INFORM REPORT 2020

Shared evidence for managing crises and disasters

Note: The geographical boundaries and names shown and the designations used in this report are not warranted to be error free nor do they necessarily imply official endorsement or acceptance by INFORM or any INFORM partner organisation. Every effort has been made to ensure the accuracy of the information contained in this report. All information was believed to be correct as of January 2020.

INFORM is a collaboration of the Inter-Agency Standing Committee and the European Commission. This report is produced by the United Nations Office for the Coordination of Humanitarian Affairs on behalf of all INFORM Partners. The Joint Research Centre of the European Commission is the scientific and technical lead of INFORM.

The European Commission support for the production of this publication does not constitute endorsement of the contents, which reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

For more information

https://drmkc.jrc.ec.europa.eu/inform-index

JRC Mission

As the science and knowledge service of the European Commission, the Joint Research Centre’s mission is to support EU policies with independent evidence throughout the whole policy cycle.

JRC 120275

EUR 30173 EN

PDF | ISBN 978-92-76-17910-8 | ISSN 1831-9424 | doi:10.2760/953633 | KJ-NA-30173-EN-N
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Luxembourg: Publications Office of the European Union, 2020

© European Union, 2020

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Inter-Agency Standing Committee and the European Commission, INFORM report 2020: Shared evidence for managing crisis and disaster, EUR 30173 EN Publications Office of the European Union, Luxembourg, 2020 ISBN 978-92-76-17910-8, doi:10.2760/953633, JRC120275

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Table of Contents

Welcome

About INFORM

INFORM Risk

INFORM Severity

Appendix

INFORM Risk Index Sources

WELCOME

Welcome to the INFORM 2020 report.

INFORM partners believe that the availability of shared analysis of crises and disasters can lead to better coordination of actors and better outcomes for at-risk and affected people. Specifically, INFORM creates a space and process for shared analysis that can support joint strategy development, planning and action to prevent, prepare for, respond to and recover from crises. This can bring together development, humanitarian and other actors to manage risk and respond better when crises do occur.

This report sets out INFORM’s vision for a suite of products to support decision-making that are easy to use and open to everyone. This vision involves bringing scientific rigour to the process of analysing crises and pooling expertise to develop shared methodologies. By working together, we can reduce the investments required by individual organisations, assure the quality of our analysis and make it available for the common good.

ABOUT INFORM

INFORM is a multi-stakeholder forum for developing shared, quantitative analysis relevant to humanitarian crises and disasters. INFORM includes organisations from across the multilateral system, including the humanitarian and development sector, donors, and technical partners. The Joint Research Center of European Commission is the scientific and technical lead for INFORM.

INFORM is developing a suite of quantitative, analytical products to support decision-making on humanitarian crises and disasters. These help make decisions at different stages of the disaster management cycle, specifically prevention, preparedness and response. INFORM develops methodologies and tools for use at the global level and also supports their application at subnational level.

INFORM principles

Global

INFORM Global products cover 191 countries and Subnational products include all parts of the region or country they cover.

Open

All INFORM products are freely available and the methodology and sources are open and transparent.

Reliable

INFORM products use the best available methods and data. INFORM partners have committed to make them available into the future.

Flexible

INFORM products can be easily adapted and included into the decision-making processes of users.

How INFORM products are used

INFORM products are used by all kinds of organisation and can be adapted to suit their decision-making processes. These are some examples:

WFP uses the uses the INFORM Risk Index in its Corporate Alert System - which analyses emerging risks to trigger timely and adequate preparedness and response - and to support the inter-agency Early Warning, Early Action and Readiness Analysis process.

ECHO uses INFORM products as part of its Integrated Analysis Framework, which supports decision-making on its Annual Aid Strategy.

IFRC uses the INFORM Risk Index as a baseline risk analysis for its Priority Countries and INFORM Subnational Risk Models in its Community Risk Assessments.

OCHA uses INFORM products to support decisions on funding from the CERF Underfunded Emergencies window.

In the Sahel region, the INFORM Sahel Subnational Risk Model has been used to support humanitarian and development planning, as well as the UN Integrated Strategy for the Sahel.

INFORM’s approach and products are increasingly recognised to support several key components of the post-2015 humanitarian, DRR and development agenda. Shared analysis and joint humanitarian and development action are principles recognised by the World Humanitarian Summit outcomes, Sendai Framework and Sustainable Development Goals.

Supporting INFORM

The approach of INFORM is inclusive and cost effective, with a small investment that has a multiplying effect through better targeted and more effective use of aid and development resources. INFORM has developed a 5 year project plan and budget, which provides an overview of activities carried out through the INFORM network. INFORM’s primary concern is long term sustainability. Therefore, it is seeking additional donors that are willing to make a long term commitment to INFORM.

INFORM RISK

INFORM RISK INDEX

The INFORM Risk Index is the first global, objective and transparent tool for understanding the risk of humanitarian crises and disasters. It can help identify where and why a crisis might occur, which means we can reduce the risk, build peoples’ resilience and prepare better for when crises do happen.

