News COMET-GEM Seismic Hazard Workshop and OpenQuake Training By: Sep 15, 2022 Share Facebook LinkedIn From June 29th to July 1st, the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) co-hosted a workshop with GEM at the Earth Sciences Department, University of Oxford, UK. The event brought together 25 participants from 12 institutes with diverse research interests, including: active tectonics, paleoseismology, precariously balanced rocks, strain mapping, ground motion modelling, physics-based fault modelling, observational seismology, induced seismicity, and volcanology. The workshop theme was to find the intersection between seismic hazard analysis and the research topics of interest to COMET scientists, with the goals of learning how their research results are currently used by seismic hazard modellers, and imagining ways to increase their utility. The workshop aimed to achieve these goals with a balance of PSHA lectures, OpenQuake Engine training, interactive exercises, discussion, and participant presentations. On the first day, Kendra Johnson, GEM Hazard Scientist, gave an introduction to probabilistic seismic hazard analysis (PSHA) and walked the participants through the hazard component of the OpenQuake Engine. On the second day, Richard Styron, GEM Active Faults Specialist, discussed bridging the gaps between research and seismic hazard models, delving into the issues and challenges in transitioning from being a hazard researcher to a hazard modeller. Marco Pagani, GEM Hazard Coordinator joined the discussion and provided his insights on the topic. On the third day, the participants explored how the seismic source parameterization and assumptions made in the first steps of PSHA impact hazard calculation results. The workshop concluded with a lecture by Manuela Villani, GEM Senior Hazard Scientist, on incorporating epistemic uncertainties into PSHA, and brief research presentations by a few participants. The workshop was organised as part of a collaborative project between the UK Natural Environment Research Council (NERC) - COMET and GEM with funding support from NERC. The project is working to combine field data, InSAR, global navigation satellite system (GNSS), remote-sensing and block modelling to develop new seismic hazard models. NERC is the leading funder of UK environmental science and a GEM public sponsor. No images found. GALLERY 1/2 VIDEO RELATED CONTENTS

News GEM shares approach in earthquake hazard and risk assessment at the 2017 Global Platform For Disaster Risk Reduction By: Jul 2, 2018 Share Facebook LinkedIn John Rees of the British Geological Survey and GEM Governing Board member presented GEM at the 2017 Global Platform for Disaster Risk Reduction held in Cancun, Mexico from May 22-26. GEM’s work on earthquake hazard and risk assessment was presented during the Sendai Framework Priority 1: Understanding Disaster Risk session. The participation was aimed to contribute to the discussions on practical examples regarding the use of open data platforms that present geo-referenced earthquake risk information and exposure data in open source and interoperable formats. In particular, GEM shared the cost effectiveness and the multiple sustainable development benefits of such open risk data platforms for the public and private sector. GEM reaffirmed its commitment to continue developing tools and products, promoting open access and open source risk assessment applications, and advancing earthquake science to help achieve disaster risk reduction globally. The Fifth Session of the Global Platform for Disaster Risk Reduction took place from 24 to 26 May 2017 in Cancun Mexico. With the Sustainable Development Goals (the SDGs) as backdrop, the program and deliberations of the Global Platform reflected the priorities of the Sendai Framework for Disaster Risk Reduction 2015-2030. The 2017 Global Platform marks the first event after the adoption of the Sendai Framework in 2015. No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News International Conference for the Decade Memory of the Wenchuan Earthquake By: Jul 12, 2018 Share Facebook LinkedIn The 4th International Conference on Continental Earthquakes organized by the China Earthquake Administration (CEA) was held from May 12-14, 2018 in Chengdu, Sichuan, China to commemorate the 10th anniversary of the Wenchuan earthquake. “It has been 10 years since the great earthquake of Wenchuan, Sichuan, southwest China. The impact of that devastating event on either natural science or social sustainability was so important that a decade review will be of no doubt worth for further development,” said Prof. Guoguang Zheng, conference convener and Director of China Earthquake Administration. In line with this, GEM’s Marco Pagani with CEA’s Prof. Mengtan Gao co-organized a session on the activities promoted by Global Earthquake Model. In this session, Anirudh Rao from the GEM Risk Team presented how the OpenQuake engine could be used to assess earthquake risk. Examples of annual average losses, exposure and vulnerability models were presented to emphasize the scientific features of the engine. Anirudh also emphasized the importance of open tools and open data being promoted by GEM. This conference had also been a venue to report the progress of GEM-CEA collaboration to implement China’s national earthquake hazard model on OpenQuake. The collaboration, which started in 2017 hopes to update China’s hazard model for better understanding of future earthquakes in the country. The GEM-CEA technical partnership aims to further fine tune the model for mitigation purposes. In one of the presentations, Professor Tso-Chien Pan from the Institute of Catastrophe Risk Management-NTU Singapore showed a case-study using OpenQuake to investigate the effects of high-resolution location-based exposure data on seismic risk estimates of urbanized regions in Southeast Asia. About the Wenchuan earthquake Sichuan earthquake of 2008, also called Wenchuan earthquake or Great Wenchuan Earthquake, Chinese Wenchuan dizhen or Wenchuan Da Dizhen, massive and enormously devastating earthquake that occurred in the mountainous central region of Sichuan province in southwestern China on May 12, 2008. The epicentre of the magnitude-7.9 quake (measured as magnitude 8.0 by the Chinese) was located near the city of Dujiangyan, about 50 miles (80 km) west-northwest of Chengdu, the provincial capital, at a depth of 11.8 miles (19 km) below the surface. The May 2008 quake flattened some four-fifths of the structures in the affected area. Whole villages and towns in the mountains were destroyed, and many schools collapsed. Almost 90,000 people were counted as dead or missing and presumed dead in the final official Chinese government assessment; the officially reported total killed included more than 5,300 children, the bulk of them students attending classes.