The web-based simulation and information service for multi-hazard impact chains. Design document.

The overall objective of the PARATUS project and the platform is the co-development of a web-based simulation and information service for first and second responders and other stakeholders to evaluate the impact chains of multi-hazard events with particular emphasis on cross-border and cascading impacts. This deliverable provides a first impression of the platform and its components. A central theme in the PARATUS project is the co-development of the tools with stakeholders. The central stakeholders within the four applications case studies are therefore full project partners. They will be directly involved in the development of the platform. We foresee that the PARATUS Platform will have two major blocks: an information service that provides static information (or regularly updated information) and simulation service, which is a dynamic component where stakeholders can interactively work with the tools in the platform. The PARATUS will further make sure that documentation (e.g., software accompanying documentation) is also publicly available via the project website1 and other trusted repositories. The deliverable 4.1 was submitted to the European Commission on 31/07/2023 and is waiting for approval by the Research Executive Agency. Therefore, this current version may not represent the final version of the deliverable

Application of a Blockchain Enabled Model in Disaster Aids Supply Network Resilience

The disaster area is a dynamic environment. The bottleneck in distributing the supplies may be from the damaged infrastructure or the unavailability of accurate information about the required amounts. The success of the disaster response network is based on collaboration, coordination, sovereignty, and equality in relief distribution. Therefore, a reliable dynamic communication system is required to facilitate the interactions, enhance the knowledge for the relief operation, prioritize, and coordinate the goods distribution. One of the promising innovative technologies is blockchain technology which enables transparent, secure, and real-time information exchange and automation through smart contracts. This study analyzes the application of blockchain technology on disaster management resilience. The influences of this most promising application on the disaster aid supply network resilience combined with the Internet of Things (IoT) and Dynamic Voltage Frequency Scaling (DVFS) algorithm are explored employing a network-based simulation. The theoretical analysis reveals an advancement in disaster-aids supply network strategies using smart contracts for collaborations. The simulation study indicates an enhance in resilience by improvement in collaboration and communication due to more time-efficient processing for disaster supply management. From the investigations, insights have been derived for researchers in the field and the managers interested in practical implementation

Facility Location Planning in Relief Logistics: Decision Support for German Authorities

Disasters have devastating impacts on societies, affecting millions of people and businesses each year. The delivery of essential goods to beneficiaries in the aftermath of a disaster is one of the main objectives of relief logistics. In this context, selecting suitable locations for three different types of essential facilities is central: warehouses, distribution centers, and points of distribution. The present dissertation aims to improve relief logistics by advancing the location selection process and its core components. Five studies published as companion articles address substantial aspects of relief logistics. Despite the case studies\u27 geographical focus on Germany, valuable insights for relief logistics are derived that could also be applied to other countries. Study A addresses the importance of public-private collaboration in disasters and highlights the significance of considering differences in resources, capabilities, and strategies when using logistical models. Moreover, power differences, information sharing, and partner selection also play an important role. Study B elaborates on the challenges to identify candidate locations for warehouses, which are jointly used by public and private actors, and suggests a methodology to approach the collaborative warehouse selection process. Study C investigates the distribution center selection process and highlights that including decision-makers\u27 preferences in the objective function of location selection models helps to raise awareness of the implications of location decisions and increases transparency for decision-makers and the general population. Study D analyzes the urban water supply in disasters using a combination of emergency wells and mobile water treatment systems. Selected locations of mobile systems change significantly if vulnerable parts of the population are prioritized. Study E highlights the importance of accurate information in disasters and introduces a framework that allows determining the value of accurate information and the planning error due to inaccurate information. In addition to the detailed results of the case studies, four general recommendations for authorities are derived: First, it is essential to collect information before the start of the disaster. Second, training exercises or role-playing simulations with companies will help to ensure that planned collaboration processes can be implemented in practice. Third, targeted adjustments to the German disaster management system can strengthen the country\u27s resilience. Fourth, initiating public debates on strategies to prioritize parts of the population might increase the acceptance of the related decision and the stockpiling of goods for the people who know in advance that they will likely not receive support. The present dissertation provides valuable insights into disaster relief. Therefore, it offers the potential to significantly improve the distribution of goods in the aftermath of future disasters and increase disaster resilience

Interoperability and Information Brokers in Public Safety: An Approach toward Seamless Emergency Communications