Use INFORM Risk

Prioritise countries by risk, or any of its components

Decide how best to reduce risk

Monitor risk trends

Adaptable

…for your organisation or region and the same methodology can be used for national and regional risk assessment.

Results and limitations of INFORM RISK

The INFORM Risk Index is a composite index, which is a simplified view of reality. Therefore, it should be used in conjunction with other sources of information. Full details of the methodology and a more detailed discussion of its limitations are available on the website.

https://drmkc.jrc.ec.europa.eu/inform-index

HOW IT WORKS

The INFORM Risk Index creates a risk profile for every country. Each has a rating between 0 and 10 for risk and all of its components, so its easy to compare.

Components of risk covered by the INFORM Risk Index

THE INFORM RISK INDEX MEASURES THE RISK OF HUMANITARIAN CRISIS AND DISASTERS IN 191 COUNTRIES

| COUNTRY | RISK | 3 YR TREND
| Afghanistan | 8.0 |
| Albania | 3.0 |
| Algeria | 4.0 |
| Angola | 5.2 |
| Antigua and Barbuda | 2.3 |
| Argentina | 2.7 |
| Armenia | 3.6 |
| Australia | 2.3 |
| Austria | 1.6 |
| Azerbaijan | 4.6 |
| Bahamas | 2.2 |
| Bahrain | 1.3 |
| Bangladesh | 6.0 |
| Barbados | 1.9 |
| Belarus | 1.9 |
| Belgium | 1.9 |
| Belize | 3.7 |
| Benin | 4.4 |
| Bhutan | 3.1 |
| Bolivia | 4.3 |
| Bosnia and Herzegovina | 3.6 |
| Botswana | 3.2 |
| Brazil | 4.3 |
| Brunei Darussalam | 1.6 |
| Bulgaria | 2.4 |
| Burkina Faso | 5.3 |
| Burundi | 6.2 |
| Cabo Verde | 2.6 |
| Cambodia | 4.8 |
| Cameroon | 6.0 |
| Canada | 2.4 |
| Central African Republic | 8.6 |
| Chad | 7.3 |
| Chile | 3.0 |
| China | 4.3 |
| Colombia | 5.4 |
| Comoros | 4.0 |
| Congo | 5.5 |
| Congo DR | 7.0 |
| Costa Rica | 3.0 |
| Côte d’Ivoire | 6.0 |
| Croatia | 2.1 |
| Cuba | 3.5 |
| Cyprus | 3.0 |
| Czech Republic | 1.2 |
| Denmark | 1.1 |
| Djibouti | 5.2 |
| Dominica | 3.5 |
| Dominican Republic | 3.8 |
| Ecuador | 4.0 |
| Egypt | 5.1 |
| El Salvador | 4.0 |
| Equatorial Guinea | 4.1 |
| Eritrea | 5.2 |
| Estonia | 0.9 |
| Eswatini | 3.9 |
| Ethiopia | 6.9 |
| Fiji | 2.9 |
| Finland | 0.6 |
| France | 2.3 |
| Gabon | 4.2 |
| Gambia | 4.2 |
| Georgia | 3.9 |
| Germany | 2.0 |
| Ghana | 3.8 |
| Greece | 3.1 |
| Grenada | 1.8 |
| Guatemala | 5.7 |
| Guinea | 5.1 |
| Guinea-Bissau | 4.6 |
| Guyana | 3.4 |
| Haiti | 6.6 |
| Honduras | 5.3 |
| Hungary | 1.9 |
| Iceland | 1.2 |
| India | 5.4 |
| Indonesia | 4.7 |
| Iran | 5.2 |
| Iraq | 7.0 |
| Ireland | 1.4 |
| Israel | 2.7 |
| Italy | 2.6 |
| Jamaica | 3.1 |
| Japan | 2.3 |
| Jordan | 4.6 |
| Kazakhstan | 1.9 |
| Kenya | 6.0 |
| Kiribati | 3.6 |
| Korea DPR | 5.2 |
| Korea Republic of | 2.1 |
| Kuwait | 1.8 |
| Kyrgyzstan | 3.9 |
| Lao PDR | 4.5 |
| Latvia | 1.5 |
| Lebanon | 5.2 |
| Lesotho | 4.2 |
| Liberia | 5.3 |
| Libya | 6.2 |
| Liechtenstein | 0.9 |
| Lithuania | 1.4 |
| Luxembourg | 0.9 |
| Madagascar | 5.2 |
| Malawi | 4.9 |
| Malaysia | 3.3 |
| Maldives | 2.4 |
| Mali | 6.4 |
| Malta | 1.9 |
| Marshall Islands | 3.7 |
| Mauritania | 5.7 |
| Mauritius | 2.0 |
| Mexico | 5.1 |
| Micronesia | 3.9 |
| Moldova Republic of | 3.0 |
| Mongolia | 2.8 |
| Montenegro | 2.2 |
| Morocco | 4.1 |
| Mozambique | 6.2 |
| Myanmar | 6.3 |
| Namibia | 3.8 |
| Nauru | 3.3 |
| Nepal | 5.4 |
| Netherlands | 1.4 |
| New Zealand | 1.6 |
| Nicaragua | 5.2 |
| Niger | 6.7 |
| Nigeria | 6.9 |
| North Macedonia | 2.6 |
| Norway | 0.9 |
| Oman | 2.5 |
| Pakistan | 6.3 |
| Palau | 2.5 |
| Palestine | 5.1 |
| Panama | 3.5 |
| Papua New Guinea | 5.8 |
| Paraguay | 3.3 |
| Peru | 4.6 |
| Philippines | 5.3 |
| Poland | 1.7 |
| Portugal | 1.6 |
| Qatar | 1.3 |
| Romania | 2.8 |
| Russian Federation | 4.0 |
| Rwanda | 4.7 |
| Saint Kitts and Nevis | 1.9 |
| Saint Lucia | 2.2 |
| Saint Vincent and the Grenadines | 2.0 |
| Samoa | 2.9 |
| Sao Tome and Principe | 2.5 |
| Saudi Arabia | 2.5 |
| Senegal | 5.0 |
| Serbia | 3.1 |
| Seychelles | 2.0 |
| Sierra Leone | 5.4 |
| Singapore | 0.5 |
| Slovakia | 1.6 |
| Slovenia | 1.2 |
| Solomon Islands | 4.7 |
| Somalia | 8.9 |
| South Africa | 4.8 |
| South Sudan | 8.1 |
| Spain | 2.2 |
| Sri Lanka | 3.7 |
| Sudan | 6.9 |
| Suriname | 3.1 |
| Sweden | 1.5 |
| Switzerland | 1.4 |
| Syria | 7.3 |
| Tajikistan | 4.5 |
| Tanzania | 5.6 |
| Thailand | 4.1 |
| Timor-Leste | 4.5 |
| Togo | 4.6 |
| Tonga | 3.9 |
| Trinidad and Tobago | 2.7 |
| Tunisia | 3.2 |
| Turkey | 5.0 |
| Turkmenistan | 2.6 |
| Tuvalu | 3.1 |
| Uganda | 6.5 |
| Ukraine | 4.7 |
| United Arab Emirates | 1.9 |
| United Kingdom | 1.8 |
| United States of America | 3.4 |
| Uruguay | 1.8 |
| Uzbekistan | 3.1 |
| Vanuatu | 4.1 |
| Venezuela | 4.6 |
| Viet Nam | 3.8 |
| Yemen | 8.1 |
| Zambia | 4.3 |
| Zimbabwe | 5.1 |