(source: https://www.britannica.com/event/Sichuan-earthquake-of-2008) No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Deep Learning Speeds Up Building Classification for Seismic Risk Assessment By: Oct 6, 2025 Aug 1, 2025 Share Facebook LinkedIn Time-consuming building surveys may soon be replaced by automation, as shown in research led by Daniel Gomez, GEM Collaborator/ Exposure Analyst, on deep learning for exposure assessment. The study introduces an automated method for identifying building typologies, reducing the time and cost of creating building inventories for seismic risk assessment. Automating a Manual Process Traditionally, compiling detailed building stock data for seismic exposure assessments has relied on in-person surveys, a process that is both expensive and time-consuming. Virtual inspections through online imagery have provided some relief but continue to require considerable manual input. The paper, Automating building typology identification for seismic risk assessment using deep learning, recognised as Editor’s Choice in the August 2025 issue of Earthquake Spectra, the journal of the Earthquake Engineering Research Institute (EERI), proposes a novel solution by applying computer vision and deep learning techniques to images from Google Street View. The methodology extracts and classifies building features such as number of storeys, structural system, and construction period (pre-code or code). Methodology and Accuracy The approach employs a convolutional neural network model enhanced with pre-processing techniques. An object detector isolates building façades while a keypoint model and homography transformation correct perspective distortions, allowing the system to perform reliably even with limited data sets. This process enables more precise classification than previous approaches, which often grouped buildings into broad categories. The study achieved an accuracy of 88% for identifying structural systems, 78% for the number of storeys, and 69% for construction period determination. These outputs were integrated into a probabilistic distribution model of building taxonomy, which can then be used to estimate seismic vulnerability. Implications for Risk Reduction By automating the creation of building inventories, the study addresses one of the biggest challenges in regional seismic exposure modelling – the need for reliable, detailed data at scale. The results pave the way for faster and more cost-effective seismic risk modelling in rapidly urbanising areas where large-scale in-person inspections are not feasible. The research demonstrates how advances in artificial intelligence can strengthen the field of disaster risk reduction by providing scalable, transparent, and globally applicable tools. Its open and adaptable methodology supports broader efforts to improve seismic exposure and risk models worldwide. Link to the study: https://journals.sagepub.com/doi/full/10.1177/87552930251327435 No images found. GALLERY dgomez building class ai study.jpeg dgomez building class ai study.jpeg 1/1 VIDEO RELATED CONTENTS

News GEM releases the South Africa Model to complete the Africa Earthquake Mosaic of models By: Dec 18, 2019 Share Facebook LinkedIn South Africa hazard map The South Africa Model developed by the Council for Geoscience, Pretoria South Africa and GEM is now available on the GEM website. The release includes the OpenQuake engine input files, documentation and a link to the paper describing the national model published by the Journal of African Earth Sciences. The model, developed by the Council for Geoscience, South Africa and the Indian Institute of Technology (IIT) with support from GEM, used 22 area sources in the probabilistic seismic hazard assessment calculation using the OpenQuake software. The peak ground acceleration (PGA) map shows high hazard in the gold mining regions of South Africa. Hazard maps show results slightly different in spatial distribution from previous results obtained for South Africa. The model is part of the Africa Earthquake Hazard and Risk model, which underpins the African portion of GEM’s global maps released in December 2018. The Africa Earthquake Model was developed as a mosaic of regional models for Sub-Saharan Africa, North Africa, West Africa and South Africa, involving and building the capacity of local experts where possible. The SubSaharan model was developed as part of the Sub-Sahara Hazard and Risk Assessment (SSAHARA) project funded by USAID, covering Eastern SubSaharan Africa. This is the first seismic hazard map released after many years since the previous national seismic hazard for South Africa. The availability of more reliable seismicity and geological data has made it possible to update the old maps using probabilistic seismic hazard analysis methodologies that take into consideration all available data. The results can be used by risk managers, urban planners, emergency responders and humanitarian agencies for input to a wide range of disaster risk reduction activities including monitoring of the Sendai Framework indicators. The model and paper can be downloaded . No images found. GALLERY 1/0 Gallery VIDEO RELATED CONTENTS

Publications Guidelines for component-based analytical vulnerability assessment of buildings and nonstructural elements Share Facebook LinkedIn Download 2014 | Report A procedure is offered forthe analytical derivation ofthe seismic vulnerability of building classes, that is, probabilistic relationships between shaking and repair cost as a fraction of replacement cost new for a categoryofbuildings.Itsimulatesstructural response,damage,and repaircost for thestructuralandnonstructuralcomponents thatcontributemost toconstructioncost,and thenscalesup results toaccount for the components thatwere not simulated.It does so fora carefully selected sample of building specimens called index buildings whose designs span the domain of up to three features that are believed to most strongly influence seismic vulnerability within the building class. One uses moment matching to combine results for theindexbuildings toestimatebehaviourandvariabilityof thebuildingclass.Onecansimulate non-structuralvulnerabilityalonebyignoringdamageandrepaircostforstructuralcomponents.Theworkis written for a structural engineer with a master’s degree, skilled in structural analysis, but not necessarily experiencedinlossmodelling.

