Risk Management in a Disaster Management Context

This paper discusses how the adoption of a systematic risk management framework can enhance disaster management. In the analysis of risk, a focus on the interactions between sources of risk and elements at risk, rather than a pre-occupation with hazards, adds more value to management. Vulnerability is the crucial modifier of consequences and, as such, its analysis highlights critical areas and opportunities for developing effective intervention strategies. Risk communication processes based on community involvement need to underpin the development and application of evaluation criteria to determine which risk treatments will be implemented. Closing considerations reflect on how risk management may be used within public administration to re-define emergency management service provision. The paper concludes that Emergency Risk Management provides a framework which, by focusing on managing community exposure to major risks, facilitates the identification and implementation of intervention options which address socially significant problems.     

Participation Patterns and Reliability of Human Sensing in Crowd-Sourced Disaster Management

Over the last ten years, there has been a significant increase in crowd-sourcing applications for disaster management. Their success depends heavily on the behaviour of social media users, acting as human sensors during disaster monitoring and emergency response. Unlike their technological counterparts, human sensors are complex social entities, contributing in different ways to their collective task and creating varying participation patterns through social media. Failing to understand these participation patterns limits our capacity to evaluate the reliability of human sensing in different contexts. Based on an analysis of flood-related information contributed by Twitter users in Jakarta during the 2014/2015 and 2015/2016 monsoonal seasons, this study establishes four categories of human sensors and their respective levels of reliability for disaster management. The results have significant implications for how we frame expectations and develop reliance on the use of social media for disaster management. Importantly, the results will serve as a useful guide for understanding levels of incentive that may be required to motivate members of the different categories of social media users during emergencies and disasters.     

Modeling pedestrian mobility in disaster areas

Realistic mobility modeling is necessary for testing disaster management strategies as well as performance of disaster–resilient networks. Evacuation of the people from a disaster area depends on the environment and type of the hazard which cause certain changes in the pedestrian flows. Although most models focus on the building evacuations or city-scale evacuation planning, there is a need for a mobility model that captures the pedestrians’ movement behavior during evacuation from large and crowded disaster areas such as theme parks.In this paper, we propose a mobility model of the pedestrians in disaster areas. In our application scenario of theme parks, the main mission of the operators is the evacuation of the visitors and providing access to transportation vehicles such as ambulances. We use real maps to generate theme park models with obstacles, roads, and disaster events. We incorporate macro and micro mobility decisions of the visitors, considering their local knowledge and the social interactions among the visitors. We analyze the outcomes of the simulation of our theme park disaster (TP-D) mobility model with simulations of currently used models and real-world GPS traces. Moreover, using the proposed model as a baseline, we analyze the performance of an opportunistic network application.     

Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches

Choosing the locations of disaster response facilities for the storage of emergency supplies is critical to the quality of service provided post-occurrence of a large scale emergency like an earthquake. In this paper, we provide two location models that explicitly take into consideration the impact a disaster can have on the disaster response facilities and the population centers in surrounding areas. The first model is a deterministic model that incorporates distance-dependent damages to disaster response facilities and population centers. The second model is a stochastic programming model that extends the first by directly considering the damage intensity as a random variable. For this second model we also develop a novel solution method based on Benders Decomposition that is generalizable to other 2-stage stochastic programming problems. We provide a detailed case study using large-scale emergencies caused by an earthquake in California to demonstrate the performance of these new models. We find that the locations suggested by the stochastic model in this paper significantly reduce the expected cost of providing supplies when one considers the damage a disaster causes to the disaster response facilities and areas near it. We also demonstrate that the cost advantage of the stochastic model over the deterministic model is especially large when only a few facilities can be placed. Thus, the value of the stochastic model is particularly great in realistic, budget-constrained situations.     

A risk management tool for tackling country-wide contingent disasters: A case study on Madagascar

Governments are key players in managing disaster risks, and fiscal risk management has become an integral part of disaster risk management. However, the ability of governments to implement disaster risk management strategies differs significantly across countries, depending on their capacity and resource constraints. The CatSim model and its most recent version presented in this paper helps to fill part of the information gap regarding the capacity and resources of a government to deal with natural disaster risk. We provide an in-depth example how the model works for the case of managing cyclone risk in Madagascar. In doing so, we provide recommendations as to how some of the more difficult concepts from the disaster risk theory and modelling field can be most easily understood by non-technically trained stakeholders. Such understanding is beneficial in facilitating consensus-building among various risk bearers from different sectors regarding options for managing risk.     