INFORM RISK INDEX

Very low
Low
Medium
High
Very high
Not included

KEY

Stable    Decreasing risk    Increasing risk

The depiction and use of boundaries are not warranted to be error free nor do they necessarily imply official endorsement or acceptance by the United Nations and European Union.

PRIORITISING USING RISK LEVEL AND TRENDS

The INFORM Risk Index can be used to group countries based on their current level of risk and the trend over previous years. For example, large increases in countries already with high levels of risk could be used to prioritise them for increased crisis and disaster prevention, preparedness and response.

NEW EPIDEMIC COMPONENT IN THE INFORM RISK INDEX

To make the INFORM Risk Index more comprehensive, the Joint Research Center (JRC) of the European Commission has added an epidemic component (infectious disease outbreaks) to the natural hazard category.¹

Although biological hazards are a significant source of risk that can lead to a humanitarian crisis, they have not previously been included in the INFORM risk model. Increasing awareness of health crises, as well as the emphasis on health in the Sendai Framework for Disaster Risk Reduction 2015-2030, led INFORM partners to make this development.

Starting from the conceptual framework of the Epidemic Risk Index (ERI), developed jointly with the World Health Organisation (WHO), the JRC developed an epidemic-specific component and integrated this into the existing natural hazard category.

For the first time, this enables the risk assessment for all types of epidemics in a single framework, and also provides the contextual information on exposure, vulnerability and coping capacity required for rapid risk assessment for public health. This enhances further the INFORM Risk Index as a multi-dimensional risk assessment tool that is globally applicable to all types of risks.

Analytical framework and results for the new epidemic component of the INFORM Risk Index

ALIGNING INFORM RISK WITH THE SDGS AND SENDAI FRAMEWORK

The Sustainable Development Goals (SDGs) and Sendai Framework Monitor (SFM) provide a unique set of reliable, consistent, and comparable indicators for understanding disaster risk drivers and underlying risk factors. These global monitoring frameworks aim to collect a massive amount of data on hazards, vulnerability and coping capacity, including important new indicators for poorly represented areas. This creates a unique opportunity to enhance the quality and coverage of the indicators used in the INFORM Risk Index.²

Supported by the European Commission’s department for European Civil Protection and Humanitarian Aid Operations (DG ECHO), the JRC has reviewed the new indicators from these processes, to assess if and how these can be used in the INFORM Risk Index.

Seven indicators were considered ready to be included in future releases of the INFORM Risk Index. Many data gaps remain, as the collection processes get up and running, but eventually more relevant indicators will become available. Specifically, SFM indicators will help improve the assessment of coping capacity in the INFORM Risk model.