News GEM and 100RC partnership to boost earthquake resilience By: Mar 1, 2019 Share Facebook LinkedIn Cities at risk to earthquakes are expected to directly benefit from the partnership between GEM and 100 Resilient Cities – Pioneered by The Rockefeller Foundation (100RC), which is dedicated to helping cities around the world become more resilient to the physical, social and economic shocks and stresses of the 21st century. (source: http://www.100resilientcities.org) The agreement signed in August provides an opportunity for 100RC member cities to understand and address their earthquake risk by working with GEM to incorporate earthquake risk reduction in their resilience strategies and capturing lessons learned to inform other cities. The Global Earthquake Model (GEM) will partner with motivated cities to build their capacity for long-term risk mitigation planning using GEM’s open source OpenQuake software and GEM’s other tools and services. “Our partnership with the 100RC is a great opportunity to share GEM’s open tools, data and technical expertise at the city level. Working together with 100RC is an important step toward achieving GEM’s vision of a world that is resilient to earthquakes.” John Schneider, GEM Secretary General. Cities will receive an ‘Earthquake Risk Thumbnail’, a report providing OpenQuake maps of the city’s or region’s seismic risk comprised of the hazard, and the physical, social and economic risk to the exposed assets and population. 'Thumbnail’ report will propose options for deeper engagement which may include collaboration on data collection, raining local city staff or partners to use GEM’s products and tools, and stakeholder engagement workshops including the Resilience Performance Scorecard (RPS) exercise. Rebecca Laberenne, Associate Director on the Solution Development and Innovation Team at 100RC, underscores the value of partnering with GEM saying, "We are delighted to have GEM Foundation as a 100RC Platform Partner to provide much needed information and technical advice to cities whose buildings and infrastructure are at risk to earthquakes. GEM's approach to collaboration and technical assistance will be very welcomed by cities to gain an understanding of their risks, as well as to assist in identifying appropriate and cost-effective mitigation and risk reduction measures as part of their resilience strategies." No images found. GALLERY 1/0 VIDEO RELATED CONTENTS

News Estimating fault slip rates in the Cascadia region of North America using joint geologic-geodetic block modeling By: Jun 3, 2021 Share Facebook LinkedIn Richard Styron, GEM hazard team, was recently invited to present at the Seismological Society of America (SSA) Conference held in April on the ongoing collaborative research between GEM, Natural Resources Canada, and other scientists to study earthquake faults in the northwestern US and western Canada. The authors of the conference paper were Richard Styron, Tiegan Hobbs (Natural Resources Canada), Zach Lifton (Idaho Geological Survey), Nick Harrichhausen (University of California, Santa Barbara) and Murray Journeay (Natural Resources Canada). The project uses a software program developed by Richard called Oiler , that estimates the long-term movement of faults and corresponding production of earthquakes. Oiler uses geodetic (mostly global positioning system or GPS) measurements of the movement of tectonic plates, as well as geologic data such as geologic mapping and paleoseismic studies, to solve for the slip rate (and therefore earthquake production rate) of all faults within a fault network. For this project, the researchers used existing fault data augmented with some new mapping in the US, and completely new mapping of possibly-active faulting in Canada, to build the fault network. Over the next year or two, the researchers hope to be able to incorporate all of this data into a comprehensive database of seismically active faults in order to evaluate the earthquake potential of previously-unstudied faults in western Canada and the northwestern US. Watch Richard’s SSA presentation here. [ VIDEO LINK ] About #SSA2021 Held on 19–23 April 2021, the virtual SSA Annual Meeting featured more than 750 technical presentations, including sessions co-sponsored by the Latin American and Caribbean Seismological Commission and the Seismological Society of China. For more about SSA, visit https://www.seismosoc.org/ . No images found. GALLERY 1/0 Gallery VIDEO RELATED CONTENTS

Global Earthquake Maps Global Economic Vulnerability Map VIEWER PDF PNG CONTRIBUTORS DOCUMENTATION References Briguglio, L., Cordina, G., Farrugia, N. & Vella, S. 2009. Economic Vulnerability and Resilience: Concepts and Measurements. Oxford Development Studies, 37:3, 229-247, DOI: 10.1080/13600810903089893. Cutter, S. L., J. T. Mitchell, and M. S. Scott. 2000. Revealing the Vulnerability of People and Place: A Case Study of Georgetown County, South Carolina. Annals of the Association of American Geographers 90(4): 713-737. TECHNICAL DESCRIPTION The Global Economic Vulnerability Map presents a composite index that was designed primarily to measure the potential for economic losses from earthquakes due to a country’s macroeconomic exposure. This index is also an appraisal of the ability of countries to respond to shocks to their economic systems. Relevant indicators include the density of exposed economic assets such as commercial and industrial infrastructure. Metrics used to measure the ability of a country to withstand shocks to its economic system include reliance on imports/exports, government debt, and purchasing power. The economic vulnerability category also considers the economic vitality of countries since the economic vitality of a country can be directly related to the vulnerability and resilience of its population. The latter includes measurements of single-sector economic dependence, income inequality, and employment status. Criteria for indicator selection To choose indicators contextually exclusive for use in each map, the starting point was an exhaustive review of the literature on earthquake social vulnerability and resilience. For a variable to be considered appropriate and selected, three equally important criteria were met: - variables were justified based on the literature regarding its relevance to one or more of the indices. - variables needed to be of consistent quality and freely available from sources such as the United Nations and the World Bank; and - variables must be scalable or available at various levels of geography to promote sub-country level analyses. This procedure resulted in