1
182
6.5
17,826
210
14.2
Suriname Swaziland
1,964
370
Slovenia
Sudan
2.1
5.5%
56.6%
5.8%
673
0.5
0.1% 40.2% 62.2% 62.3%
Singapore
South Africa
43
92.0%
Qatar
Rwanda
95.4%
39.3%
28.6% 27.4%
Sweden
0.4%
99.0% 99.0%
Switzerland
0.7%
Syrian Arab Republic
1.7%
Tajikistan
6.5% 34.6%
-
71
23.3%
19.6%
129
86.7%
85.1%
129
2.5%
2.1%
106
97.1%
99.7%
15
0.02
Preliminary Analysis
126
Score on the GEF benefits index for biodiversity
215
Combustible renewables and waste (% of total energy)
25,689
22.8
Average carbon content in the topsoil (% total weight)
4.3
15.5%
Renewable water available within a country per capita (cubic meters)
469
50.4%
Level of air pollution (Micrograms per capita)
6.9
230
# of people who are indirect health recipients of IFRC programmes ('000s)
78.0%
1.5%
1.5%
% adult population who are literate
70.3%
5.5%
8.5%
% population which has an account at a formal financial institution
221
40.8%
Nicaragua
% social insurance coverage
6.1% 14.2% 12.8%
Niger
% of population living under $1.25
% children of primary school age attending school
Environmental Conservation
Average financial aid received 2008-2014 (millions)
Aid
Natural capital Informal training
% female population with an account at a formal financial institution
Means to cover basic needs
Human capital Formal education and vocational training
5.3% 21.5%
0.3
4,999
2.1%
9.3%
0.2
15.9
312
0.8%
0.0%
0.9
13.2
7,732
0.9%
0.0%
0.7
25
Indicator Data (8 of 10)
1.61
0.73
110.6
13.40
1.16
101.8
100
97%
93%
94%
690
5.00
1.55
111.9
200
Oman Pakistan
48%
91%
91%
39
0.57
0.70
122.2
22%
10,001
Panama
73%
94%
88%
723
2.40
1.63
114.0
11%
346
Papua New Guinea
19%
40%
15%
114
0.46
0.41
116.4
Paraguay
80%
94%
97%
392
1.79
1.04
156.9
11%
100
Peru
73%
87%
85%
337
1.51
0.98
141.7
9%
26,488
Philippines
74%
92%
83%
119
6.00
1.05
121.1
12% 167,025
90%
0%
100%
854
5.84
1.50
108.1
259
Portugal
100%
100%
100%
1,905
5.33
1.13
99.5
75
Puerto Rico
99%
94%
88%
0.84
111.5
100%
100%
94%
2,029
11.87
1.53
135.3
31
Romania
72%
88%
100%
420
5.51
1.06
86.8
268
Russian Federation
71%
97%
100%
887
8.52
1.53
113.5
6,005
0.57
Rwanda
64%
71%
11%
66
0.69
Samoa
92%
99%
100%
245
1.85
Sao Tome and Principe
34%
97%
57%
109
1.87
Saudi Arabia
24.7%
42.8%
21.2%
564.2
36%
40.0
35%
31.9%
4
Poland
Qatar
5.6%
168.5
34%
743
106.3
<5.0%
310
0.65
122.4
7%
21.0%
5.1%
12.0%
25.1%
253.0
15%
5.4%
3.8
31%
17.9%
15.3%
2.5
24%
19.1%
20.7%
2.0
20%
7.2%
14.2%
13.3%
8.1%
12.0
16%
1.1
19%
10.3%
1.4%
6.5
8%
8.6%
68%
5.7
17%
5.5%
42%
12.3
10%
21.5%
53%
19.1%
21.7%
34.4%
108.8
<5.0%
752
134.7
17%
269
24.7%
32.9%
13.1%
20.0
Serbia
97%
99%
100%
561
4.55
1.19
92.4
620
6.6%
5.0%
6.9%
60.0
43.7%
39.9%
0.44
163.8 105.3
Slovak Republic
100%
100%
100%
1,326
0.33
1.14
83.5
Slovenia
100%
100%
100%
1,942
8.46
1.10
83.2
Solomon Islands
29%
81%
19%
148
2.05
0.58
119.9
Somalia
24%
32%
29%
0.11
0.49
115.2
South Africa
74%
95%
83%
645
4.90
1.47
120.5
South Sudan
9%
57%
2%
27
Spain
26%
<5.0%
100%
100%
100%
2,808
5.08
1.07
90.1
92%
94%
85%
89
1.64
0.95
122.7
25%
St. Lucia
65%
94%
88%
556
2.16
1.16
71.3
<5.0%
Sudan
24%
56%
29%
115
0.84
0.73
100.2
Suriname
80%
95%
100%
521
5.88
1.27
104.3
8%
Swaziland
58%
74%
35%
259
1.60
0.71
111.7
26%
Sweden
100%
100%
100%
5,319
11.86
1.24
94.2
100%
100%
100%
8,980
17.36
1.34
104.7
Syrian Arab Republic
96%
90%
93%
105
1.86
0.56
93.2
Tajikistan
94%
72%
100%
55
4.48
0.92
145.5
2
65.1%
22.4% 45.3%
Sri Lanka
Switzerland
36 20
0.25
43.5%
5.6%
586
51.5%
45.6%
421
11.8%
10.7%
7.5%
3.5
32.9% 23.1%
6.5%
12.5% 13.3%
87 27 0.5%
15%
7.4 17%
13.6
11%
14.7
34%
16.2%
67%
9.5%
54%
0.54
2.8
0.44
3.0
0.65 2.0
4.6 21%
18.1%
54%
204.8
17%
6.2%
61%
3.0
46%
0.55
3.0
0.67 0.52
2.1
18.8%
338
3.3 0.45
0.6
2,568
1,081
32%
47%
14%
5.0
13%
3.3
0.66
0.1
0.93
1.56
4.0
0.4
1.76
0.17
3.0
3.6%
2.10
6.39
0.49
3.8 88%
0.50
0.42
96
3.5 3.0
0.67
51
2,426
0.36
82%
795
12%
3.8
0.50
62%
57%
73%
36%
4.4%
94%
60%
5.6%
11.6%
97%
100%
4.0
43%
74%
13%
3.0
12%
52%
100%
0.39
192.3
100%
Sierra Leone
3.8
115.9
Senegal
Singapore
3.0
0.3
45.7% 9.3%
43%
0.43
0.88
13.0%
21.3% 1.9%
11.3%
Score on the disaster risk reduction progress scale
94 9,055
11%
Priority given to disaster risk reduction within legislation score
48% 100%
17%
5.5
3.5 3.0
201.9
19%
0.3
22%
3.3
0.7 31.5
13%
72.7
32%
4.8 3.5
13.3%
6.6%
3.0
15%
11.6%
8.9%
6.8
41%
12.2%
84%
0.85
3.8
26
Preliminary Analysis
64% 100%
2.5
55.1%
World Justice Project Overal Score (2014)
1,608
28% 100%
31.1%
76.3%
% population volunteering for any kind of organisation
6%
Nigeria Norway
40.6% 26.8%
# people volunteering for the RC/RC ('000s)
6.6%
240
% of children in employment
293
11%
% of women 20-24 who were first married or in union before the age of 18
17%
140.3
Links and social networks
% of men who consider a husband to be justified in hitting or beating his wife
133.6
0.39
Prevalence of undernourishment
1.12
0.14
Food production index (2012) (2004-2006 = 100)
1.07
25
# mobile subscriptions per capita
144
9%
# nurses and midwives per 1000 people
74%
52%
Health expenditure per year per capita