INFORM can also provide many contributions to the post-2015 global frameworks. The INFORM Risk Index can be used as a tool to assess and monitor the progress towards risk reduction of the Sendai Framework and SDGs. Application of the INFORM Risk methodology at national scale (INFORM Subnational) contributes to Global Targets E (“national and local disaster risk reduction strategies”) and G (“increased availability of and access to disaster risk information”) of the Sendai Framework.

Mapping of Sustainable Development Goal and Sendai Framework indicators against the INFORM Analytical Framework

PROJECTING EFFECTS OF CLIMATE CHANGE ON THE INFORM RISK INDEX

Researchers at the Euro-Mediterranean Center on Climate Change are collaborating with JRC to try to understand how the INFORM Risk Index would be affected by the impacts of climate change.³ The purpose is to look into how climate change-amplified hazards and development pathways may change the performance of countries on the INFORM Risk Index. This is part of a larger project to try to determine how climate change and variability may undermine development, stability and resilience of countries.

The research is focused on adding projections to existing INFORM Risk Index indicators and/or exploring ways of replacing existing indicators with ones that can be projected. The study considers a time horizon to the 2050s and uses high-emissions scenarios and high-challenge shared socioeconomic pathways.

It attempts to model three main effects of climate change on the INFORM Risk Index, of which the first two are presented here:

1. The change in exposure due to amplified climate related hazards – by adding projections of climate-related hazards

2. The change in risk due to amplified hazard and exposure – by adding projections of future development by 2050

3. The change in vulnerability and coping capacity required to reduce risk to an acceptable level - by setting a future level of acceptable risk in the model.

Climate-related hazards in INFORM Risk Index | Projected climate-related hazards
Floods | GAR2015 – annual expected population exposed | Floods | JRC LISFLOOD RCP 8.5 – potential population affected by river floods per year and per country
Storm surge | GAR2015 – annual expected population exposed | Coastal floods | JRC LISCoAsT RCP 8.5 – annual expected population exposed
Droughts | Probability of droughts (ASI from FAO) and population affected (EMDAT) | Droughts | Extreme climate indices related to droughts (SPI, SPEI) based on the CMIP5 simulations for RCP 8.5

Preliminary results of the project show that the extension of the INFORM Risk Index to capture future impacts of climate change can be extremely useful for understanding the challenges and risk trajectories of countries and guiding long term adaptation and assistance priorities. However, a number of challenges remain. For example, some climate change-amplified hazards, such as tropical cyclones, are difficult to model and vulnerability (and its components such as coping/adaptive capacity) is addressed by proxies that are difficult to project.

Work on this project will continue and INFORM partners will consider developing a product based on the final results.

Preliminary results showing the effect of climate change on the Natural Hazard dimension of the INFORM Risk Index by 2050s.

Preliminary results showing the effect of climate change on the INFORM Risk Index by 2050s, therefore including current levels of vulnerability and coping capacity.

The depiction and use of boundaries are not warranted to be error free nor do they necessarily imply official endorsement or acceptance by the United Nations and European Union.

1 Poljansek, K., Marin Ferrer, M., Vernaccini, L. and Messina, L. 2018. 'Incorporating epidemics risk in the INFORM Global Risk Index', EUR 29603 EN. www.doi.org/10.2760/990429

2 Poljansek, K., Marin Ferrer, M., Vernaccini, L., Marzi, S. and Messina, L. 2019. 'Review of the Sendai Framework Monitor and Sustainable Development Goals indicators for their inclusion into INFORM Global Risk Index,' EUR 29753 EN. www.doi.org/10.2760/54937

3 S Marzi, J Mysiak, A Essenfelder. Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici. https://www.cmcc.it/. The research contributes to RECEIPT (Remote Climate Effects and their Impact on European Sustainability, Policy and Trade) and is funded by Grant Agreement ID: 820712.

INFORM SEVERITY

INFORM SEVERITY INDEX

The INFORM Severity Index is an improved way to objectively measure the severity of humanitarian crises globally. It can help us develop a shared understanding of crisis severity and ensure all those affected get the help they need.

Since 2016, INFORM has been developing an improved method for quantitatively measuring crisis severity. The INFORM Severity Index has been released in beta during 2019 and will be launched in 2020. This section of the report provides an overview of the beta version of the Severity Index.

Objectives of the INFORM Severity Index

The objective of the Severity Index is to measure the severity of humanitarian crises globally (i.e. between rather than within crises) and on an ongoing and regular basis. It seeks to communicate the current status of crises in a systematic and comparable way.

A good crisis severity model can:

• Inform a shared and objective understanding of crisis severity

• Contribute to decisions on the allocation of resources in a way that is proportionate with crisis severity

• Justify and advocate for action, especially in the case of forgotten or unrecognised crises, and

• Monitor trends in crisis severity over time.

Measuring severity

The INFORM Severity Index is a composite indicator, which brings together around 30 indicators about the specific crisis or the affected country, which directly or indirectly measure the components of in the analytical framework. The data comes from a variety of reliable sources, including international organisations, research centres, and media analysis.

All the indicators are categorised on a scale of 0-5, where 5 represents a higher contribution to overall severity. This categorisation is based on thresholds developed through assessment of past crises and expert opinion. These scores are then aggregated into components, dimensions and the overall severity index based on the analytical framework, and using a combination of arithmetic and geometric average. Indicators often have a relative and absolute component. This is intended to recognise that the relative size of a crisis in comparison to the size of the country is an important consideration in severity.