a ‘wish list’ of approximately 300 variables of which 78 were available and fit for use based on the three criteria. Process for indicator selection For variables to be allocated to an index, a two-tiered validation procedure was utilized. For the first tier, variables were assigned to each of the respective indices based on how each variable was cited within the literature, i.e., as being part of an index of social vulnerability, economic vulnerability, or recovery/resilience. For the second tier, machine learning and a multivariate ordinal logistic regression modelling procedure was used for external validation. Here, focus was placed on the statistical association between the socio-economic vulnerability indicators and the adverse impacts from historical earthquakes on a country-by country-basis. The Global Significant Earthquake Database provided the external validation metrics that were used as dependent variables in the statistical analysis. To include both severe and moderate earthquakes within the dependent variables, adverse impact data was collected from damaging earthquake events that conformed to at least one of five criteria: 1) caused deaths, 2) caused moderate damage (approximately $1 million USD or more), 3) had a magnitude 7.5 or greater 4) had a Modified Mercalli Intensity (MMI) X or greater, or 5) generated a tsunami. This database was chosen because it considers low magnitude earthquakes that were damaging (e.g., MW >=2.5 & MW<=5.5) and contains socio-economic data such as the total number of fatalities, injuries, houses damaged or destroyed, and dollar loss estimates in $USD. Countries not demonstrating at least a minimal earthquake risk, i.e., seismicity <0.05 PGA (Pagani et al. 2018) and <$10,000 USD in predicted average annual losses (Silva et al. 2018) were eliminated from the analyses so as not to include countries with minimal to no earthquake risk. A total study area consists of 136 countries. The Global Earthquake Model (GEM) Foundation The Global Socio-Economic Vulnerability Maps 2020 is a product of the GEM Foundation’s collaborative work with the Department of Geography at the University of Connecticut, USA. GEM is a non-profit foundation in Pavia, Italy funded through a public-private partnership with a vision to create a world that is resilient to earthquakes. Formed in 2009 through the initiative of the Organization for Economic Co-operation and Development (OECD) Global Science Forum in 2006, GEM participants represent national research and disaster management institutions; private sector companies mainly in insurance, risk financing and engineering; and academic and international organizations. GEM’s OpenQuake Platform website (platform.openquake.org) provides access to all of the data, models, tools and software behind the maps. GEM’s open-source OpenQuake engine enables probabilistic hazard and risk calculations worldwide and at all scales, from global down to regional, national, local, and site-specific applications in a single software package. GEM supports the Sendai Framework for Disaster Risk Reduction (SFDRR) goals by contributing openly accessible products for hazard and risk assessment and capacity development through risk reduction projects. GEM also serves as a baseline or exemplar for the development of a broader multi-hazard framework for risk assessment in support of a holistic and comprehensive approach to disaster risk reduction. Technical details on the development and compilation of the socio-economic vulnerability maps, underlying models and the list of contributors can be found at https://www.globalquakemodel.org/svrmaps/Economic-Vulnerability-Index-Technical-Description. How to use and cite this work Please cite this work as: C Burton, M. Toquica (September 2020). Global Earthquake Model (GEM) Social Vulnerability Map (version 2020.1) DOI: 10.13117/GEM-ECONOMIC-VULNERABILITY-MAP. This work is licensed under the terms of the Creative Commons Attribution - Non Commercial-Share Alike 4.0 International License (CC BY-NC-SA). Acknowledgements This map is the result of a collaborative effort and extensively relies on the enthusiasm and commitment of various organisations to openly share and collaborate. The creation of this map would not have been possible without the support provided by several public and private organisations during GEM’s second and third working programmes, 2014-2018 and 2019-2021 respectively. None of this would have been possible without the extensive support of all GEM Secretariat staff. These key contributions are profoundly acknowledged. A complete list of the contributors can be found at: www. globalquakemodel.org/global-social-vulnerability. Legal statements This map is an informational product created by the GEM Foundation for public dissemination purposes. The information included in this map must not be used for the design of seismic socio-economic policies or to support any important decisions involving human life, capital and movable and immovable properties. The values of social vulnerability and risk values used in this map do not constitute an alternative nor do they replace any national government policy or actions defined in national codes or earthquake risk estimates derived nationally. Readers seeking this information should contact the national authorities tasked with socio economic and risk assessment. The socio-economic vulnerability maps are based on the results of an integration process that is solely the responsibility of the GEM Foundation. Contact GEM (Global Earthquake Model) Foundation Via Ferrata, 1 - 27100, Pavia, Italy info@globalquakemodel.org . More information available at: www. globalquakemodel.org/global-social-vulnerability MAJOR SPONSORS Verisk ARUP GEOSCIENCE AUSTRALIA CSSC NRCan EAFIT ETH ZURICH EUCENTRE FM GLOBAL GFZ GIROJ GNS SCIENCE HANNOVER RE MUNICH RE NTU ICRM NEPHILA NERC NIED NSET OYO PARTNER RE DPC SGC SWISS SER SWISS RE FOUNDATION SURAMERICANA TEM RCN USGS USAID WTW ZURICH INSURANCE

