Occupancy patterns are known to strongly affect the number of people killed by earthquakes. Existing exposure models for Europe based on housing census do not account for the daily movement of the population between the place of residence (residential occupancy) and places of economic activity (non-residential occupancy), or the seasonal patterns due to tourism. This study presents a framework to upgrade exposure models from static to 'dynamic', i.e., allowing the input population to change in time and space based on daily and monthly population movement patterns. Open-source population data is used to disaggregate and rescale occupants inside residential, commercial and industrial buildings of 28 European countries, resulting in 24 occupancy categories: two times (i.e., day and night) x 12 months at 30 arc-seconds resolution. The static vs dynamic exposure models are compared using the number and distribution of fatalities resulting from loss calculations for a stochastic set of earthquakes generated from the European Seismic Hazard model (ESHM20). The results demonstrate that the spatiotemporal patterns of population can significantly impact earthquake mortality rates and should not be neglected in scenario loss assessment. The results also demonstrate that the worst occurrence time depends on both the distribution of indoor population between building occupancies and the earthquake rupture characteristics. The ability to capture population distribution during the day and night or seasonal changes (e.g., winter vs summer) is a feature that can advance the ongoing rapid damage/loss assessment services in Europe and consequently support emergency response planning.

This study introduces a unified framework for evaluating the physical impacts of earthquakes and volcanic eruptions on buildings, leveraging upon the existing capabilities of the OpenQuake engine for earthquake risk assessment and various existing packages for computing volcanic hazard footprints. We illustrate the capabilities of the new OpenQuake volcanic scenario module using two case studies: a VEI (Volcanic Explosivity Index) 3-4 eruption of Nevado del Ruiz volcano in Colombia and a VEI 6 eruption of Mount Pinatubo in the Philippines, employing various methods for simulating hazard footprints for tephra fall, lava flows, pyroclastic density currents, and lahars. The findings demonstrate the versatility of OpenQuake in managing diverse geohazards and its potential for further extension to other hazards, while this integration advances our ability to assess and manage disaster risk.

In recent decades, hundreds of studies have covered seismic vulnerability assessment and the derivation of fragility models. However, these studies primarily focus on structural damage and the associated repair costs. Assessing fatalities requires an evaluation of the proportion of damaged buildings that suffer partial or total collapse, as well as the expected fatality rates for occupants inside those collapsed buildings. To support these modeling needs, we reviewed past studies on casualties, existing proposals for collapse and fatality rates, and detailed damage databases that characterize different collapse mechanisms. Based on this review, collapse and fatality rates are proposed relative to a baseline building class. These rates are further calibrated considering reported fatalities since 1950 and the average annual fatalities estimated by the Global Seismic Risk Model of the Global Earthquake Model (GEM) Foundation. Results show that the probability of collapse tends to decrease with the number of stories, while fatality rates have the opposite trend. Furthermore, an open-access database of calibrated collapse and fatality rates is provided and can be used to assess fatalities due to earthquake scenarios or in probabilistic seismic risk analysis.

The estimation of road disruptions due to building debris in urban contexts requires the availability of exposure data at the building level, which is often not available. In this study, we explore how open global datasets at different scales can be integrated with machine learning algorithms to estimate road disruptions following seismic events, overcoming the need for detailed datasets. Using simulated impact data for the municipality of Lisbon, we train a Random Forest model to predict road disruptions due to building collapses. Then, we apply this model to another urban environment (the municipality of Amadora) to evaluate the performance of the model using input data unseen during the training process. Finally, we employ the surrogate model using information extracted from globally available datasets characterizing the built environment and the road network. The proposed approach allows identifying areas within urban centers where road disruptions are likely to occur, and where risk reduction measures should be prioritized to minimize the impact of destructive earthquakes.

This study has been sponsored by the Asian Development Bank (ADB) and is a contribution to the project ADB TA 9307-MYA: Strengthening Climate and Disaster Resilience of Myanmar Communities. This report has been produced as part of a collaboration between the GEM Foundation and the Myanmar Earthquake Committee.

Please prepare your proposals with this Application Template and convert to a PDF file. Please ensure that your responses are clear and concise. If your organisation can provide additional supporting documents (e.g., reports, case studies, project summaries), you may attach them to your application.

The Global Earthquake Model (GEM) Foundation is committed to advancing earthquake risk assessment, modelling, and mitigation efforts worldwide. As part of our mission to strengthen global collaboration, we are offering a unique opportunity for public organisations to join GEM’s Governing Board as Public Governors. While GEM’s Public Governors typically contribute annual sponsorship fees, selected public sector partners under this opportunity will instead be granted Public Governor status (for a period of 3 years) based purely on merit, strategic alignment, and contributions to seismic risk reduction. Through this partnership, Public Governors will gain access to GEM’s global network, research, models and tools, thus contributing to and benefiting from the latest advances in earthquake hazard and risk knowledge. We invite interested public organisations to submit a proposal outlining their commitment and potential contributions to GEM’s mission using the template that can be downloaded from the GEM website.

GEM’s Gender Equality Plan reflects ongoing efforts to promote fairness, inclusivity, and equal opportunities across the organisation. The highlights below present key achievements and areas of focus in 2024, including gender pay equity, workforce balance, leadership opportunities, and support for work-life balance.

The assessment of the seismic risk at a national scale represents an important resource in order to introduce measures that may reduce potential losses due to future earthquakes. This evaluation results from the combination of three components: seismic hazard, structural vulnerability and exposure data. In this study, a review of existing studies focusing on each one of these areas is carried out, and used together with data from the 2011 Building Census in Portugal to compile the required input models for the evaluation of seismic hazard and risk. In order to better characterize the epistemic uncertainty in the calculations, several approaches are considered within a logic tree structure, such as the consideration of different seismic source zonations, the employment of vulnerability functions derived based on various damage criteria and the employment of distinct spatial resolutions in the exposure model. The aim of this paper is thus to provide an overview of the recent developments regarding the different aspects that influence the seismic hazard and risk in Portugal, as well as an up-to-date identification of the regions that are more vulnerable to earthquakes, together with the expected losses for a probability of exceedance of 10 % in 50 years. The results from the present study were obtained through the OpenQuake engine, the open-source software for seismic risk and hazard assessment developed within the global earthquake model (GEM) initiative.

The lack of empirical data regarding earthquake damage or losses has propelled the development of dozens of analytical methodologies for the derivation of fragility and vulnerability functions. Each method will naturally have its strengths and weaknesses, which will consequently affect the associated risk estimates. With the purpose of sharing knowledge on vulnerability modeling, identifying shortcomings in the existing methods, and recommending improvements to the current practice, a group of vulnerability experts met in Pavia (Italy) in April 2017. Critical topics related to the selection of ground motion records, modeling of complex real structures through simplified approaches, propagation of aleatory and epistemic uncertainties, and validation of vulnerability results were discussed, and suggestions were proposed to improve the reliability and accuracy in vulnerability modeling.