BETA TESTING THE INFORM SEVERITY INDEX

During 2019 the beta version of the INFORM Severity Index was made publically available through monthly releases. The purpose of the beta testing phase was to gather feedback that could inform improvements to the data collection and methodology in advance of the final release. The testing tried to understand how the Severity Index captured the following features. (See graphic, right).

In order to answer these questions, we needed to identify a reliable baseline with which to compare the results of the Severity Index. This was challenging, since there is not currently a single public data source that measures the severity of humanitarian crises in a comparable way.

To build a baseline, we asked INFORM partners to share their current methods and tools for measuring crisis severity. These were screened and normalised to produce a baseline that could be used to test the Severity Index. The baseline consisted of 111 crises.

Global landscape of humanitarian crisis

We compared the cumulative total number of crises identified by the Severity Index for the period January to June 2019 and the cumulative total number of crises identified by the baseline. The Severity Index identified 130 crises while the baseline identified 111 crises, with three crises apparently not captured by Index.

Comparison of crises captured by the Severity Index with baseline dataset

Match between Severity Index and baseline in crisis type. Less easily categorised crises are less well matched.

Location and type of crisis

The locations of crises captured by the baseline and the Severity Index were overlaid. There was a very good geographic match. Two of the three crises not captured by the Severity Index could be explained. Papua New Guinea was included in the watch list for the Severity Index but had not met the inclusion criteria and Serbia was included in a regional crisis. These findings will help us adjust the watch list and inclusion criteria.

On crisis type, the Severity Index showed a good match with the baseline for most types of crisis, with more variability for crises identified as refugee/migration, complex, political/economic and international displacement. This represents the difficulty in categorising these types of crisis and the different taxonomies used by INFORM partners.

Severity of crisis

We compared the results of the Severity Index with normalised severity values from the baseline. Although this has limitations – mainly because of the different organisations use different methodologies – it is useful for assessing the Severity Index.

For the 55 crises used, the match between the Severity Index and the baseline was within one point for the majority of crises. Certain types of crises, particularly displacement crises, show more variability. These will be addressed specifically in the next phase of development.

Comparison of the Severity Index with severity scores generated from the baseline for different types of crisis

INFORM SEVERITY INDEX BETA RESULTS: NOVEMBER 2019

The below table shows results of the INFORM Severity Index (beta version) for November 2019. The results show the dimensions of the Index, each rated on a scale of 0-5, where 0 represents the lowest contribution to severity and 5 the highest. The overall level of severity is categorised into five levels, from low to very high. It is very important to note that crises of all levels will include some people at the highest levels of severity. Complete results are available on the INFORM website.

APPENDIX

INFORM RISK INDEX 2020 FULL RESULTS

KEY     Increasing risk     Stable     Decreasing risk

*Reliability Index: more reliable 0    10 less reliable

*Countries with lower Reliability Index scores have risk scores that are based on more reliable data

KEY     Increasing risk     Stable     Decreasing risk

*Reliability Index: more reliable 0    10 less reliable

*Countries with lower Reliability Index scores have risk scores that are based on more reliable data

KEY     Increasing risk     Stable     Decreasing risk

*Reliability Index: more reliable 0    10 less reliable

*Countries with lower Reliability Index scores have risk scores that are based on more reliable data

KEY     Increasing risk     Stable     Decreasing risk

*Reliability Index: more reliable 0    10 less reliable

*Countries with lower Reliability Index scores have risk scores that are based on more reliable data

KEY     Increasing risk     Stable     Decreasing risk

*Reliability Index: more reliable 0    10 less reliable

*Countries with lower Reliability Index scores have risk scores that are based on more reliable data

INFORM RISK INDEX SOURCES

Hazards & Exposure

Earthquake

Physical exposure to extensive earthquake
GEM, JRC

M. Pagani, J. Garcia-Pelaez, R. Gee, K. Johnson, V. Poggi, R. Styron, G. Weatherill, M. Simionato, D. Viganò, L. Danciu, D. Monelli (2018). Global Earthquake Model (GEM) Seismic Hazard Map (version 2018.1 - December 2018), DOI: 10.13117/GEM-GLOBAL-SEISMIC-HAZARD-MAP-2018.1

https://www.globalquakemodel.org/gem

Physical exposure to intensive earthquake
GEM, JRC

M. Pagani, J. Garcia-Pelaez, R. Gee, K. Johnson, V. Poggi, R. Styron, G. Weatherill, M. Simionato, D. Viganò, L. Danciu, D. Monelli (2018). Global Earthquake Model (GEM) Seismic Hazard Map (version 2018.1 - December 2018), DOI: 10.13117/GEM-GLOBAL-SEISMIC-HAZARD-MAP-2018.1

https://www.globalquakemodel.org/gem

Tsunami

Physical exposure to tsunamis
UNDRR, JRC

UNISDR Global Risk Assessment 2015: GVM and IAVCEI, UNEP, CIMNE and associates and INGENIAR, FEWS NET and CIMA Foundation

http://risk.preventionweb.net/capraviewer/download.jsp

Flood

Physical exposure to flood
UNDRR, JRC

UNISDR Global Risk Assessment 2015: GVM and IAVCEI, UNEP, CIMNE and associates and INGENIAR, FEWS NET and CIMA Foundation.