OpenQuake engine input model to perform hazard calculations for Australia Project Name Products Australia Hazard OpenQuake engine input model to perform hazard calculations for Australia Share Facebook LinkedIn Description The Global Hazard Mosaic coverage of the Australian continent uses the 2018 national model developed by Geoscience Australia, with input from the wider seismology community in Australia. More recently, GA have released a 2023 model. Both models have been implemented in the OpenQuake (OQ) engine format. How to cite this work Allen, T.I., Griffin, J.D., Clark, D.J., Cummins, P.R., Ghasemi, H., Ebrahimi, R., et al. (2023). The 2023 National Seismic Hazard Assessment for Australia: model overview. Geoscience Australia Record 2023/53. Canberra. https://dx.doi.org/10.26186/148969 Available Versions Two open versions (v2023.0.0 and v2018) are available for direct download under a CC BY 4.0 license. Users interested in any of the versions can click one of the "Open Version Download" buttons on the right panel to access the information. License information Both open versions are available under a Creative Commons CC BY 4.0 license, which requires: *Attribution (you must give appropriate credit, provide a link to the license, and indicate if changes were made) Any deviation from these terms incur in license infringement. Share License CC BY 4.0 Available resources Open Version 2018 Download Documentation version 2018 Open Version 2023 Download Documentation version 2023 License Request Facebook LinkedIn text Map View Search Popup title Close Country/Region Available Resources Afghanistan Exposure Africa Exposure Alaska Exposure Albania Exposure Algeria Exposure American Samoa Exposure Andorra Exposure Angola Exposure Anguilla Exposure Antigua and Barbuda Exposure Arabia Exposure Argentina Exposure Armenia Exposure Aruba Exposure Australia Exposure Austria Exposure Azerbaijan Exposure Bahamas Exposure Bahrain Exposure Bangladesh Exposure Barbados Exposure Belarus Exposure Belgium Exposure Belize Exposure Benin Exposure Bhutan Exposure Bolivia Exposure Bosnia and Herzegovina Exposure Botswana Exposure Brazil Exposure British Virgin Islands Exposure Brunei Exposure Bulgaria Exposure Burkina Faso Exposure Burundi Exposure Cambodia Exposure Cameroon Exposure Canada Exposure Cape Verde Exposure Caribbean 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Hong Kong Exposure Hungary Exposure Iceland Exposure India Exposure Indonesia Exposure Iran Exposure Iraq Exposure Ireland Exposure Isle of Man Exposure Israel Exposure Italy Exposure Ivory Coast Exposure Jamaica Exposure Japan Exposure Jordan Exposure Kazakhstan Exposure Kenya Exposure Kiribati Exposure Kosovo Exposure Kuwait Exposure Kyrgyzstan Exposure Laos Exposure Latvia Exposure Lebanon Exposure Lesotho Exposure Liberia Exposure Libya Exposure Liechtenstein Exposure Lithuania Exposure Luxembourg Exposure Macao Exposure Madagascar Exposure Malawi Exposure Malaysia Exposure Mali Exposure Malta Exposure Marshall Islands Exposure Martinique Exposure Mauritania Exposure Mauritius Exposure Mexico Exposure Micronesia Exposure Middle East Exposure Moldova Exposure Monaco Exposure Mongolia Exposure Montenegro Exposure Montserrat Exposure Morocco Exposure Mozambique Exposure Myanmar Exposure Namibia Exposure Nauru Exposure Nepal Exposure Netherlands Exposure New Caledonia Exposure New Zealand Exposure Nicaragua Exposure Niger Exposure Nigeria Exposure Niue Exposure North Africa Exposure North America Exposure North Asia Exposure North Korea Exposure North Macedonia Exposure North and South Korea Exposure Northeast Asia Exposure Northern Mariana Islands Exposure Northwest Asia Exposure Norway Exposure Oceania Exposure Oman Exposure Pacific Islands Exposure Pakistan Exposure Palau Exposure Palestine Exposure Panama Exposure Papua New Guinea Exposure Paraguay Exposure Peru Exposure Philippines Exposure Poland Exposure Portugal Exposure Puerto Rico Exposure Qatar Exposure Romania Exposure Russia Exposure Rwanda Exposure Saint Kitts and Nevis Exposure Saint Lucia Exposure Saint Vincent and the Grenadines Exposure Samoa Exposure Sao Tome and Principe Exposure Saudi Arabia Exposure Senegal Exposure Serbia Exposure Seychelles Exposure Sierra Leone Exposure Singapore Exposure Slovakia Exposure Slovenia Exposure Solomon Islands Exposure Somalia Exposure South Africa Exposure South America Exposure South Asia Exposure South Korea Exposure Country/Region Available Resources Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Albania Vulnerability Algeria Vulnerability American Samoa Vulnerability Andorra Vulnerability Angola Vulnerability Anguilla Vulnerability Antigua and Barbuda Vulnerability Arabia Vulnerability Argentina Vulnerability Armenia Vulnerability Aruba Vulnerability Australia Vulnerability Austria Vulnerability Azerbaijan Vulnerability Bahamas Vulnerability Bahrain Vulnerability Bangladesh Vulnerability Barbados Vulnerability Belarus Vulnerability Belgium Vulnerability Belize Vulnerability Benin Vulnerability Bhutan Vulnerability Bolivia Vulnerability Bosnia and Herzegovina Vulnerability Botswana Vulnerability Brazil Vulnerability British Virgin Islands Vulnerability Brunei Vulnerability Bulgaria Vulnerability Burkina Faso Vulnerability Burundi Vulnerability Cambodia Vulnerability Cameroon Vulnerability Canada Vulnerability Cape Verde Vulnerability Caribbean Central America Vulnerability Cayman Islands Vulnerability Central African Republic Vulnerability Central Asia Vulnerability Chad Vulnerability Chile Vulnerability China Vulnerability Colombia Vulnerability Comoros Vulnerability Congo Vulnerability Conterminous US Vulnerability Cook Islands Vulnerability Costa Rica Vulnerability Croatia Vulnerability Cuba Vulnerability Cyprus Vulnerability Czechia Vulnerability Democratic Republic of the Congo Vulnerability Denmark Vulnerability Djibouti Vulnerability Dominica Vulnerability Dominican Republic Vulnerability East Asia Vulnerability Ecuador Vulnerability Egypt Vulnerability El Salvador Vulnerability Equatorial Guinea Vulnerability Eritrea Vulnerability Estonia Vulnerability Eswatini Vulnerability Ethiopia Vulnerability Europe Vulnerability Fiji Vulnerability Finland Vulnerability France Vulnerability French Guiana Vulnerability Gabon Vulnerability Gambia Vulnerability Georgia Vulnerability Germany Vulnerability Ghana Vulnerability Gibraltar Vulnerability Greece Vulnerability Grenada Vulnerability Guadeloupe Vulnerability Guam Vulnerability Guatemala Vulnerability Guinea Vulnerability Guinea Bissau Vulnerability Guyana Vulnerability Haiti Vulnerability Hawaii Vulnerability Honduras Vulnerability Hong Kong Vulnerability Hungary Vulnerability Iceland Vulnerability India Vulnerability Indonesia Vulnerability Iran Vulnerability Iraq Vulnerability Ireland Vulnerability Isle of Man Vulnerability Israel Vulnerability Italy Vulnerability Ivory Coast Vulnerability Jamaica Vulnerability Japan Vulnerability Jordan Vulnerability Kazakhstan Vulnerability Kenya Vulnerability Kiribati Vulnerability Kosovo Vulnerability Kuwait Vulnerability Kyrgyzstan Vulnerability Laos Vulnerability Latvia Vulnerability Lebanon Vulnerability Lesotho Vulnerability Liberia Vulnerability Libya Vulnerability Liechtenstein Vulnerability Lithuania