Lobbying and emergency management in the United States: Issues,priorities and implications

Recent scholarship has explored the impact of interest groups on policy in the United States. However, little remains known about lobbying efforts and their effects in emergency management. Through analysis of a large data set of declared political activities from 1999 to 2020, we describe lobbying efforts in disaster planning and emergencies. Our findings suggest that lobbying efforts and expenditure are positively associated with appropriations (but not disaster incidence or severity), that corporations and trade associations are the organizations most involved in lobbying and that many of these efforts appear to be aimed at impacting legislation and the procurement of public funds for recovery efforts. We also find that only a minuscule number of lobbying efforts are related to socially vulnerable populations or social equity concerns. Collectively, these insights raise important questions about this process, demonstrating the need for further research to better understand lobbying and emergency management in the United States across all phases of the disaster life cycle.     

省级统筹社会保险信息系统建设与技术探讨

全国有2000多个社会保险基金统筹单位,统筹层次低带来诸多社会问题。以大整合、大集中、大统一的省级统筹将在这几年施行。探讨了基于省级统筹的社会保险信息系统建设的几种模式,探讨网络及软硬件平台,以及系统风险、数据安全、异地容灾等技术问题。     

Spatial biases in crowdsourced data: Social media content attention concentrates on populous areas in disasters

The objective of this study is to examine and quantify the relationships among sociodemographic factors, damage claims, and social media attention on areas during natural disasters. Social media has become an important communication channel for people to share and seek situational information to learn of risks, to cope with community disruptions, and to support disaster response. Recent studies in disaster informatics have recognized the presence of bias in the representation of social media activity in areas affected by disasters. To explore related factors for such bias, existing studies have used geo-tagged tweets to assess the extent of social media activity in disaster-affected areas to evaluate whether vulnerable populations remain silent on social media. However, less than 1% of all tweets are actually geo-tagged; therefore, attempts to understand the representativeness of geotagged tweets to the general population have shown that certain populations are over- or underrepresented. To address this limitation, this study examined the attention given to locations based on social media content. The study conducted a content-based analysis to filter tweets related to 84 super-neighborhoods in Houston during Hurricane Harvey and 57 cities in North Carolina during Hurricane Florence. By examining the relationships among sociodemographic factors, the number of damage claims, and the volume of tweets, the results showed that social media attention concentrates in populous areas, independent of education, language, unemployment, and median income. The relationship between population and social media attention is characterized by a sub-linear power law, indicating a large variation among the sparsely populated areas. Using a machine-learning model to label the topics of the tweets, the results showed that social media users pay more attention to rescue- and donation-related information; nevertheless, the topic variation is consistent across areas with different levels of attention. These findings contribute to a better understanding of the spatial concentration of social media attention regarding posting and spreading situational information in disasters. The findings could inform emergency managers and public officials to effectively use social media data for equitable resource allocation and action prioritization.     

Using SDI and web-based system to facilitate disaster management

Spatial data and related technologies have proven to be crucial for effective collaborative decision-making in disaster management. However, there are currently substantial problems with availability, access and usage of reliable, up-to-date and accurate data for disaster management. This is a very important aspect to disaster response as timely, up-to-date and accurate spatial data describing the current situation is paramount to successfully responding to an emergency. This includes information about available resources, access to roads and damaged areas, required resources and required disaster response operations that should be available and accessible for use in a short period of time. Any problem or delay in data collection, access, usage and dissemination has negative impacts on the quality of decision-making and hence the quality of disaster response. Therefore, it is necessary to utilize appropriate frameworks and technologies to resolve current spatial data problems for disaster management.This paper aims to address the role of Spatial Data Infrastructure (SDI) as a framework for the development of a web-based system as a tool for facilitating disaster management by resolving current problems with spatial data. It is argued that the design and implementation of an SDI model and consideration of SDI development factors and issues, together with development of a web-based GIS, can assist disaster management agencies to improve the quality of their decision-making and increase efficiency and effectiveness in all levels of disaster management activities.The paper is based on an ongoing research project on the development of an SDI conceptual model and a prototype web-based system which can facilitate sharing, access and usage of spatial data in disaster management, particularly disaster response.     

Social workflows—Vision and potential study

Social workflows pervade peoples׳ everyday life. Whenever a group of persons works together on a challenging or multifaceted task, a social workflow begins. Unlike traditional business workflows, such social workflows aim at supporting processes that contain personal tasks and data. In this work, we envision a social workflow service as part of a social network that enables private individuals to construct social workflows according to their specific needs and to keep track of the workflow execution. The proposed features for a social workflow service could help individuals to accomplish their private goals. The presented idea is contrasted with established research areas and applications to show the degree of novelty of this work. It is shown how novel ideas for knowledge management, facilitated by a process-oriented case-based reasoning approach, support private individuals and how they can obtain an appropriate social workflow through sharing and reuse of respective experience. Two empirical studies confirm the potential benefits of a social workflow service in general and the core features of the developed concept.     