http://risk.preventionweb.net/capraviewer/download.jsp

Tropical Cyclone

Physical exposure to Storm Surges
UNDRR, JRC

UNISDR Global Risk Assessment 2015: GVM and IAVCEI, UNEP, CIMNE and associates and INGENIAR, FEWS NET and CIMA Foundation.

http://risk.preventionweb.net/capraviewer/download.jsp

Physical exposure to extensive tropical cyclone
UNDRR, JRC

UNISDR Global Risk Assessment 2015: GVM and IAVCEI, UNEP, CIMNE and associates and INGENIAR, FEWS NET and CIMA Foundation.

http://risk.preventionweb.net/capraviewer/download.jsp

Physical exposure to intensive tropical cyclone
UNDRR, JRC

UNISDR Global Risk Assessment 2015: GVM and IAVCEI, UNEP, CIMNE and associates and INGENIAR, FEWS NET and CIMA Foundation.

http://risk.preventionweb.net/capraviewer/download.jsp

Drought

Agriculture Stress Index Probability
FAO

http://www.fao.org/giews/earthobservation/asis

People affected by droughts
EMERGENCY EVENTS DATABASE (EM-DAT), CENTRE FOR RESEARCH ON THE EPIDEMIOLOGY OF DISASTERS (CRED)

D. Guha-Sapir, R. Below, Ph. Hoyois - EM-DAT: International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium.

http://www.emdat.be/

Frequency of droughts events
EMERGENCY EVENTS DATABASE (EM-DAT), CENTRE FOR RESEARCH ON THE EPIDEMIOLOGY OF DISASTERS (CRED)

D. Guha-Sapir, R. Below, Ph. Hoyois - EM-DAT: International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium.

http://www.emdat.be/

Epidemic

Population exposed to CCHF

Messina JP, Pigott DM, Golding N, et al. The global distribution of Crimean-Congo hemorrhagic fever. Trans R Soc Trop Med Hyg 2015; 109: 503–13.

Messina JP, Pigott DM, Golding N, et al. The global distribution of Crimean-Congo hemorrhagic fever. Trans R Soc Trop Med Hyg 2015; 109: 503–13.

Population exposed to EVD

Pigott DM, Millear, Anoushka I, Earl L, et al. Updates to the zoonotic niche map of Ebola virus disease in Africa. Elife 2016; 5: e16412.

Pigott DM, Golding N, Mylne A, et al. Mapping the zoonotic niche of Ebola virus disease in Africa. Elife 2014; 3: e04395. Pigott DM, Millear, Anoushka I, Earl L, et al. Updates to the zoonotic niche map of Ebola virus disease in Africa. Elife 2016; 5: e16412.

Pigott DM, Golding N, Mylne A, et al. Mapping the zoonotic niche of Ebola virus disease in Africa. Elife 2014; 3: e04395.

Population exposed to Lassa Fever

Mylne AQN, Pigott DM, Longbottom J, et al. Mapping the zoonotic niche of Lassa fever in Africa. Trans R Soc Trop Med Hyg 2015; 109: 483–92.

Mylne AQN, Pigott DM, Longbottom J, et al. Mapping the zoonotic niche of Lassa fever in Africa. Trans R Soc Trop Med Hyg 2015; 109: 483–92.

Population exposed to MVD

Pigott DM, Golding N, Mylne A, et al. Mapping the zoonotic niche of Marburg virus disease in Africa. Trans R Soc Trop Med Hyg 2015; 109: 366-78

Pigott DM, Golding N, Mylne A, et al. Mapping the zoonotic niche of Marburg virus disease in Africa. Trans R Soc Trop Med Hyg 2015; 109: 366-78

Populations at risk of Plasmodium vivax malaria
MALARIA MAP PROJECT

Gething, P. W., Elyazar, I. R., Moyes, C. L., Smith, D. L., Battle, K. E., Guerra, C. A., Patil, A. P., Tatem, A. J., Howes, R. E., Myers, M. F., George, D. B., Horby, P., Wertheim, H. F., Price, R. N., Müeller, I., Baird, J. K., … Hay, S. I. (2012). A long neglected world malaria map: Plasmodium vivax endemicity in 2010. PLoS neglected tropical diseases, 6(9), e1814.

https://map.ox.ac.uk/explorer/#/

Population exposed to Zika

Messina, Jane; Kraemer, Moritz; Brady, Oliver; Pigott, David; Shearer, Freya; Weiss, Daniel; et al. (2016): Environmental suitability for Zika virus transmission. figshare. Dataset.

https://figshare.com/articles/Environmental_suitability_for_Zika_virus_transmission/2574298