Vulnerability Luxembourg Vulnerability Macao Vulnerability Madagascar Vulnerability Malawi Vulnerability Malaysia Vulnerability Mali Vulnerability Malta Vulnerability Marshall Islands Vulnerability Martinique Vulnerability Mauritania Vulnerability Mauritius Vulnerability Mexico Vulnerability Micronesia Vulnerability Middle East Vulnerability Moldova Vulnerability Monaco Vulnerability Mongolia Vulnerability Montenegro Vulnerability Montserrat Vulnerability Morocco Vulnerability Mozambique Vulnerability Myanmar Vulnerability Namibia Vulnerability Nauru Vulnerability Nepal Vulnerability Netherlands Vulnerability New Caledonia Vulnerability New Zealand Vulnerability Nicaragua Vulnerability Niger Vulnerability Nigeria Vulnerability Niue Vulnerability North Africa Vulnerability North America Vulnerability North Asia Vulnerability North Korea Vulnerability North Macedonia Vulnerability North and South Korea Vulnerability Northeast Asia Vulnerability Northern Mariana Islands Vulnerability Northwest Asia Vulnerability Norway Vulnerability Oceania Vulnerability Oman Vulnerability Pacific Islands Vulnerability Pakistan Vulnerability Palau Vulnerability Palestine Vulnerability Panama Vulnerability Papua New Guinea Vulnerability Paraguay Vulnerability Peru Vulnerability Philippines Vulnerability Poland Vulnerability Portugal Vulnerability Puerto Rico Vulnerability Qatar Vulnerability Romania Vulnerability Russia Vulnerability Rwanda Vulnerability Saint Kitts and Nevis Vulnerability Saint Lucia Vulnerability Saint Vincent and the Grenadines Vulnerability Samoa Vulnerability Sao Tome and Principe Vulnerability Saudi Arabia Vulnerability Senegal Vulnerability Serbia Vulnerability Seychelles Vulnerability Sierra Leone Vulnerability Singapore Vulnerability Slovakia Vulnerability Slovenia Vulnerability Solomon Islands Vulnerability Somalia Vulnerability South Africa Vulnerability South America Vulnerability South Asia Vulnerability South Korea Vulnerability Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Albania Risk Profile Algeria Risk Profile American Samoa Risk Profile Andorra Risk Profile Angola Risk Profile Anguilla Risk Profile Antigua and Barbuda Risk Profile Arabia Risk Profile Argentina Risk Profile Armenia Risk Profile Aruba Risk Profile Australia Risk Profile Austria Risk Profile Azerbaijan Risk Profile Bahamas Risk Profile Bahrain Risk Profile Bangladesh Risk Profile Barbados Risk Profile Belarus Risk Profile Belgium Risk Profile Belize Risk Profile Benin Risk Profile Bhutan Risk Profile Bolivia Risk Profile Bosnia and Herzegovina Risk Profile Botswana Risk Profile Brazil Risk Profile British Virgin Islands Risk Profile Brunei Risk Profile Bulgaria Risk Profile Burkina Faso Risk Profile Burundi Risk Profile Cambodia Risk Profile Cameroon Risk Profile Canada Risk Profile Cape Verde Risk Profile Caribbean Central America Risk Profile Cayman Islands Risk Profile Central African Republic Risk Profile Central Asia Risk Profile Chad Risk Profile Chile Risk Profile China Risk Profile Colombia Risk Profile Comoros Risk Profile Congo Risk Profile Conterminous US Risk Profile Cook Islands Risk Profile Costa Rica Risk Profile Croatia Risk Profile Cuba Risk Profile Cyprus Risk Profile Czechia Risk Profile Democratic Republic of the Congo Risk Profile Denmark Risk Profile Djibouti Risk Profile Dominica Risk Profile Dominican Republic Risk Profile East Asia Risk Profile Ecuador Risk Profile Egypt Risk Profile El Salvador Risk Profile Equatorial Guinea Risk Profile Eritrea Risk Profile Estonia Risk Profile Eswatini Risk Profile Ethiopia Risk Profile Europe Risk Profile Fiji Risk Profile Finland Risk Profile France Risk Profile French Guiana Risk Profile Gabon Risk Profile Gambia Risk Profile Georgia Risk Profile Germany Risk Profile Ghana Risk Profile Gibraltar Risk Profile Greece Risk Profile Grenada Risk Profile Guadeloupe Risk Profile Guam Risk Profile Guatemala Risk Profile Guinea Risk Profile Guinea Bissau Risk Profile Guyana Risk Profile Haiti Risk Profile Hawaii Risk Profile Honduras Risk Profile Hong Kong Risk Profile Hungary Risk Profile Iceland Risk Profile India Risk Profile Indonesia Risk Profile Iran Risk Profile Iraq Risk Profile Ireland Risk Profile Isle of Man Risk Profile Israel Risk Profile Italy Risk Profile Ivory Coast Risk Profile Jamaica Risk Profile Japan Risk Profile Jordan Risk Profile Kazakhstan Risk Profile Kenya Risk Profile Kiribati Risk Profile Kosovo Risk Profile Kuwait Risk Profile Kyrgyzstan Risk Profile Laos Risk Profile Latvia Risk Profile Lebanon Risk Profile Lesotho Risk Profile Liberia Risk Profile Libya Risk Profile Liechtenstein Risk Profile Lithuania Risk Profile Luxembourg Risk Profile Macao Risk Profile Madagascar Risk Profile Malawi Risk Profile Malaysia Risk Profile Mali Risk Profile Malta Risk Profile Marshall Islands Risk Profile Martinique Risk Profile Mauritania Risk Profile Mauritius Risk Profile Mexico Risk Profile Micronesia Risk Profile Middle East Risk Profile Moldova Risk Profile Monaco Risk Profile Mongolia Risk Profile Montenegro Risk Profile Montserrat Risk Profile Morocco Risk Profile Mozambique Risk Profile Myanmar Risk Profile Namibia Risk Profile Nauru Risk Profile Nepal Risk Profile Netherlands Risk Profile New Caledonia Risk Profile New Zealand Risk Profile Nicaragua Risk Profile Niger Risk Profile Nigeria Risk Profile Niue Risk Profile North Africa Risk Profile North America Risk Profile North Asia Risk Profile North Korea Risk Profile North Macedonia Risk Profile North and South Korea Risk Profile Northeast Asia Risk Profile Northern Mariana Islands Risk Profile Northwest Asia Risk Profile Norway Risk Profile Oceania Risk Profile Oman Risk Profile Pacific Islands Risk Profile Pakistan Risk Profile Palau Risk Profile Palestine Risk Profile Panama Risk Profile Papua New Guinea Risk Profile Paraguay Risk Profile Peru Risk Profile Philippines Risk Profile Poland Risk Profile Portugal Risk Profile Puerto Rico Risk Profile Qatar Risk Profile Romania Risk Profile Russia Risk Profile Rwanda Risk Profile Saint Kitts and Nevis Risk Profile Saint Lucia Risk Profile Saint Vincent and the Grenadines Risk Profile Samoa Risk Profile Sao Tome and Principe Risk Profile Saudi Arabia Risk Profile Senegal Risk Profile Serbia Risk Profile Seychelles Risk Profile Sierra Leone Risk Profile Singapore Risk Profile Slovakia Risk Profile Slovenia Risk Profile Solomon Islands Risk Profile Somalia Risk Profile South Africa Risk Profile South America Risk Profile South Asia Risk Profile South Korea Risk Profile Search Found Country/Region Resource Url Afghanistan Exposure Africa Exposure Alaska Exposure Albania