85%
9%
% population access with access to electricity
% of women 15-19 who have ever experienced sexual violence
Principles and values
# of people made homeless by a disaster between 2008-2014
Resources
52%
% of the population with access to sanitation
Nicaragua Niger
% of the population with access to a clean water source
Services
Governance Structures Policy and planning for disasters
Partici-pation in politics % of the population who always vote in national elections
Social capital
% of the adult population who are a member of a group in the community
Physical capital
Indicator Data (9 of 10) Financial capital
Timor-Leste
34.9%
0.2%
Togo
52.5%
0.2%
Trinidad and Tobago Tunisia
0.7%
Turkey
0.1%
34.8%
Turkmenistan
1,705
1.6%
88.2%
14.8
739
14.6
3,350
1.0%
18.3%
8.0
112
72.1%
58.3%
6.6
2.9
6,972
1.8%
7.5
1,687
0.9%
82.1%
0.3
2.2
1,008
# vocational pupils at secondary school ('000s)
Score on the GEF benefits index for biodiversity
234
96.4%
Combustible renewables and waste (% of total energy)
67.8%
95.7%
Average carbon content in the topsoil (% total weight)
80.4%
138
Renewable water available within a country per capita (cubic meters)
982
72.6%
Level of air pollution (Micrograms per capita)
13.8%
72.7%
# of people who are indirect health recipients of IFRC programmes ('000s)
17.3%
% adult population who are literate
% children of primary school age attending school
98.9%
Average financial aid received 2008-2014 (millions)
0.3%
% female population with an account at a formal financial institution
43.5%
Thailand
Environmental Conservation
0.6
10.2%
9.2%
281
88.6%
60.4%
28
75.9%
69.9%
3.4
97.7%
98.8%
0.9
3.0
2,863
1.8%
0.1%
2.2
32.2%
25.2%
268
98.0%
79.7%
161
7.7
385
0.7%
14.6%
0.5
57.6%
32.7%
1,434
92.7%
94.9%
1,830
12.1
3,029
1.0%
3.2%
6.2
0.4%
0.8%
13
8.4
268
0.4%
0.0%
1.8
7.8
1,038
1.1%
99.6%
Uganda
37.8%
9.7%
20.5%
15.1%
599
81.2%
73.2%
83
Ukraine
0.0%
52.8%
41.3%
39.2%
1,251
99.8%
99.7%
257
11.9
1,167
2.3%
1.2%
0.5
59.7%
47.2%
0.1
90.0%
4.0
11.7
16
0.5%
0.1%
0.2
2,262
7.0%
3.6%
3.5
8,914
1.5%
4.2%
94.2
3.9
27,061
2.7%
29.3%
1.2
12.6
540
0.5%
0.0%
1.1
-
2.0%
26,476
0.0%
0.9%
25.3
4,006
1.3%
24.0%
12.1
195
0.0%
86
0.6%
1.5%
3.2
8.2
5,516
1.6%
80.2%
3.8
5.0
866
0.6%
64.2%
1.9
United Arab Emirates United Kingdom
1.0%
97.2%
97.7%
United States
1.7%
88.0%
84.1%
27
Uruguay
0.3%
23.5%
23.8%
116
98.4%
44
22.5%
21.3%
74
95.8%
99.5%
891
27
77.2%
83.4%
2.0 126
36.0%
Uzbekistan Vanuatu
470 0.0%
99.0%
Venezuela, RB
6.6%
10.2%
44.1%
36.2%
32
91.9%
95.5%
Vietnam
2.4%
20.5%
21.4%
18.9%
1,172
97.9%
93.5%
West Bank and Gaza
0.1%
4.2%
19.4%
10.2%
937
Yemen
9.8%
10.1%
3.7%
1.1%
237
Zambia
74.3%
1.1%
21.4%
23.3%
300
39.7%
37.1%
357
Zimbabwe
4,489
95.9%
2.8
69.7%
66.4%
12
71.6%
61.4% 83.6%
12
1.8
46 2.0
Preliminary Analysis
Tanzania
Aid
Natural capital Informal training
% population which has an account at a formal financial institution
% social insurance coverage
% of population living under $1.25
Means to cover basic needs
Human capital Formal education and vocational training
2.8
2.1
-
27
Indicator Data (10 of 10)
50
1.11
0.57
123.6
29%
197 181
2.0%
19%
37.0
12%
18.9%
19.9%
3.1
25.2%
48.8%
52.8
8.1%
3.4%
0.2
80.7%
Togo
11%
60%
28%
41
0.27
0.63
135.8
15%
Trinidad and Tobago
92%
94%
99%
972
3.56
1.45
97.7
9%
Tunisia
90%
97%
100%
297
3.28
1.16
114.3
<5.0%
8
1.6%
Turkey
91%
100%
100%
665
2.40
0.93
126.7
<5.0%
5,157
14.0%
70% 19%
0.55
2.6%
11.4
5%
4.2%
80%
0.50
4.0%
62%
0.47
71%
100%
129
4.42
1.17
117.6
<5.0%
75%
15%
44
1.31
0.44
110.6
26%
Ukraine
94%
98%
100%
293
7.60
1.38
118.5
United Arab Emirates
98%
100%
94%
1,343
4.09
1.72
68.0
United Kingdom
100%
100%
100%
3,647
8.83
1.24
98.2
47
31.9
29%
United States
100%
99%
100%
8,895
9.82
0.96
105.9
7,507
501.2
45%
96%
100%
99%
1,308
5.55
1.55
128.8
7.3%
0.5
3.1
57%
1,309
18.9%
43.7%
39.7%
36.7%
346.0
23%
2,612
0.3%
9.4%
9.1%
17.3%
60.0
29%
5.1%
35.9
<5.0%
8
87%
100%
105
11.97
0.74
139.7
6%
30
60.8%
7.2%
58%
91%
24%
116
1.70
0.59
134.5
7%
6
60.2%
21.4%
Venezuela, RB
91%
93%
100%
593
1.13
1.02
114.5
<5.0%
188
102
1.14
1.31
132.3
13%
2,325
0.74
93.4
95%
96%
82%
94%
3.0
0.65
100%
75%
0.41
<5.0%
Vanuatu
94%
3.8
2.4%
99%
Vietnam
3.5
0.52
10.3%
34%
West Bank and Gaza
0.47
4%
Turkmenistan
Uzbekistan
84%
2.0
Uganda
Uruguay
8.5%
Score on the disaster risk reduction progress scale
38%
30.0
15.1%
Priority given to disaster risk reduction within legislation score
71%
29.4%
22.1%
% of the population who always vote in national elections
39%
36.9%
% population volunteering for any kind of organisation
Timor-Leste
38.1%
# people volunteering for the RC/RC ('000s)
13.2%
556
% of children in employment
1,512
7%
% of women 20-24 who were first married or in union before the age of 18
35%
Prevalence of undernourishment
138.9 125.8
Food production index (2012) (2004-2006 = 100)
0.56 1.38
# mobile subscriptions per capita
0.24 2.08
# nurses and midwives per 1000 people
41 215
Health expenditure per year per capita
15% 100%
% population access with access to electricity
53% 96%