When a disaster occurs, the rapid gathering and sharing of crucial information among public safety agencies, emergency response units, and the public can save lives and reduce the scope of the problem; yet, this is seldom achieved. The lack of interoperability hinders effective collaboration across organizational and jurisdictional boundaries. In this article, we propose a general architecture for emergency communications that incorporates (1) an information broker, (2) events and event-driven processes, and (3) interoperability. This general architecture addresses the question of how an information broker can overcome obstacles, breach boundaries for seamless communication, and empower the public to become active participants in emergency communications. Our research is based on qualitative case studies on emergency communications, workshops with public safety agencies, and a comparative analysis of interoperability issues in the European public sector. This article features a conceptual approach toward proposing a way in which public safety agencies can achieve optimal interoperability and thereby enable seamless communication and crowdsourcing in emergency prevention and response

Public-private perspectives on supply chains of essential goods in crisis management

Public authorities are responsible to maintain the population’s supply with essential goods like food or drugs at any time. Such goods are produced, transported and sold by companies in supply chains. Past supply crises all over the world have showcased numerous examples of spontaneous collaboration between public authorities and companies in supply chains. However, insights on formal collaboration which is agreed upon in the preparedness phase is rare in both practice and literature. Therefore, this dissertation’s first research objective is to identify under which circumstances companies are most willing to collaborate with public authorities. In this context, public authorities\u27 and companies\u27 characteristics, resources and roles in a collaboration are identified from literature research as well as real-life cases in Study A. Study B empirically determines companies\u27 preferred preconditions for collaboration: Companies value the continuity of their business processes and expect to be compensated monetarily or by lifted restrictions. The second research objective is to develop collaborative supply chain concepts and evaluate them from public and private perspectives. Study C develops a collaboration concept in a real-time setting in which commercial trucks are jointly re-routed into crisis regions. In Study D, public authorities coordinate tactical use of commercial last-mile delivery vehicles for the home supply with food and drugs. In Study E, strategic collaboration in using dual-use warehouses is investigated with a focus on logistics networks. Study F determines the impact of demand shortfalls and payment term extensions on financial and physical flows in food supply chains. In Studies C-F, the main drivers for effectiveness and efficiency are investigated. By examining collaboration between companies and public authorities in supply crises, this dissertation contributes to the research streams of supply chain risk management and so-called extreme supply chain management. The results provide public decision-makers with insights into companies\u27 motivation to engage in public crisis management. The developed collaborative supply chain concepts serve public authorities as a basis for collaboration design and companies as starting points for integrating public-private collaboration into their endeavors to make supply chains more resilient

Enhancing hospital planning capacity and resilience in crisis scenarios using interpretive structural modeling (ISM)

Hospitals are the critical support infrastructures. In the confrontation with natural disasters, infectious diseases, and other crises that severely affect the supply and demand of local medical services—and even jeopardize the hospital itself—, the hospital needs first to secure the essential emergency functions and, secondly, to recover from the impact as quickly as possible. Hospital resilience has numerous influencing elements and evaluation criteria, but there are still ambiguous boundaries in their internal influence relationships and hierarchical structures. Therefore, this study explores the determinants and pathways of practice for strengthening hospital resilience from an internal management perspective, applying Group Decision Making and Interpretive Structural Modeling (ISM) to pool the knowledge and experience of experts in related fields and identify critical variables. Based on the information collected and analyzed, a hierarchical model of hospital resilience was established. The results and practical applicability of the model were then validated by external experts to provide new knowledge for the development of hospital resilience management.Os hospitais são infraestruturas críticas. No confronto com desastres naturais, doenças infeciosas ou outras crises que afetem gravemente a oferta e a procura de serviços médicos locais—e que até põem em risco o próprio hospital—, o hospital precisa, em primeiro lugar, de assegurar as funções essenciais de emergência e, em segundo lugar, de recuperar desses impactos o mais rapidamente possível. A resiliência do hospital tem numerosos elementos de influência e critérios de avaliação, mas existem ainda fronteiras ambíguas nas suas relações de influência interna e nas suas estruturas hierárquicas. Neste contexto, o presente estudo explora determinantes e práticas para reforçar a resiliência hospitalar a partir de uma perspetiva de gestão interna, aplicando métodos de tomada de decisão de grupo e Interpretive Structural Modeling (ISM) para reunir o conhecimento e a experiência de especialistas em áreas relacionadas e identificar variáveis críticas. Com base na informação recolhida, foi estabelecido um modelo hierárquico de resiliência hospitalar. Os resultados e a aplicabilidade prática do modelo foram validados por peritos externos, no sentido de fornecer novos conhecimentos para o desenvolvimento da gestão da resiliência hospitalar