Exposure Algeria Exposure American Samoa Exposure Andorra Exposure Angola Exposure Anguilla Exposure Antigua and Barbuda Exposure Arabia Exposure Argentina Exposure Armenia Exposure Aruba Exposure Australia Exposure Austria Exposure Azerbaijan Exposure Bahamas Exposure Bahrain Exposure Bangladesh Exposure Barbados Exposure Belarus Exposure Belgium Exposure Belize Exposure Benin Exposure Bhutan Exposure Bolivia Exposure Bosnia and Herzegovina Exposure Botswana Exposure Brazil Exposure British Virgin Islands Exposure Brunei Exposure Bulgaria Exposure Burkina Faso Exposure Burundi Exposure Cambodia Exposure Cameroon Exposure Canada Exposure Cape Verde Exposure Caribbean Central America Exposure Cayman Islands Exposure Central African Republic Exposure Central Asia Exposure Chad Exposure Chile Exposure China Exposure Colombia Exposure Comoros Exposure Congo Exposure Conterminous US Exposure Cook Islands Exposure Costa Rica Exposure Croatia Exposure Cuba Exposure Cyprus Exposure Czechia Exposure Democratic Republic of the Congo Exposure Denmark Exposure Djibouti Exposure Dominica Exposure Dominican Republic Exposure East Asia Exposure Ecuador Exposure Egypt Exposure El Salvador Exposure Equatorial Guinea Exposure Eritrea Exposure Estonia Exposure Eswatini Exposure Ethiopia Exposure Europe Exposure Fiji Exposure Finland Exposure France Exposure French Guiana Exposure Gabon Exposure Gambia Exposure Georgia Exposure Germany Exposure Ghana Exposure Gibraltar Exposure Greece Exposure Grenada Exposure Guadeloupe Exposure Guam Exposure Guatemala Exposure Guinea Exposure Guinea Bissau Exposure Guyana Exposure Haiti Exposure Hawaii Exposure Honduras Exposure Hong Kong Exposure Hungary Exposure Iceland Exposure India Exposure Indonesia Exposure Iran Exposure Iraq Exposure Ireland Exposure Isle of Man Exposure Israel Exposure Italy Exposure Ivory Coast Exposure Jamaica Exposure Japan Exposure Jordan Exposure Kazakhstan Exposure Kenya Exposure Kiribati Exposure Kosovo Exposure Kuwait Exposure Kyrgyzstan Exposure Laos Exposure Latvia Exposure Lebanon Exposure Lesotho Exposure Liberia Exposure Libya Exposure Liechtenstein Exposure Lithuania Exposure Luxembourg Exposure Macao Exposure Madagascar Exposure Malawi Exposure Malaysia Exposure Mali Exposure Malta Exposure Marshall Islands Exposure Martinique Exposure Mauritania Exposure Mauritius Exposure Mexico Exposure Micronesia Exposure Middle East Exposure Moldova Exposure Monaco Exposure Mongolia Exposure Montenegro Exposure Montserrat Exposure Morocco Exposure Mozambique Exposure Myanmar Exposure Namibia Exposure Nauru Exposure Nepal Exposure Netherlands Exposure New Caledonia Exposure New Zealand Exposure Nicaragua Exposure Niger Exposure Nigeria Exposure Niue Exposure North Africa Exposure North America Exposure North Asia Exposure North Korea Exposure North Macedonia Exposure North and South Korea Exposure Northeast Asia Exposure Northern Mariana Islands Exposure Northwest Asia Exposure Norway Exposure Oceania Exposure Oman Exposure Pacific Islands Exposure Pakistan Exposure Palau Exposure Palestine Exposure Panama Exposure Papua New Guinea Exposure Paraguay Exposure Peru Exposure Philippines Exposure Poland Exposure Portugal Exposure Puerto Rico Exposure Qatar Exposure Romania Exposure Russia Exposure Rwanda Exposure Saint Kitts and Nevis Exposure Saint Lucia Exposure Saint Vincent and the Grenadines Exposure Samoa Exposure Sao Tome and Principe Exposure Saudi Arabia Exposure Senegal Exposure Serbia Exposure Seychelles Exposure Sierra Leone Exposure Singapore Exposure Slovakia Exposure Slovenia Exposure Solomon Islands Exposure Somalia Exposure South Africa Exposure South America Exposure South Asia Exposure South Korea Exposure Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Vulnerability Africa Vulnerability Alaska Vulnerability Albania Vulnerability Algeria Vulnerability American Samoa Vulnerability Andorra Vulnerability Angola Vulnerability Anguilla Vulnerability Antigua and Barbuda Vulnerability Arabia Vulnerability Argentina Vulnerability Armenia Vulnerability Aruba Vulnerability Australia Vulnerability Austria Vulnerability Azerbaijan Vulnerability Bahamas Vulnerability Bahrain Vulnerability Bangladesh Vulnerability Barbados Vulnerability Belarus Vulnerability Belgium Vulnerability Belize Vulnerability Benin Vulnerability Bhutan Vulnerability Bolivia Vulnerability Bosnia and Herzegovina Vulnerability Botswana Vulnerability Brazil Vulnerability British Virgin Islands Vulnerability Brunei Vulnerability Bulgaria Vulnerability Burkina Faso Vulnerability Burundi Vulnerability Cambodia Vulnerability Cameroon Vulnerability Canada Vulnerability Cape Verde Vulnerability Caribbean Central America Vulnerability Cayman Islands Vulnerability Central African Republic Vulnerability Central Asia Vulnerability Chad Vulnerability Chile Vulnerability China Vulnerability Colombia Vulnerability Comoros Vulnerability Congo Vulnerability Conterminous US Vulnerability Cook Islands Vulnerability Costa Rica Vulnerability Croatia Vulnerability Cuba Vulnerability Cyprus Vulnerability Czechia Vulnerability Democratic Republic of the Congo Vulnerability Denmark Vulnerability Djibouti Vulnerability Dominica Vulnerability Dominican Republic Vulnerability East Asia Vulnerability Ecuador Vulnerability Egypt Vulnerability El Salvador Vulnerability Equatorial Guinea Vulnerability Eritrea Vulnerability Estonia Vulnerability Eswatini Vulnerability Ethiopia Vulnerability Europe Vulnerability Fiji Vulnerability Finland Vulnerability France Vulnerability French Guiana Vulnerability Gabon Vulnerability Gambia Vulnerability Georgia Vulnerability Germany Vulnerability Ghana Vulnerability Gibraltar Vulnerability Greece Vulnerability Grenada Vulnerability Guadeloupe Vulnerability Guam Vulnerability Guatemala Vulnerability Guinea Vulnerability Guinea Bissau Vulnerability Guyana Vulnerability Haiti Vulnerability Hawaii Vulnerability Honduras Vulnerability Hong Kong Vulnerability Hungary Vulnerability Iceland Vulnerability India Vulnerability Indonesia Vulnerability Iran Vulnerability Iraq Vulnerability Ireland Vulnerability Isle of Man Vulnerability Israel Vulnerability Italy Vulnerability Ivory Coast Vulnerability Jamaica Vulnerability Japan Vulnerability Jordan Vulnerability Kazakhstan Vulnerability Kenya Vulnerability Kiribati Vulnerability Kosovo Vulnerability Kuwait Vulnerability Kyrgyzstan Vulnerability Laos Vulnerability Latvia Vulnerability Lebanon Vulnerability Lesotho Vulnerability Liberia Vulnerability Libya Vulnerability Liechtenstein Vulnerability Lithuania Vulnerability Luxembourg Vulnerability Macao Vulnerability Madagascar