% of the population with access to sanitation
12% 93%
0.78 10.2%
58%
0.71
3.0
15%
89%
0.69
2.0
38%
53%
0.45
0.6
3.0
5.1%
2.3
19%
0.31
13.0%
301.2
8%
0.48
32.2%
16.1%
12.0
4%
41.6%
34.4%
3.5
27%
9.3%
3.5
2.0 2.8
4.0
100
Yemen
53%
55%
45%
71
0.68
0.69
142.1
26%
Zambia
43%
63%
19%
96
0.78
0.72
155.6
48%
Zimbabwe
40%
80%
37%
1.25
0.96
96.9
32%
220 15.5% 120
49.3%
49%
2.3 0.47
14.0%
40%
3.8
0.34
28
Preliminary Analysis
Tanzania Thailand
Links and social networks
% of men who consider a husband to be justified in hitting or beating his wife
Principles and values
% of women 15-19 who have ever experienced sexual violence
Resources
# of people made homeless by a disaster between 2008-2014
% of the population with access to a clean water source
Services
Governance Structures Policy and planning for disasters
Partici-pation in politics
World Justice Project Overal Score (2014)
Social capital
% of the adult population who are a member of a group in the community
Physical capital
Annex 2: Country Classifications
Country Classifications (1 of 3) Region South Asia Europe & Central Asia Middle East & North Africa Sub-Saharan Africa Latin America & Caribbean Europe & Central Asia East Asia & Pacific Europe & Central Asia Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Latin America & Caribbean Europe & Central Asia Europe & Central Asia Latin America & Caribbean Sub-Saharan Africa South Asia Latin America & Caribbean Europe & Central Asia Sub-Saharan Africa Latin America & Caribbean East Asia & Pacific Europe & Central Asia Sub-Saharan Africa Sub-Saharan Africa Sub-Saharan Africa East Asia & Pacific Sub-Saharan Africa North America Sub-Saharan Africa Sub-Saharan Africa Europe & Central Asia Latin America & Caribbean East Asia & Pacific Latin America & Caribbean Sub-Saharan Africa Sub-Saharan Africa Sub-Saharan Africa Latin America & Caribbean Sub-Saharan Africa Europe & Central Asia Latin America & Caribbean Latin America & Caribbean Europe & Central Asia Europe & Central Asia Europe & Central Asia Middle East & North Africa Latin America & Caribbean Latin America & Caribbean Middle East & North Africa Latin America & Caribbean Sub-Saharan Africa Sub-Saharan Africa Europe & Central Asia Sub-Saharan Africa East Asia & Pacific Europe & Central Asia Europe & Central Asia East Asia & Pacific Sub-Saharan Africa Sub-Saharan Africa Europe & Central Asia Europe & Central Asia Sub-Saharan Africa Europe & Central Asia East Asia & Pacific Latin America & Caribbean Sub-Saharan Africa Sub-Saharan Africa Latin America & Caribbean
Income Group Low income Upper middle income Upper middle income Upper middle income Upper middle income Lower middle income High income: OECD High income: OECD Upper middle income High income: nonOECD High income: nonOECD Low income High income: nonOECD Upper middle income High income: OECD Upper middle income Low income Lower middle income Lower middle income Upper middle income Upper middle income Upper middle income High income: nonOECD Upper middle income Low income Low income Lower middle income Low income Lower middle income High income: OECD Low income Low income High income: nonOECD High income: OECD Upper middle income Upper middle income Low income Lower middle income Upper middle income Lower middle income High income: nonOECD Upper middle income High income: nonOECD High income: nonOECD High income: OECD High income: OECD Lower middle income Upper middle income Upper middle income Lower middle income Lower middle income High income: nonOECD Low income High income: OECD Low income Upper middle income High income: OECD High income: OECD High income: nonOECD Upper middle income Low income Lower middle income High income: OECD Lower middle income High income: OECD High income: nonOECD Lower middle income Low income Low income Lower middle income
Financial Capital Human Capital
4th Quintile 3rd Quintile 3rd Quintile 3rd Quintile 2nd Quintile 3rd Quintile 1st Quintile 1st Quintile 3rd Quintile Insufficient Data 3rd Quintile 3rd Quintile 5th Quintile 2nd Quintile 1st Quintile 4th Quintile 5th Quintile 4th Quintile 3rd Quintile 2nd Quintile 3rd Quintile 2nd Quintile Insufficient Data 2nd Quintile 4th Quintile 5th Quintile 4th Quintile 5th Quintile 4th Quintile 1st Quintile 5th Quintile 5th Quintile Insufficient Data 2nd Quintile 2nd Quintile 2nd Quintile 5th Quintile 5th Quintile 4th Quintile 2nd Quintile 3rd Quintile 1st Quintile 5th Quintile Insufficient Data 1st Quintile 1st Quintile 1st Quintile 5th Quintile 3rd Quintile 3rd Quintile 3rd Quintile 4th Quintile 5th Quintile 5th Quintile 1st Quintile 3rd Quintile 5th Quintile 1st Quintile 1st Quintile Insufficient Data 4th Quintile 5th Quintile 2nd Quintile 1st Quintile 3rd Quintile 1st Quintile Insufficient Data 4th Quintile 5th Quintile 5th Quintile 5th Quintile
