top of page

Global Earthquake Social Vulnerability Map



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.

Cutter, S. L., B. J. Boruff, and W. L. Shirley. 2003. Social Vulnerability to Environmental Hazards. Social Science Quarterly 84 (2): 242-261.

National Research Council. 2006. Facing Hazards and Disasters: Understanding Human Dimensions, Joseph Henry Press, Washington, D.C. Nersesian, W. 1988. Infant Mortality in Socially Vulnerable Populations. Ann. Rev. Public Health 9:361-377.

Tierney, K. J., M. K. Lindell, and R. W. Perry. 2001. Facing the Unexpected: Disaster Preparedness and Response in the United States. Washington, D.C.: Joseph Henry Press.


The Global Social Vulnerability Map, is a composite index that was developed to measure characteristics or qualities of social systems that create the potential for loss or harm. Here, the social vulnerability index helps to explain why some countries will experience adverse impacts from earthquakes differentially where the linking of social capacities with demographic attributes suggests that communities with higher percentages of age dependent populations, homeless, disabled, under-educated, and foreign migrants are likely to exhibit higher social vulnerability than communities lacking these characteristics. Other relevant factors that affect the social vulnerability of populations include population density, slum populations, and international tourists.

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 ( 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:

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: This work is licensed under the terms of the Creative Commons Attribution - Non Commercial-Share Alike 4.0 International License (CC BY-NC-SA).


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.

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.


GEM (Global Earthquake Model) Foundation Via Ferrata, 1 - 27100, Pavia, Italy

More information available at: www.


bottom of page