Vulnerability Malawi Vulnerability Malaysia Vulnerability Mali Vulnerability Malta Vulnerability Marshall Islands Vulnerability Martinique Vulnerability Mauritania Vulnerability Mauritius Vulnerability Mexico Vulnerability Micronesia Vulnerability Middle East Vulnerability Moldova Vulnerability Monaco Vulnerability Mongolia Vulnerability Montenegro Vulnerability Montserrat Vulnerability Morocco Vulnerability Mozambique Vulnerability Myanmar Vulnerability Namibia Vulnerability Nauru Vulnerability Nepal Vulnerability Netherlands Vulnerability New Caledonia Vulnerability New Zealand Vulnerability Nicaragua Vulnerability Niger Vulnerability Nigeria Vulnerability Niue Vulnerability North Africa Vulnerability North America Vulnerability North Asia Vulnerability North Korea Vulnerability North Macedonia Vulnerability North and South Korea Vulnerability Northeast Asia Vulnerability Northern Mariana Islands Vulnerability Northwest Asia Vulnerability Norway Vulnerability Oceania Vulnerability Oman Vulnerability Pacific Islands Vulnerability Pakistan Vulnerability Palau Vulnerability Palestine Vulnerability Panama Vulnerability Papua New Guinea Vulnerability Paraguay Vulnerability Peru Vulnerability Philippines Vulnerability Poland Vulnerability Portugal Vulnerability Puerto Rico Vulnerability Qatar Vulnerability Romania Vulnerability Russia Vulnerability Rwanda Vulnerability Saint Kitts and Nevis Vulnerability Saint Lucia Vulnerability Saint Vincent and the Grenadines Vulnerability Samoa Vulnerability Sao Tome and Principe Vulnerability Saudi Arabia Vulnerability Senegal Vulnerability Serbia Vulnerability Seychelles Vulnerability Sierra Leone Vulnerability Singapore Vulnerability Slovakia Vulnerability Slovenia Vulnerability Solomon Islands Vulnerability Somalia Vulnerability South Africa Vulnerability South America Vulnerability South Asia Vulnerability South Korea Vulnerability Preview Preview is not available. Search Found Country/Region Resource Url Afghanistan Risk Profile Africa Risk Profile Alaska Risk Profile Albania Risk Profile Algeria Risk Profile American Samoa Risk Profile Andorra Risk Profile Angola Risk Profile Anguilla Risk Profile Antigua and Barbuda Risk Profile Arabia Risk Profile Argentina Risk Profile Armenia Risk Profile Aruba Risk Profile Australia Risk Profile Austria Risk Profile Azerbaijan Risk Profile Bahamas Risk Profile Bahrain Risk Profile Bangladesh Risk Profile Barbados Risk Profile Belarus Risk Profile Belgium Risk Profile Belize Risk Profile Benin Risk Profile Bhutan Risk Profile Bolivia Risk Profile Bosnia and Herzegovina Risk Profile Botswana Risk Profile Brazil Risk Profile British Virgin Islands Risk Profile Brunei Risk Profile Bulgaria Risk Profile Burkina Faso Risk Profile Burundi Risk Profile Cambodia Risk Profile Cameroon Risk Profile Canada Risk Profile Cape Verde Risk Profile Caribbean Central America Risk Profile Cayman Islands Risk Profile Central African Republic Risk Profile Central Asia Risk Profile Chad Risk Profile Chile Risk Profile China Risk Profile Colombia Risk Profile Comoros Risk Profile Congo Risk Profile Conterminous US Risk Profile Cook Islands Risk Profile Costa Rica Risk Profile Croatia Risk Profile Cuba Risk Profile Cyprus Risk Profile Czechia Risk Profile Democratic Republic of the Congo Risk Profile Denmark Risk Profile Djibouti Risk Profile Dominica Risk Profile Dominican Republic Risk Profile East Asia Risk Profile Ecuador Risk Profile Egypt Risk Profile El Salvador Risk Profile Equatorial Guinea Risk Profile Eritrea Risk Profile Estonia Risk Profile Eswatini Risk Profile Ethiopia Risk Profile Europe Risk Profile Fiji Risk Profile Finland Risk Profile France Risk Profile French Guiana Risk Profile Gabon Risk Profile Gambia Risk Profile Georgia Risk Profile Germany Risk Profile Ghana Risk Profile Gibraltar Risk Profile Greece Risk Profile Grenada Risk Profile Guadeloupe Risk Profile Guam Risk Profile Guatemala Risk Profile Guinea Risk Profile Guinea Bissau Risk Profile Guyana Risk Profile Haiti Risk Profile Hawaii Risk Profile Honduras Risk Profile Hong Kong Risk Profile Hungary Risk Profile Iceland Risk Profile India Risk Profile Indonesia Risk Profile Iran Risk Profile Iraq Risk Profile Ireland Risk Profile Isle of Man Risk Profile Israel Risk Profile Italy Risk Profile Ivory Coast Risk Profile Jamaica Risk Profile Japan Risk Profile Jordan Risk Profile Kazakhstan Risk Profile Kenya Risk Profile Kiribati Risk Profile Kosovo Risk Profile Kuwait Risk Profile Kyrgyzstan Risk Profile Laos Risk Profile Latvia Risk Profile Lebanon Risk Profile Lesotho Risk Profile Liberia Risk Profile Libya Risk Profile Liechtenstein Risk Profile Lithuania Risk Profile Luxembourg Risk Profile Macao Risk Profile Madagascar Risk Profile Malawi Risk Profile Malaysia Risk Profile Mali Risk Profile Malta Risk Profile Marshall Islands Risk Profile Martinique Risk Profile Mauritania Risk Profile Mauritius Risk Profile Mexico Risk Profile Micronesia Risk Profile Middle East Risk Profile Moldova Risk Profile Monaco Risk Profile Mongolia Risk Profile Montenegro Risk Profile Montserrat Risk Profile Morocco Risk Profile Mozambique Risk Profile Myanmar Risk Profile Namibia Risk Profile Nauru Risk Profile Nepal Risk Profile Netherlands Risk Profile New Caledonia Risk Profile New Zealand Risk Profile Nicaragua Risk Profile Niger Risk Profile Nigeria Risk Profile Niue Risk Profile North Africa Risk Profile North America Risk Profile North Asia Risk Profile North Korea Risk Profile North Macedonia Risk Profile North and South Korea Risk Profile Northeast Asia Risk Profile Northern Mariana Islands Risk Profile Northwest Asia Risk Profile Norway Risk Profile Oceania Risk Profile Oman Risk Profile Pacific Islands Risk Profile Pakistan Risk Profile Palau Risk Profile Palestine Risk Profile Panama Risk Profile Papua New Guinea Risk Profile Paraguay Risk Profile Peru Risk Profile Philippines Risk Profile Poland Risk Profile Portugal Risk Profile Puerto Rico Risk Profile Qatar Risk Profile Romania Risk Profile Russia Risk Profile Rwanda Risk Profile Saint Kitts and Nevis Risk Profile Saint Lucia Risk Profile Saint Vincent and the Grenadines Risk Profile Samoa Risk Profile Sao Tome and Principe Risk Profile Saudi Arabia Risk Profile Senegal Risk Profile Serbia Risk Profile Seychelles Risk Profile Sierra Leone Risk Profile Singapore Risk Profile Slovakia Risk Profile Slovenia Risk Profile Solomon Islands Risk Profile Somalia Risk Profile South Africa Risk Profile South America Risk Profile South Asia Risk Profile South Korea Risk Profile Preview Preview is not available. 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