4th Quintile 4th Quintile 2nd Quintile 3rd Quintile 2nd Quintile 2nd Quintile 1st Quintile 1st Quintile 3rd Quintile Insufficient Data 4th Quintile 4th Quintile 5th Quintile 2nd Quintile 1st Quintile 4th Quintile 5th Quintile 5th Quintile 2nd Quintile 1st Quintile 4th Quintile 2nd Quintile 4th Quintile 3rd Quintile 5th Quintile 3rd Quintile 5th Quintile 4th Quintile 3rd Quintile 1st Quintile 5th Quintile 5th Quintile Insufficient Data 1st Quintile 1st Quintile 2nd Quintile 5th Quintile 4th Quintile 4th Quintile 2nd Quintile 5th Quintile 2nd Quintile 1st Quintile Insufficient Data 3rd Quintile 2nd Quintile 1st Quintile 5th Quintile 4th Quintile 2nd Quintile 3rd Quintile 3rd Quintile 5th Quintile 5th Quintile 2nd Quintile 3rd Quintile 5th Quintile 1st Quintile 1st Quintile Insufficient Data 4th Quintile 5th Quintile 2nd Quintile 1st Quintile 4th Quintile 2nd Quintile Insufficient Data 3rd Quintile 4th Quintile 5th Quintile 4th Quintile
Natural Capital Physical Capital
4th Quintile 3rd Quintile 4th Quintile 1st Quintile 3rd Quintile 4th Quintile 2nd Quintile 3rd Quintile 5th Quintile 4th Quintile 5th Quintile 4th Quintile 3rd Quintile 4th Quintile 5th Quintile 1st Quintile 4th Quintile 3rd Quintile 1st Quintile 4th Quintile 3rd Quintile 1st Quintile 3rd Quintile 4th Quintile 4th Quintile 5th Quintile 4th Quintile 2nd Quintile 1st Quintile 1st Quintile 3rd Quintile 4th Quintile 5th Quintile 1st Quintile 3rd Quintile 1st Quintile 2nd Quintile 1st Quintile 1st Quintile 1st Quintile 2nd Quintile 4th Quintile 1st Quintile 5th Quintile 5th Quintile 5th Quintile 4th Quintile 5th Quintile 3rd Quintile 1st Quintile 5th Quintile 2nd Quintile 2nd Quintile 4th Quintile 2nd Quintile 2nd Quintile 1st Quintile 2nd Quintile 3rd Quintile 3rd Quintile 1st Quintile 4th Quintile 3rd Quintile 4th Quintile 3rd Quintile 3rd Quintile 5th Quintile 1st Quintile 2nd Quintile 2nd Quintile 1st Quintile
5th Quintile 2nd Quintile 3rd Quintile 4th Quintile 3rd Quintile 2nd Quintile 1st Quintile 1st Quintile 2nd Quintile 2nd Quintile 1st Quintile 5th Quintile 3rd Quintile 2nd Quintile 1st Quintile 3rd Quintile 4th Quintile 3rd Quintile 4th Quintile 2nd Quintile 3rd Quintile 2nd Quintile 2nd Quintile 1st Quintile 5th Quintile 5th Quintile 4th Quintile 4th Quintile 4th Quintile 1st Quintile 5th Quintile 5th Quintile 1st Quintile 3rd Quintile 4th Quintile 4th Quintile 4th Quintile 5th Quintile 5th Quintile 2nd Quintile 5th Quintile 1st Quintile 3rd Quintile 3rd Quintile 2nd Quintile 1st Quintile 1st Quintile 4th Quintile 3rd Quintile 3rd Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile 1st Quintile 5th Quintile 4th Quintile 1st Quintile 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 3rd Quintile 1st Quintile 4th Quintile 2nd Quintile 3rd Quintile 3rd Quintile 5th Quintile 5th Quintile 4th Quintile
Social Capital
3rd Quintile 3rd Quintile 5th Quintile 5th Quintile 3rd Quintile 3rd Quintile 1st Quintile 1st Quintile 2nd Quintile 5th Quintile 5th Quintile 4th Quintile 5th Quintile 1st Quintile 1st Quintile 5th Quintile 4th Quintile 4th Quintile 3rd Quintile 1st Quintile 4th Quintile 4th Quintile Insufficient Data 4th Quintile 5th Quintile 3rd Quintile 1st Quintile 2nd Quintile 5th Quintile 1st Quintile 5th Quintile 5th Quintile Insufficient Data 3rd Quintile 4th Quintile 2nd Quintile 2nd Quintile 4th Quintile 5th Quintile 1st Quintile 4th Quintile 4th Quintile 3rd Quintile Insufficient Data 3rd Quintile 5th Quintile 2nd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 5th Quintile 5th Quintile 5th Quintile 4th Quintile 5th Quintile 1st Quintile 1st Quintile Insufficient Data 4th Quintile 5th Quintile 3rd Quintile 1st Quintile 3rd Quintile 4th Quintile Insufficient Data 2nd Quintile 5th Quintile 5th Quintile 2nd Quintile
Governance Structures
5th Quintile 4th Quintile 3rd Quintile 5th Quintile 2nd Quintile 2nd Quintile 1st Quintile 2nd Quintile 5th Quintile Insufficient Data 4th Quintile 3rd Quintile 1st Quintile 3rd Quintile 1st Quintile Insufficient Data Insufficient Data Insufficient Data 5th Quintile 2nd Quintile 3rd Quintile 1st Quintile 5th Quintile 2nd Quintile 3rd Quintile 4th Quintile 3rd Quintile 5th Quintile 5th Quintile 1st Quintile Insufficient Data Insufficient Data Insufficient Data 2nd Quintile 4th Quintile 2nd Quintile 5th Quintile Insufficient Data Insufficient Data 1st Quintile 5th Quintile 2nd Quintile 1st Quintile Insufficient Data 1st Quintile 3rd Quintile 1st Quintile Insufficient Data 4th Quintile 3rd Quintile 4th Quintile 4th Quintile Insufficient Data Insufficient Data 2nd Quintile 5th Quintile 5th Quintile 1st Quintile 1st Quintile Insufficient Data Insufficient Data Insufficient Data 3rd Quintile 1st Quintile 2nd Quintile 2nd Quintile Insufficient Data 4th Quintile Insufficient Data 5th Quintile Insufficient Data
Preliminary Analysis
Country Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bahamas, The Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Central African Republic Chad Channel Islands Chile China Colombia Comoros Congo, Dem. Rep. Congo, Rep. Costa Rica Cote d'Ivoire Croatia Cuba Curacao Cyprus Czech Republic Denmark Djibouti Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Fiji Finland France French Polynesia Gabon Gambia, The Georgia Germany Ghana Greece Guam Guatemala Guinea Guinea-Bissau Guyana
