Effective flood risk mitigation requires the impacts of flood events to be much better and more reliably known than is currently the case. Available post-flood damage assessments usually supply only a partial vision of the consequences of the floods as they typically respond to the specific needs of a particular stakeholder. Consequently, they generally focus (i) on particular items at risk, (ii) on a certain time window after the occurrence of the flood, (iii) on a specific scale of analysis or (iv) on the analysis of damage only, without an investigation of damage mechanisms and root causes. This paper responds to the necessity of a more integrated interpretation of flood events as the base to address the variety of needs arising after a disaster. In particular, a model is supplied to develop multipurpose complete event scenarios. The model organizes available information after the event according to five logical axes. This way post-flood damage assessments can be developed that (i) are multisectoral, (ii) consider physical as well as functional and systemic damage, (iii) address the spatial scales that are relevant for the event at stake depending on the type of damage that has to be analyzed, i.e., direct, functional and systemic, (iv) consider the temporal evolution of damage and finally (v) allow damage mechanisms and root causes to be understood. All the above features are key for the multi-usability of resulting flood scenarios. The model allows, on the one hand, the rationalization of efforts currently implemented in ex post damage assessments, also with the objective of better programming financial resources that will be needed for these types of events in the future. On the other hand, integrated interpretations of flood events are fundamental to adapting and optimizing flood mitigation strategies on the basis of thorough forensic investigation of each event, as corroborated by the implementation of the model in a case study.

The paper offers a disaster risk management perspective to analyze the COVID-19 pandemic and to propose and assess non-pharmaceutical mitigation measures for the recovery phase. Three main aspects are tackled: (i) the need to take a scenario-based approach; (i) the need to propose more fine-tuned and context-sensitive mitigation measures, the effectiveness and the cost–benefit of which must be carefully appraised; (iii) better communication as a fundamental pillar of any mitigation measure. Evidence and ideas from the field of natural disasters and man-made technological incidents are applied to tackle the health risk posed by the SARS-COV 2 virus and its rapid spread according to a multi-disciplinary perspective that addresses the health-related challenges and the need to avoid societal and economic breakdown.

This review seeks to understand what urban planning and management can do to reduce disaster risk and help cities adapt to the impacts of climate change. To achieve this, it examines various streams of the literature, as the topic sits at the intersection of several distinct but relevant disciplinary fields. These include urban planning in hazardous areas, recovery planning, disaster risk reduction (an umbrella term encompassing disciplines from engineering to geography and sociology), and, more recently, climate change adaptation. To navigate this vast body of knowledge, a conceptual framework is proposed to guide the selection of the relevant literature, and the strategy for this selection is detailed in the methodological section. This review adopts elements of both critical and theoretical approaches: it does not aim to be comprehensive or to systematically search each disciplinary domain addressed. While acknowledging the limitations and potential biases in the selection of articles and books, the review reflects an evolution in the discourse on urban planning for resilience. The discussion explores how the concept of resilience has emerged as a valuable bridge between disaster risk reduction, sustainability, and climate change adaptation—especially as cities face increasing exposure and vulnerability to stresses that are now more frequently compounded, multi-hazard, and cascading. The conclusion outlines the gaps and challenges that researchers, practitioners, and policy makers need to address moving forward.

The increasing trend towards the global use of Information Technology (IT) is currently determining the need for more and better infrastructures (both physical and digital) for processing, storing and transferring large amounts of data. As Critical Infrastructure (CI) that is potentially exposed and vulnerable to the impact of different types of phenomena (natural, technological, na-tech, etc.), data centers have to guarantee higher levels of security (physical, logical and operational), reliability and efficiency in the provision of services. Starting from a discussion of the main evidence related to this topic, considering both the most recent cases of failure and serious damage to data centers and the evolution of international and European regulation and standards, the authors propose an analytical methodology to assess the territorial risk factors for data centers by a multirisk, multi-dimensional and systemic approach. This proposal leads not only to a more explicit definition of exposure and vulnerable components, but also to the recognition of resources that—in the case of accidental events involving (directly or indirectly) data center infrastructures—may be implemented at different territorial levels as “protection” factors to ensure business continuity by considering the entire resilience cycle, from the prevention phase to the response and recovery phases.

Effective and efficient management of post-disaster damage and loss data is a key component of disaster risk reduction and climate change adaptation policies to fulfil the requirements of the Sendai Framework, Sustainable Development Goals, and more recently, the European Climate Law. However, the reality of organized and structured damage and loss data collection is still in its infancy. In the era of rapid technological improvements, with overwhelming volumes and channels of data, we still record a lack of basic figures of disaster losses at the scale, granularity and level of detail needed for most applications. First, a theoretical overview of data science applied to disaster risk management and the description of collection procedures and use of damage data for buildings in the case of earthquakes for Italy and Greece are provided. Second, the Information System (IS) which is intended to enhance damage and loss data collection and management proposed by the LODE (Loss Data Enhancement for Disaster Risk Reduction and Climate Change Adaptation) project is illustrated. The IS is described in detail, starting from the stakeholder consultation to elicit the requirements, to the system’s architecture, design and implementation. The IS provides a comprehensive tool to input and query multisectoral post-disaster damage and loss data at relevant spatial and temporal scales. The part of the IS devoted to building damage is described in depth showing how obstacles and difficulties highlighted in the collection and use of data in the Greek and the Italian case have been approached and solved. Finally, further developments of the IS and its background philosophy are discussed, including the need for institutionalized damage data collection, engineering of the developed software and re-engineering of current damage and loss data practices.