Interdependencies between critical infrastructures and the economy amplify the effects of damage caused by disasters. The growing interest in impacts beyond physical damage and community resilience has spurred a surge in literature on economic modeling methodologies for estimating indirect economic impacts of disasters and the recovery of economic activity over time. In this review, we present a framework for categorizing modeling approaches that assess indirect economic impacts across natural hazards and anthropogenic disasters such as cyber attacks. We first conduct a comparative analysis of macroeconomic models, focusing on the approaches capturing sectoral interdependencies. These include the Leontief Input-Output (I/O) model, the Inoperability Input-Output Model (IIM), the Dynamic Inoperability Input-Output Model (DIIM), the Adaptive Regional Input-Output (ARIO) model, and the Computable General Equilibrium (CGE) model and its extensions. We evaluate their applicability to disaster scenarios based on input data availability, the compatibility of model assumptions, and output capabilities. We also reveal the functional relationships of input data and output metrics across economic modeling approaches for inter-sectoral impacts. Furthermore, we examine how the damage mechanisms posed by different types of disasters translate into model inputs and impact modeling processes. This synthesis provides guidance for researchers and practitioners in selecting and configuring models based on specific disaster scenarios. It also identifies the gaps in the literature, including the need for a deeper understanding of model performance reliability, key drivers of economic outcomes in different disaster contexts, and the disparities in modeling approach applications across various hazard types.
Recent research demonstrates the need for comprehensive frameworks to achieve an appropriate level of resilience (e.g., energy, seismic) of the European building stock, through integrated retrofitting interventions. Different frameworks have been proposed to identify optimal interventions when several feasible alternatives are available, considering multiple decision variables of different nature, such as social, economic, or technical. Within these efforts and frameworks, less attention has been paid to the post-earthquake recovery time of buildings and communities, thus ignoring the significance of reaching a desired recovery state (e.g., functional recovery) within a specified time frame. To overcome this limitation, this study estimates post-earthquake recovery times and uses them as one of the decision variables in multi-criteria identification of optimal retrofitting of an existing RC building. The case-study building is representative of the Italian school buildings constructed between the 1960s and 1970s and was analysed under two seismic hazard levels (moderate and high). Following the identification of the main structural deficiencies of the as-built structure through nonlinear static analyses, four seismic retrofit measures were selected. Then, the earthquake-induced downtime of each of the four retrofitted building configurations was assessed, analysing the different recovery times as a function of the seismic hazard level and the recovery state. A downtime-based metric, namely the expected annual downtime, was introduced as decision variable within an available multi-criteria decision-making framework to include the impact of downtime, rank the four retrofit measures and identify the preferable one.
Self-centering systems are increasingly studied after devastating earthquakes in the 2010s that caused irreparable damage to buildings. Currently, there is conflicting evidence as to whether the re-centering (restoring) capabilities are gained at the expense of hysteretic damping, potentially leading to larger peak displacements and damage to non-structural elements. This study examines the earthquake response of self-centering and non-self-centering systems through analyses of 4-storey and 8-storey steel-braced frames. The Resilient Slip Friction Joint (RSFJ) dampers, combined with steel braces in series, represent the self-centering bracing system, whereas the Buckling Restrained Braces (BRBs) represent the non-self-centering bracing system. Results suggest that peak displacements, base shears, and floor accelerations were comparable between the two systems. A possible explanation is that the peak response occurs on the first major excursion; similar peaks result from similar backbone curves in the run-up to the peak. Conversely, the amount of hysteretic damping only begins to affect the post-peak behavior. For instance, the RSFJ system reintroduces seismic energy into the structure post-peak (rather than dissipating it like the BRB). Subsequently, it leads to larger vibration amplitudes about the central position, increasing the risk of secondary peaks. This contrasts with the BRB system, which exhibits smaller vibration amplitudes about an increasingly deformed position due to seismic ratcheting. Unsurprisingly, residual deformations were high for the BRBs (1.7 % on average) and negligible for the RSFJ. However, RSFJ produced smaller peak inter-storey drifts between 13 %-18 % but higher peak accelerations by 4 %-5 %. The results suggest that multi-storey braced frames could be designed with similar or smaller forces when self-centering systems are used.
This study developed a digital twin (DT) and structural health monitoring (SHM) system for a balanced cantilever bridge, utilizing advanced measurement techniques to enhance accuracy. Vibration and dynamic strain measurements were obtained using accelerometers and piezo-resistive strain gauges, capturing low-magnitude dynamic strains during operational vibrations. 3D-LiDAR scanning and Ultrasonic Pulse Velocity (UPV) tests captured the bridge's as-is geometry and modulus of elasticity. The resulting detailed 3D point cloud model revealed the structure's true state and highlighted discrepancies between the as-designed and as-built conditions. Dynamic properties, including modal frequencies and shapes, were extracted from the strain and acceleration measurements, providing critical insights into the bridge's structural behavior. The neutral axis depth, indicating stress distribution and potential damage, was accurately determined. Good agreement between vibration measurement data and the as-is model results validated the reliability of the digital twin model. Dynamic strain patterns and neutral axis parameters showed strong correlation with model predictions, serving as sensitive indicators of local damage. The baseline digital twin model and measurement results establish a foundation for future bridge inspections and investigations. This study demonstrates the effectiveness of combining digital twin technology with field measurements for real-time monitoring and predictive maintenance, ensuring the sustainability and safety of the bridge infrastructure, thereby enhancing its overall resilience to operational and environmental stressors.