30
Country Classifications (2 of 3) Region Latin America & Caribbean Latin America & Caribbean East Asia & Pacific Europe & Central Asia Europe & Central Asia South Asia East Asia & Pacific Middle East & North Africa Middle East & North Africa Europe & Central Asia Middle East & North Africa Europe & Central Asia Latin America & Caribbean East Asia & Pacific Middle East & North Africa Europe & Central Asia Sub-Saharan Africa East Asia & Pacific East Asia & Pacific Europe & Central Asia Middle East & North Africa Europe & Central Asia East Asia & Pacific Europe & Central Asia Middle East & North Africa Sub-Saharan Africa Sub-Saharan Africa Middle East & North Africa Europe & Central Asia Europe & Central Asia East Asia & Pacific Europe & Central Asia Sub-Saharan Africa Sub-Saharan Africa East Asia & Pacific South Asia Sub-Saharan Africa Middle East & North Africa Sub-Saharan Africa Sub-Saharan Africa Latin America & Caribbean Europe & Central Asia East Asia & Pacific Europe & Central Asia Middle East & North Africa Sub-Saharan Africa East Asia & Pacific Sub-Saharan Africa South Asia Europe & Central Asia East Asia & Pacific East Asia & Pacific Latin America & Caribbean Sub-Saharan Africa Sub-Saharan Africa Europe & Central Asia Middle East & North Africa South Asia Latin America & Caribbean East Asia & Pacific Latin America & Caribbean Latin America & Caribbean East Asia & Pacific Europe & Central Asia Europe & Central Asia Latin America & Caribbean Middle East & North Africa Europe & Central Asia Europe & Central Asia Sub-Saharan Africa
Income Group Low income Lower middle income High income: nonOECD Upper middle income High income: OECD Lower middle income Lower middle income Upper middle income Upper middle income High income: OECD High income: OECD High income: OECD Upper middle income High income: OECD Upper middle income Upper middle income Low income Low income High income: OECD High income: nonOECD Lower middle income Lower middle income High income: nonOECD Upper middle income Lower middle income Low income Upper middle income High income: nonOECD High income: OECD High income: nonOECD Upper middle income Low income Low income Upper middle income Upper middle income Low income High income: nonOECD Lower middle income Upper middle income Upper middle income Lower middle income Lower middle income Upper middle income Lower middle income Low income Low income Upper middle income Low income High income: OECD High income: nonOECD High income: OECD Lower middle income Low income Lower middle income High income: OECD High income: nonOECD Lower middle income Upper middle income Lower middle income Lower middle income Upper middle income Lower middle income High income: OECD High income: OECD High income: nonOECD High income: nonOECD High income: nonOECD Low income
Financial Capital Human Capital
4th Quintile 4th Quintile 1st Quintile 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 2nd Quintile 3rd Quintile 1st Quintile 1st Quintile 2nd Quintile 2nd Quintile 1st Quintile 2nd Quintile 2nd Quintile 3rd Quintile 5th Quintile 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 4th Quintile 2nd Quintile 2nd Quintile 5th Quintile 5th Quintile 5th Quintile 2nd Quintile 1st Quintile Insufficient Data 2nd Quintile 5th Quintile 5th Quintile 2nd Quintile 4th Quintile 5th Quintile 1st Quintile 4th Quintile 2nd Quintile 2nd Quintile 3rd Quintile 2nd Quintile 2nd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 4th Quintile 4th Quintile 1st Quintile Insufficient Data 1st Quintile 4th Quintile 5th Quintile 4th Quintile 1st Quintile 3rd Quintile 4th Quintile 3rd Quintile 5th Quintile 4th Quintile 3rd Quintile 3rd Quintile 1st Quintile 1st Quintile Insufficient Data 2nd Quintile 1st Quintile 2nd Quintile 4th Quintile
5th Quintile 2nd Quintile 5th Quintile 1st Quintile 2nd Quintile 3rd Quintile 1st Quintile 3rd Quintile 4th Quintile 3rd Quintile 2nd Quintile 1st Quintile 4th Quintile 1st Quintile 2nd Quintile 2nd Quintile 3rd Quintile 1st Quintile 1st Quintile Insufficient Data 4th Quintile 1st Quintile 5th Quintile 2nd Quintile 2nd Quintile 4th Quintile 5th Quintile 3rd Quintile 3rd Quintile 2nd Quintile 4th Quintile 2nd Quintile 5th Quintile 5th Quintile 2nd Quintile 3rd Quintile 5th Quintile 4th Quintile 5th Quintile 5th Quintile 1st Quintile 1st Quintile 2nd Quintile 3rd Quintile 3rd Quintile 5th Quintile 4th Quintile 4th Quintile 4th Quintile 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile 5th Quintile 1st Quintile 4th Quintile 4th Quintile 3rd Quintile 4th Quintile 3rd Quintile 2nd Quintile 3rd Quintile 1st Quintile 3rd Quintile 3rd Quintile 4th Quintile 1st Quintile 1st Quintile 3rd Quintile
Natural Capital Physical Capital