Population at Risk to Aedes

Kraemer et al. eLife 2015;4:e08347. DOI: 10.7554/eLife.08347

Population exposed to Dengue

Messina JP, Brady OJ, Golding N, Kraemer MUG, Wint GRW, Ray SE, Pigott DM, Shearer FM, Johnson K, Earl L, Marczak LB, Shirude S, Davis Weaver N, Gilbert M, Velayudhan R, Jones P, Jaenisch T, Scott TW, Reiner RC and Hay SI (2019). The current and future global distribution and population at risk of dengue. Nature Microbiology

https://www.nature.com/articles/s41564-019-0476-8

Population exposed to West Nile fever

https://www.researchgate.net/publication/308876010_Climate_Change_Influences_on_the_Global_Potential_Distribution_of_the_Mosquito_Culex_quinquefasciatus_Vector_of_West_Nile_Virus_and_Lymphatic_Filariasis

Population density (people per sq. km of land area)
WORLD BANK

http://data.worldbank.org/indicator/EN.POP.DNST

Urban population growth (annual %)
WORLD BANK

https://data.worldbank.org/indicator/SP.URB.GROW

Population living in urban areas (%)
WORLD BANK

http://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS

Household size
UNDESA UNITED NATIONS, DEPARTMENT OF ECONOMIC AND SOCIAL AFFAIRS, POPULATION DIVISION (2018).

Household Size and Composition 2018. (POP/DB/PD/HSCD/2018).

https://population.un.org/Household/index.html

People using at least basic sanitation services (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

People using at least basic drinking water services (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

People practicing open defecation (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://unstats.un.org/sdgs/indicators/database/

Proportion of population with basic handwashing facilities on premises (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

Number of vets
WAHIS, OIE

Copyright © World Organisation for Animal Health (OIE)

https://www.oie.int/wahis_2/public/wahid.php/Countryinformation/Veterinarians

HR capacity score: Food safety
WHO

http://apps.who.int/gho/data/view.main.IHRSPARCTRYALL

Population living in slums (% of urban population)
UN HABITAT

http://data.worldbank.org/indicator/EN.POP.SLUM.UR.ZS

Children under 5
UNDESA

United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019, Online Edition.

https://population.un.org/wpp/Download/Standard/Population/

Conflict Risk

Conflict Barometer - National Power Conflicts
HEIDELBERG INSTITUTE

Heidelberg Institute for International Conflict Research (HIIK) (2019): Conflict Barometer 2018, Heidelberg

http://www.hiik.de/en/konfliktbarometer/index.html

Conflict Barometer – Subnational Conflicts
HEIDELBERG INSTITUTE

Heidelberg Institute for International Conflict Research (HIIK) (2019): Conflict Barometer 2018, Heidelberg

http://www.hiik.de/en/konfliktbarometer/index.html

GCRI Violent Internal Conflict probability
EUROPEAN COMMISSION, JOINT RESEARCH CENTRE (JRC)

http://conflictrisk.jrc.ec.europa.eu/

Vulnerability

Poverty & Development

Human Development Index
UNDP HUMAN DEVELOPMENT REPORT

http://hdr.undp.org/en/composite/HDI

Multidimensional Poverty Index
UNDP HUMAN DEVELOPMENT REPORT

http://hdr.undp.org/en/composite/MPI

Inequality

Gender Inequality Index
UNDP HUMAN DEVELOPMENT REPORT

http://hdr.undp.org/en/composite/GII

Income Gini coefficient – Inequality in income or consumption
WORLD BANK

http://data.worldbank.org/indicator/SI.POV.GINI

Economical Dependency

Public aid per capita
FTS (OCHA); OECD DAC

https://fts.unocha.org/; http://stats.oecd.org/Index.aspx?DataSetCode=TABLE2A

Net ODA received (% of GNI)
WORLD BANK

http://data.worldbank.org/indicator/DT.ODA.ODAT.GN.ZS

Volume of remittances as a proportion of total GDP (%)
WORLD BANK

https://data.worldbank.org/indicator/BX.TRF.PWKR.DT.GD.ZS

Uprooted people

Refugees and asylum-seekers by country of asylum
UNHCR

Global Trends Report and Operational Portal, UNHCR

http://www.unhcr.org; https://data2.unhcr.org/en/situations

Internally displaced persons (IDPs)
INTERNAL DISPLACEMENT MONITORING CENTRE

IDMC Global Report on Internal Displacement 2018 Conflict Dataset

http://www.internal-displacement.org

Returned refugees
UNHCR

http://www.unhcr.org

Other Vulnerable Groups

Adult Prevalence of HIV-AIDS
WHO - GLOBAL HEALTH OBSERVATORY DATA REPOSITORY

http://apps.who.int/ghodata

Number of new HIV infections per 1,000 uninfected population

The Joint United Nations Programme on HIV/AIDS (UNAIDS)

https://unstats.un.org/sdgs/indicators/database/

Malaria incidence per 1,000 population at risk
GLOBAL MALARIA PROGRAMME AT WORLD HEALTH ORGANIZATION (WHO)

https://unstats.un.org/sdgs/indicators/database/

Incidence of Tuberculosis
WHO GLOBAL HEALTH OBSERVATORY DATA REPOSITORY

http://apps.who.int/ghodata

Number of people requiring interventions against neglected tropical diseases
NATIONAL NTD PROGRAMMES WITHIN MINISTRIES OF HEALTH, COMPILED BY WHO

https://unstats.un.org/sdgs/indicators/database/

Child Mortality
UN INTER-AGENCY GROUP FOR CHILD MORTALITY ESTIMATION (UNICEF, WHO, WORLD BANK, UN DESA POPULATION DIVISION)

www.childmortality.org

Children Under Weight
WORLD HEALTH ORGANIZATION, GLOBAL DATABASE ON CHILD GROWTH AND MALNUTRITION.