Assessing vulnerability and modelling assistance: using demographic indicators of vulnerability and agent-based modelling to explore emergency flooding relief response

Flooding is a significant concern for much of the UK and is recognised as a primary threat by most local councils. Those in society most often deemed vulnerable: the elderly, poor or sick, for example, often see their level of vulnerability increase during hazard events. A greater knowledge of the spatial distribution of vulnerability within communities is key to understanding how a population may be impacted by a hazard event. Vulnerability indices are regularly used – in conjunction with needs assessments and on-the-ground research – to target service provision and justify resource allocation. Past work on measuring and mapping vulnerability has been limited by a focus on income-related indicators, a lack of consideration of accessibility, and the reliance on proprietary data. The Open Source Vulnerability Index (OSVI) encompasses an extensive range of vulnerability indicators supported by the wider literature and expert validation and provides data at a sufficiently fine resolution that can identify vulnerable populations. Findings of the OSVI demonstrate the potential cascading impact of a flood hazard as it impacts an already vulnerable population: exacerbating pre-existing vulnerabilities, limiting capabilities and restricting accessibility and access to key services. The OSVI feeds into an agent-based model (ABM) that explores the capacity of the British Red Cross (BRC) to distribute relief during flood emergencies using strategies based upon the OSVI. A participatory modelling approach was utilised whereby the BRC were included in all aspects of the model development. The major contribution of this work is the novel synthesis of demographics analysis, vulnerability mapping and geospatial simulation. The project contributes to the growing understanding of vulnerability and response management within the NGO sector. It is hoped that the index and model produced will allow responder organisations to run simulations of similar emergency events and adjust strategic response plans accordingly

Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty : A System Design Approach

With respect to copyright, all the papers were excluded from the dissertation.Disasters threaten society with widespread destruction of infrastructure and livelihood. For their survival, affected inhabitants depend on immediate humanitarian assistance from diverse organizations. During quick responses, humanitarian decision- makers (HDMs) act rapidly to distribute necessary relief goods, despite the deep, prevailing uncertainty that arises from scarce, conflicting, and uncertain information. To support HDMs in humanitarian relief distribution (HRD) decision-making, humanitarian logistics (HL) researchers have developed various mathematical models. These models are, however, specific to disaster scenarios, and most of them are detached from the realities of the field since end-users (mainly practitioners) have been absent in the development process. When tested, these decision-making models were found to be capable of producing good results, but they have not been implemented in practice because of operational inconsistency or complexity (i.e., lack of user-friendliness). Therefore, humanitarian responders are still in need of support systems to assist them in determining effective HRD. A computer-based decision support system (DSS) can fill this need by providing necessary recommendations and suggesting decision alternatives. Hence, developing such DSSs is always the priority in HL.publishedVersio

Adaptive Pathways Using Emerging Technologies: Applications for Critical Transportation Infrastructure

Hazards are becoming more frequent and disturbing the built environment; this issue underpins the emergence of resilience-based engineering. Adaptive pathways (APs) were recently introduced to help flexible and dynamic decision making and adaptive management. Especially under the climate change challenge, APs can account for stressors occurring incrementally or cumulatively and for amplified-hazard scenarios. Continuous records from structural health monitoring (SHM) paired with emerging technologies such as machine learning and artificial intelligence can increase the reliability of measurements and predictions. Thus, emerging technologies can play a crucial role in developing APs through the lifetimes of critical infrastructure. This article contributes to the state of the art by the following four ameliorations. First, the APs are applied to the critical transportation infrastructure (CTI) for the first time. Second, an enhanced and smart AP framework for CTI is proposed; this benefits from the resilience and sustainability of emerging technologies to reduce uncertainties. Third, this innovative framework is assisted by continuous infrastructure performance assessment, which relies on continuous monitoring and mitigation measures that are implemented when needed. Next, it explores the impact of emerging technologies on structural health monitoring (SHM) and their role in enhancing resilience and adaptation by providing updated information. It also demonstrates the flexibility of monitoring systems in evolving conditions and the employment of AI techniques to manage pathways. Finally, the framework is applied to the Hollandse bridge, considering climate-change risks. The study delves into the performance, mitigation measures, and lessons learned during the life cycle of the asset