2nd Quintile 1st Quintile 5th Quintile 4th Quintile 2nd Quintile 3rd Quintile 1st Quintile 4th Quintile 5th Quintile 2nd Quintile 5th Quintile 3rd Quintile 1st Quintile 2nd Quintile 5th Quintile 3rd Quintile 2nd Quintile 4th Quintile 4th Quintile 5th Quintile 5th Quintile 4th Quintile 3rd Quintile 2nd Quintile 5th Quintile 3rd Quintile 2nd Quintile 5th Quintile 3rd Quintile 5th Quintile 5th Quintile 4th Quintile 1st Quintile 3rd Quintile 2nd Quintile 5th Quintile 3rd Quintile 5th Quintile 4th Quintile 1st Quintile 2nd Quintile 5th Quintile 2nd Quintile 5th Quintile 4th Quintile 1st Quintile 2nd Quintile 3rd Quintile 3rd Quintile 4th Quintile 1st Quintile 1st Quintile 1st Quintile 5th Quintile 3rd Quintile 2nd Quintile 5th Quintile 2nd Quintile 1st Quintile 1st Quintile 2nd Quintile 1st Quintile 1st Quintile 3rd Quintile 1st Quintile 2nd Quintile 5th Quintile 3rd Quintile 2nd Quintile 2nd Quintile
5th Quintile 4th Quintile 3rd Quintile 2nd Quintile 1st Quintile 4th Quintile 4th Quintile 4th Quintile 4th Quintile 1st Quintile 1st Quintile 2nd Quintile 3rd Quintile 2nd Quintile 2nd Quintile 2nd Quintile 5th Quintile 5th Quintile 3rd Quintile 1st Quintile 1st Quintile 3rd Quintile 4th Quintile 1st Quintile 3rd Quintile 5th Quintile 5th Quintile 2nd Quintile 1st Quintile 1st Quintile 3rd Quintile 3rd Quintile 5th Quintile 5th Quintile 1st Quintile 1st Quintile 4th Quintile 1st Quintile 4th Quintile 2nd Quintile 3rd Quintile 2nd Quintile 3rd Quintile 2nd Quintile 4th Quintile 5th Quintile 5th Quintile 4th Quintile 4th Quintile 1st Quintile 3rd Quintile 1st Quintile 4th Quintile 5th Quintile 5th Quintile 1st Quintile 2nd Quintile 5th Quintile 3rd Quintile 4th Quintile 2nd Quintile 4th Quintile 4th Quintile 2nd Quintile 1st Quintile 3rd Quintile 1st Quintile 3rd Quintile 2nd Quintile 5th Quintile
Social Capital
2nd Quintile 2nd Quintile 1st Quintile 3rd Quintile 3rd Quintile 2nd Quintile 1st Quintile 1st Quintile 4th Quintile 2nd Quintile 2nd Quintile 1st Quintile 2nd Quintile 2nd Quintile 4th Quintile 1st Quintile 3rd Quintile 1st Quintile 1st Quintile Insufficient Data 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile 2nd Quintile 3rd Quintile 4th Quintile 2nd Quintile 5th Quintile 1st Quintile Insufficient Data 3rd Quintile 4th Quintile 3rd Quintile 3rd Quintile 2nd Quintile 5th Quintile 5th Quintile 5th Quintile 5th Quintile 2nd Quintile 3rd Quintile 1st Quintile 4th Quintile 3rd Quintile 4th Quintile 1st Quintile 3rd Quintile 3rd Quintile 1st Quintile Insufficient Data 1st Quintile 4th Quintile 5th Quintile 2nd Quintile 1st Quintile Insufficient Data 2nd Quintile 2nd Quintile 5th Quintile 2nd Quintile 4th Quintile 1st Quintile 4th Quintile 2nd Quintile Insufficient Data 3rd Quintile 3rd Quintile 4th Quintile 2nd Quintile
Governance Structures
Insufficient Data 2nd Quintile 3rd Quintile 1st Quintile Insufficient Data 4th Quintile 3rd Quintile 5th Quintile 4th Quintile Insufficient Data Insufficient Data 2nd Quintile 2nd Quintile 1st Quintile 3rd Quintile 4th Quintile 4th Quintile 3rd Quintile 1st Quintile Insufficient Data 5th Quintile 4th Quintile 5th Quintile Insufficient Data 4th Quintile 5th Quintile 5th Quintile 4th Quintile Insufficient Data Insufficient Data Insufficient Data 3rd Quintile 4th Quintile 4th Quintile 3rd Quintile 5th Quintile Insufficient Data Insufficient Data Insufficient Data 3rd Quintile 2nd Quintile 4th Quintile 4th Quintile Insufficient Data 4th Quintile 1st Quintile 5th Quintile 1st Quintile 5th Quintile 1st Quintile Insufficient Data 1st Quintile 3rd Quintile Insufficient Data 3rd Quintile 1st Quintile Insufficient Data 4th Quintile 4th Quintile Insufficient Data 2nd Quintile 2nd Quintile 2nd Quintile 2nd Quintile 1st Quintile Insufficient Data 4th Quintile 2nd Quintile 5th Quintile 3rd Quintile
Preliminary Analysis
Country Haiti Honduras Hong Kong SAR, China Hungary Iceland India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Luxembourg Macao SAR, China Macedonia, FYR Madagascar Malawi Malaysia Maldives Mali Malta Mauritania Mauritius Mexico Moldova Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russian Federation Rwanda
31
Country Classifications (3 of 3) Region East Asia & Pacific Sub-Saharan Africa Middle East & North Africa Sub-Saharan Africa Europe & Central Asia Sub-Saharan Africa East Asia & Pacific Europe & Central Asia Europe & Central Asia East Asia & Pacific Sub-Saharan Africa Sub-Saharan Africa Sub-Saharan Africa Europe & Central Asia South Asia Latin America & Caribbean Sub-Saharan Africa Latin America & Caribbean Sub-Saharan Africa Europe & Central Asia Europe & Central Asia Middle East & North Africa Europe & Central Asia Sub-Saharan Africa East Asia & Pacific Europe & Central Asia Sub-Saharan Africa Latin America & Caribbean Middle East & North Africa Europe & Central Asia Europe & Central Asia Sub-Saharan Africa Europe & Central Asia Middle East & North Africa Europe & Central Asia North America Latin America & Caribbean Europe & Central Asia East Asia & Pacific Latin America & Caribbean East Asia & Pacific Middle East & North Africa Middle East & North Africa Sub-Saharan Africa Sub-Saharan Africa