During the Mw = 7.1 September 19, 2017 earthquake with epicenter nearby the boundary of Puebla and Morelos states, an important amount of structural damage occurred in Mexico City, 120 km away from the epicenter. Among the most severely affected sectors was the housing sector. At least 16 houses collapsed or partially collapsed during the earthquake, more than 5100 were demolished with public funds and more than 5800 were sternly damaged and required to be rehabilitated. Close to 1300 apartment buildings were severely damaged, where 33 of them collapsed or partially collapsed. Then, the recovery of the housing sector, which is instrumental for both the social and economy recovery of the city, have posed a monumental task and challenge to the citizens and authorities of Mexico City. In this paper, the author summarizes how these efforts to recover the affected housing sector have been in Mexico City close to eight years after the 9/19/2017 earthquake, based upon detailed statistics and information compiled by the author from different sources. It can be concluded that after 7+ years, the recovery process of single-family houses has been a success, as close to 100 % of the affected homes have been fully recovered with much better projects than the originally damaged. However, the recovery process of apartment buildings, although important, still has a long way to go. As of May 2025, only 59.6 % of the affected buildings have been fully recovered (31.3 % using public funds), other 11.3 % are under construction or rehabilitation process and, in 29.1 % of the affected buildings, no action has been taken to speed their recovery.
The efficient transportation of goods is vital for the economic growth of communities, making developing and maintaining seaport infrastructure an essential component of the marine transportation system. Given their geographic locations, ports are consistently at risk from natural hazards, making the resilience of port infrastructure an essential goal.
Despite considerable progress in resilience research, there remains a gap in methods tailored explicitly to assessing port resilience, particularly under extreme wind events. Current approaches often do not capture the full complexity of port systems, as they tend to focus on isolated aspects, such as structural resilience.
This paper introduces the PORT Resilience Framework, addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources. The indicators are then organized under four comprehensive resilience dimensions: Physical Infrastructure, ICT (i.e., Information and Communication Technology) and Equipment; Organization and Business Management; Resources and Economic Development; and Territory, Environment, and Stakeholders. This classification is summarized under the acronym "PORT."
This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard, transforming the data into a quantifiable Loss of Resilience index. The approach is applied to a case study, assessing the resilience of a real Terminal against wind action using real data sourced from the port management.
The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery, with insufficient staffing leading to prolonged recovery periods. The study further demonstrated that post-disruption activity surges, captured by different serviceability function methodologies, often created operational bottlenecks, challenging the port's overall recovery.
Flooding has become an emerging global catastrophe, generating considerable damage to both infrastructures and lives. Despite the critical need for quantitative assessments of both flood damage and the effectiveness of flood mitigation measures, most existing studies have focused on isolated aspects of flood risk. Only a very limited number of studies have comprehensively integrated hazard mapping, hydrodynamic simulations, and economic damage estimations to evaluate the real-world impact and effectiveness of flood mitigation measures (FMMs). This study presents a multi-method approach to evaluate the performance of such established structural FMMs. Initially, hazard assessments for two selected case study areas, the Colombo Metropolitan Area in Sri Lanka and Auckland, New Zealand, two flood-prone cities with contrasting geographical contexts. Flood inundation mapping for the Madiwela South Diversion, Colombo, Sri Lanka, was performed using hydrodynamic modeling to demonstrate the reduction in flood inundation area and depth after the implementation of the measure, considering six (6) design return periods (RPs). Subsequently, tangible and intangible property damage estimations for “without FMMs” and “with FMMs” were evaluated to identify the benefit of responding to flood conditions, utilising a vulnerability-based economic analysis. In addition to damage estimations, the study adopts a novel approach by conducting an investment viability analysis to find the Benefit-to-Cost ratios and Net Present Value of nine (9) selected FMMs implemented by Sri Lanka Land Development Co-operation (SLLDC). The FMMs implemented by SLLDC were selected from Colombo, Sri Lanka. The quantified damage estimates revealed a reduction in flood damages ranging from 39 % to 63 %, alongside a decrease in flood inundation depths between 9 % and 12 %, and the results underscore the significant effectiveness of FMMs in managing urban flooding and minimising its impacts. This cross-disciplinary methodology enables a transferable framework for resilience-oriented urban planning in diverse hydrological and geographical contexts.
Resilience of residential buildings depends on the recovery process that follows the impact of natural hazards, such as tsunamis. In particular, the historical database from tsunamis that occurred in different Countries (Sri Lanka, Thailand, Indonesia, and Japan) have been considered. This study proposes a selection of the best-fitting models to assess the recovery process of tsunamis to derive a framework for resilience at geographical scales. Since the damage depends on the vulnerability of the buildings, several typologies have been considered. In addition, aggregations of different damage sources have been considered to propose comprehensive relationships. The definition of best-fitting recovery functions for different countries has been discussed to implement them in advanced platforms and calculate the resilience to tsunamis.