http://www.who.int/nutgrowthdb/en

Population affected by natural disasters in the last 3 years
EMERGENCY EVENTS DATABASE (EM-DAT), CENTRE FOR RESEARCH ON THE EPIDEMIOLOGY OF DISASTERS (CRED)

EM-DAT: The Emergency Events Database - Université catholique de Louvain (UCL) - CRED, D. Guha-Sapir Brussels, Belgium. www.emdat.be,

D. Guha-Sapir, R. Below, Ph. Hoyois - EM-DAT: International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium. http://www.emdat.be/

Average dietary supply adequacy
FAO

http://www.fao.org/economic/ess/ess-fs/ess-fadata/en/

Prevalence of undernourishment
FAO

http://www.fao.org/economic/ess/ess-fs/ess-fadata/en/

Lack of Coping Capacity

Governance

Government effectiveness
WORLDWIDE GOVERNANCE INDICATORS WORLD BANK

http://info.worldbank.org/governance/wgi/

Corruption Perception Index
TRASPARENCY INTERNATIONAL

http://cpi.transparency.org/

DRR implementation

Hyogo Framework for Action
UNISDR

http://preventionweb.net/applications/hfa/qbnhfa/

Communication

Adult literacy rate
UNESCO

http://stats.uis.unesco.org/unesco

Access to electricity
WORLD BANK

http://data.worldbank.org/indicator/EG.ELC.ACCS.ZS

Internet Users
INTERNATIONAL TELECOMMUNICATION UNION, REDISTRIBUTED BY WORLD BANK

International Telecommunication Union, World Telecommunication/ICT Development Report and database.

http://data.worldbank.org/indicator/IT.NET.USER.P2

Mobile celluar subscriptions
INTERNATIONAL TELECOMMUNICATION UNION, REDISTRIBUTED BY WORLD BANK

International Telecommunication Union, World Telecommunication/ICT Development Report and database.

http://data.worldbank.org/indicator/IT.CEL.SETS.P2

Physical Connectivity

Improved sanitation facilities
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

Improved water source
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

Road density
OPENSTREETMAP OSM

https://www.openstreetmap.org

People using at least basic sanitation services (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

People using at least basic drinking water services (% of population)
WHO/UNICEF JOINT MONITORING PROGRAMME (JMP) FOR WATER SUPPLY AND SANITATION

https://washdata.org/

Access to health care

Current health expenditure per capita
WHO GLOBAL HEALTH OBSERVATORY DATA REPOSITORY

http://apps.who.int/nha/database

Coverage of DTP3 vaccine
WHO, UNICEF

https://unstats.un.org/sdgs/indicators/database/

Coverage of measles-containing vaccine
WHO, UNICEF

https://unstats.un.org/sdgs/indicators/database/

Coverage of pneumococcal conjugate vaccine
WHO, UNICEF

https://unstats.un.org/sdgs/indicators/database/

Physicians density
WHO

https://unstats.un.org/sdgs/indicators/database/

Maternal Mortality Ratio
WHO, UNICEF, UNFPA, WORLD BANK GROUP AND THE UNITED NATIONS POPULATION DIVISION

The Maternal Mortality Estimation Group (composed of WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division) prepares estimates and trends of this indicator.

http://www.who.int/reproductivehealth/publications/monitoring/maternal-mortality-2015/en/

Common

GHSL Population Grid
EUROPEAN COMMISSION, JOINT RESEARCH CENTRE (JRC)

Schiavina, Marcello; Freire, Sergio; MacManus, Kytt (2019): GHS population grid multitemporal (1975, 1990, 2000, 2015) R2019A. European Commission, Joint Research Centre (JRC) DOI: 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218 PID:

http://data.europa.eu/89h/0c6b9751-a71f-4062-830b-43c9f432370f

https://data.jrc.ec.europa.eu/dataset/0c6b9751-a71f-4062-830b-43c9f432370f

Total population
UNDESA

United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019, Online Edition. Rev. 1.

https://population.un.org/wpp/Download/Standard/Population/

GDP per capita
WORLD BANK

http://data.worldbank.org/indicator/NY.GDP.PCAP.CD

INFORM is a collaboration of the Inter-Agency Standing Committee and the European Commission. The Joint Research Centre of the European Commission is the scientific and technical lead of INFORM. This report is based on the data available at https://drmkc.jrc.ec.europa.eu/inform-index.

This report is produced by the United Nations Office for the Coordination of Humanitarian Affairs on behalf of all INFORM Partners.

INFORM Steering Group

INFORM Partners

For more information, go to https://drmkc.jrc.ec.europa.eu/inform-index