Income Group Lower middle income Lower middle income High income: nonOECD Lower middle income Upper middle income Low income High income: nonOECD High income: OECD High income: OECD Lower middle income Low income Upper middle income Lower middle income High income: OECD Lower middle income Upper middle income Lower middle income Upper middle income Lower middle income High income: OECD High income: OECD Lower middle income Low income Low income Upper middle income
Financial Capital Human Capital
5th Quintile 5th Quintile 4th Quintile 4th Quintile 2nd Quintile 4th Quintile 1st Quintile 1st Quintile 1st Quintile 5th Quintile 3rd Quintile 2nd Quintile Insufficient Data 1st Quintile 2nd Quintile 5th Quintile 4th Quintile 5th Quintile 4th Quintile 1st Quintile 1st Quintile 3rd Quintile 4th Quintile 4th Quintile 2nd Quintile 5th Quintile Low income 5th Quintile High income: nonOECD 3rd Quintile Upper middle income 3rd Quintile Upper middle income 2nd Quintile Upper middle income 5th Quintile Low income 4th Quintile Lower middle income 1st Quintile High income: nonOECD 3rd Quintile High income: OECD 1st Quintile High income: OECD 2nd Quintile High income: nonOECD 3rd Quintile Lower middle income 4th Quintile Lower middle income 5th Quintile Upper middle income 3rd Quintile Lower middle income 3rd Quintile 3rd Quintile Lower middle income 4th Quintile Lower middle income 4th Quintile Low income 2nd Quintile
2nd Quintile 4th Quintile 3rd Quintile 5th Quintile 1st Quintile 4th Quintile 3rd Quintile 2nd Quintile 2nd Quintile 5th Quintile 5th Quintile 2nd Quintile 5th Quintile 1st Quintile 3rd Quintile 3rd Quintile 5th Quintile 3rd Quintile 4th Quintile 1st Quintile 1st Quintile 3rd Quintile 3rd Quintile 4th Quintile 1st Quintile 5th Quintile 3rd Quintile 3rd Quintile 2nd Quintile 1st Quintile 1st Quintile 3rd Quintile 1st Quintile 4th Quintile 1st Quintile 1st Quintile 2nd Quintile 2nd Quintile 5th Quintile 2nd Quintile 2nd Quintile 4th Quintile 5th Quintile 5th Quintile 4th Quintile
Natural Capital Physical Capital
4th Quintile 2nd Quintile 4th Quintile 4th Quintile 4th Quintile 2nd Quintile 5th Quintile 4th Quintile 2nd Quintile 1st Quintile 4th Quintile 4th Quintile 5th Quintile 3rd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 1st Quintile 3rd Quintile 2nd Quintile 3rd Quintile 5th Quintile 5th Quintile 1st Quintile 3rd Quintile 2nd Quintile 3rd Quintile 2nd Quintile 4th Quintile 4th Quintile 5th Quintile 4th Quintile 4th Quintile 5th Quintile 2nd Quintile 2nd Quintile 1st Quintile 5th Quintile 2nd Quintile 3rd Quintile 1st Quintile 5th Quintile 5th Quintile 1st Quintile 3rd Quintile
3rd Quintile 4th Quintile 2nd Quintile 4th Quintile 2nd Quintile 5th Quintile 1st Quintile 2nd Quintile 1st Quintile 4th Quintile 5th Quintile 3rd Quintile 5th Quintile 1st Quintile 4th Quintile 4th Quintile 5th Quintile 2nd Quintile 5th Quintile 1st Quintile 1st Quintile 3rd Quintile 4th Quintile 5th Quintile 2nd Quintile 5th Quintile 5th Quintile 2nd Quintile 2nd Quintile 3rd Quintile 3rd Quintile 5th Quintile 2nd Quintile 2nd Quintile 1st Quintile 2nd Quintile 1st Quintile 2nd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 3rd Quintile 4th Quintile 5th Quintile 5th Quintile
Social Capital
5th Quintile 4th Quintile 4th Quintile 3rd Quintile 1st Quintile 5th Quintile 2nd Quintile 4th Quintile 1st Quintile 5th Quintile 5th Quintile 1st Quintile 5th Quintile 2nd Quintile 2nd Quintile 2nd Quintile 2nd Quintile 4th Quintile 2nd Quintile 2nd Quintile 1st Quintile 3rd Quintile 1st Quintile 4th Quintile 3rd Quintile 4th Quintile 4th Quintile 2nd Quintile 4th Quintile 3rd Quintile 2nd Quintile 4th Quintile 1st Quintile Insufficient Data 1st Quintile 1st Quintile 4th Quintile 1st Quintile 5th Quintile 3rd Quintile 2nd Quintile Insufficient Data 4th Quintile 5th Quintile 1st Quintile
Governance Structures
3rd Quintile Insufficient Data Insufficient Data 4th Quintile Insufficient Data 5th Quintile 2nd Quintile Insufficient Data 2nd Quintile 5th Quintile Insufficient Data 3rd Quintile Insufficient Data 2nd Quintile 3rd Quintile 3rd Quintile Insufficient Data Insufficient Data Insufficient Data 1st Quintile 1st Quintile 3rd Quintile Insufficient Data 3rd Quintile 1st Quintile Insufficient Data Insufficient Data 1st Quintile 4th Quintile 2nd Quintile Insufficient Data 5th Quintile 3rd Quintile 1st Quintile 1st Quintile 2nd Quintile 2nd Quintile 4th Quintile 4th Quintile 5th Quintile 2nd Quintile Insufficient Data 5th Quintile 3rd Quintile 5th Quintile
Preliminary Analysis
Country Samoa Sao Tome and Principe Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Solomon Islands Somalia South Africa South Sudan Spain Sri Lanka St. Lucia Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, RB Vietnam West Bank and Gaza Yemen Zambia Zimbabwe
32
Annex 3: Methodology and Data Availability
Approach for Selecting Indicators 1.
2. 3.
Extracted indicators from the resilience literature: a. Completed a desk review of resilience literature and selected indicators which could be used to assess one or more capitals of resilience; b. Removed any indicators for which there is no publically available data; c. Aligned remaining indicators to the capitals and the assets. Extracted indicators from additional targeted data sources: a. Ensured coverage of all assets by adding indicators from publically available data sources. Selected indicators for the initial mapping exercise: a. Identified categories for the indicators grouped under each asset; b. Selected one or two indicators per category by prioritizing indicators which are: overarching, have broad geographic coverage and have recent quantitive data available. c. Refined the list of indicators through discussions with staff at the IFRC.
• • • • •
• • •
EM-DAT Database (CRED) Community resilience framework (IFRC) Measuring resilience: a concept note on the resilience tool (FAO) Guidelines for Resilience Systems Analysis (OECD) Human Development Report 2014. Sustaining Human Progress: Reducing Vulnerabilities and Building Resilience (UNDP) Hyogo framework for action (UNISDR) Country disaster loss databases (UNISDR) Community resilience performance measurement methodology and standard indicators (URD)
Preliminary Analysis
Resilience Specific Resources
General Development Resources • • • • •
• • • • • • • • •
Federation Wide Reporting System (IFRC) Global Road Safety Partnership (IFRC) FAOSTAT (FAO) Global Green Growth Institute Database (GGGI) Logistics performance index and number of natural disasters (Humanitarian data exchange) OECD Database (OECD) Household economy approach (Save the Children) UNICEF website (UNICEF) Global health observatory (WHO) Gender indicators (World Bank) Living Standards Measurement (World Bank) Prospects data: migration and remittances (World Bank) World Development Indicators (World Bank) World Values Survey
34
Data Availability (1 of 3)
Capital
Financial capital
Asset
Means to cover basic needs
Formal Education Human capital
Vocational training Informal training
Natural capital
% social insurance coverage % population which has an account at a formal financial institution % female population with an account at a formal financial institution Average financial aid received 2008-2014 % children of primary school age attending school % adult population who are literate # vocational pupils at secondary school # of people who are indirect health recipients of IFRC programmes
Level of air pollution Renewable water available within a country per capita Environmental Average carbon content in the conservation topsoil (% total weight) Combustible renewables and waste (% of total energy) Score on the GEF benefits index for biodiversity
World Bank
122
4,170
59%
World Bank
122
4,170
59%
OECD
130
4,633
65%
97
3,605
51%
127
4,043
57%
147
4,636
65%
39
740
10%
GGGI World Bank
155
5,394
76%
165
5,459
77%
FAO World Bank World Bank
178
5,688
80%
136
6,813
96%
173
5,734
81%
UNICEF World Bank World Bank IFRC
35
Preliminary Analysis
Financial aid
Indicator % of population living under $1.25
# of People # of Covered Percent of Total Countries by with Indicator PopSource Indicator (millions) ulation World Bank 116 4,210 59% World Bank 85 3,346 47%
Data Availability (2 of 3)
Capital
Social capital
36
Preliminary Analysis
Physical capital
# of People Covered Percent # of Countries by of Total with Indicator PopAsset Indicator Source Indicator (millions) ulation % of the population with World access to sanitation Bank 166 5,606 79% % of the population with World access to a clean water source Bank 167 5,573 78% % population access with World access to electricity Bank 179 5,781 81% Services Health expenditure per year World Bank per capita 158 5,442 77% # nurses and midwives per World Bank capita 158 5,444 77% # mobile subscriptions per World capita Bank 170 5,600 79% Food production index (2012) World Bank (2004-2006 = 100) 182 7,086 100% # people who are Resources undernourished (2010-2012) FAO 128 6,015 85% # of people made homeless by a disaster between 2008-2014 CRED 99 2,531 36% % of women 15-19 who have ever experienced sexual violence UNICEF 33 1,987 28% % of men who consider a husband to be justified in Principles and hitting or beating his wife UNICEF 52 2,730 38% values % of women 20-24 who were first married or in union before the age of 20 UNICEF 96 3,756 53% World % of children in employment Bank 77 3,098 44% # people volunteering for the National Red Cross and Red IFRC 149 5,261 74% Links and social Crescent Societies networks: % population volunteering for voluntary any kind of organisation WVS 107 3,806 54% service % of the adult population who are a member of a group in the community WVS 46 1,078 15%
Data Availability (3 of 3)
Asset
Indicator
Institutional and Governance
Participation in % of the population who always vote in national politics elections Policy and planning for World Justice Project Overall disasters Score (2014) Policy and planning for disasters DRM legal frameworks score Policy and planning for Score on the disaster risk disasters reduction progress scale
Percent of Total Population
WVS
45
1,012
14%
WJP
79
3,101
44%
IFRC
26
486
7%
World Bank
72
1,914
27%
37
Preliminary Analysis
Capital
# of People # of Covered Countries by with Indicator Source Indicator (millions)