Ambulance routing for disaster response with patient groups

We consider a routing problem for ambulances in a disaster response scenario, in which a large number of injured people require medical aid at the same time. The ambulances are used to carry medical personnel and patients. We distinguish two groups of patients: slightly injured people who can be assisted directly in the field, and seriously injured people who have to be brought to hospitals. Since ambulances represent a scarce resource in disaster situations, their efficient usage is of the utmost importance. Two mathematical formulations are proposed to obtain route plans that minimize the latest service completion time among the people waiting for help. Since disaster response calls for high-quality solutions within seconds, we also propose a large neighborhood search metaheuristic. This solution approach can be applied at high frequency to cope with the dynamics and uncertainties in a disaster situation. Our experiments show that the metaheuristic produces high quality solutions for a large number of test instances within very short response time. Hence, it fulfills the criteria for applicability in a disaster situation. Within the experiments, we also analyzed the effect of various structural parameters of a problem, like the number of ambulances, hospitals, and the type of patients, on both running time of the heuristic and quality of the solutions. This information can additionally be used to determine the required fleet size and hospital capacities in a disaster situation.     

Move out or dig in? Risk awareness and mobility plans in disaster‐affected communities

Post‐disaster migration patterns have been thoroughly studied from a demographic standpoint, but affected community residents’ perceptions of ongoing risks and their willingness to remain in an affected community remain under‐researched. Using data generated by 407 surveys and 40 interviews with residents impacted by the 2013 Calgary flood, this study analyses the effects of flood experience on residents’ worry about future floods and their ensuing short‐term and medium‐term mobility plans. The results indicate that home flooding and evacuation orders are both predictive of worry about future floods. In turn, worry about future floods as well as age, homeownership, and place attachment are all predictive of post‐disaster mobility plans. Residents discuss how the flood either strengthened or weakened their place attachment. The paper concludes by discussing the implications for social science research and for public policy that aims to mitigate disaster risk.     

面向受灾差异的跨区域应急救援路径优化

关注各灾区待救人员的不同受伤程度,用“伤员在途可坚持时间”的区别来表征差异化受灾情形,研究带有时间窗限制、基于受灾差异的跨区域应急救援路径优化问题.构建以最小化救援车辆行车总时间为决策目标的车辆路径模型,设计蚁群算法对仿真算例进行求解.讨论考虑受灾差异因素对整个跨区域救援路径优化方案的影响,并对以决策者风险态度为例的关键参数实施敏感性分析.研究结果可为构建高效的应急管理体系提供有益参考.     

Serving the Public Interest in a Crisis: Does Local Radio Meet the Public Interest?

During a crisis, radio stations frequently operate in the public interest, disseminating critical information the public needs. Past research offers that stations in smaller markets may be better prepared for crises and more willing to serve the public under such circumstances. These postulates were empirically tested in the context of a specific natural disaster. A survey of 124 radio stations in areas directly impacted by the 2008 Midwest flooding largely supports these assertions. The results indicate that while radio stations in a disaster‐prone region may be more cognizant of their responsibilities to the public than those in more stable locations, these stations are often reluctant to coordinate with public officials. Further, stations in larger markets tended to perceive less civic responsibility than those in smaller markets, consistent with previous research. This lends further support to a disturbing argument – that radio stations who reach the greatest number of people may be both unwilling and unable to effectively communicate with the public during times of crisis and disaster.     

Towards a lightweight framework for service management evaluation in SMEs

Small and Medium-sized Enterprises (SMEs) are currently immersed in Volatility, Uncertainty, Complexity and Ambiguity (VUCA) environments and need to adapt and innovate both their services and their management practices and processes. Unfortunately, models and standards for service management are focused on large organisations, therefore, their application in SMEs is expensive and, generally, unfeasible. In order to contribute to the sustained success and development of SMEs, this paper presents a framework for service management evaluation. The objective of this framework, which is based on international standards and the main models for service management, is to be a roadmap containing well-defined and formalised processes that helps SMEs to improve the quality of their customer services. The proposal is validated in this work by means of its application to a real case study.

     

汶川地震大型单体滑坡遥感调查与危险性评价

＂5.12＂汶川特大地震诱发了大量次生地质灾害,山体大面积滑坡、崩塌,给人民的生命财产造成了重大损失。对这些次生性灾害进行详细的调查与监测,评价其近期的稳定性,对于防灾减灾,指导灾后重建具有现实意义。本文探讨了利用遥感影像对大型滑坡进行识别与解译,并运用AHP层次分析法对汶川地震形成的文家坝大型滑坡进行危险性评价的方法。在野外调查的基础上,对2008年5月16日获取的SPOT5影像进行解译,实现了对滑坡的规模、结构、类型、物质组成、稳定性等特征的遥感调查;选取与该滑坡发生有密切关联的地层岩性、坡度、区域降雨量、地震和水文条件5个因素作为滑坡危险性评价的指标,采用比例标度法构建判别矩阵,建立了滑坡危险度判别模型。经计算,文家坝滑坡危险性指数为0.684,危险度较高,有必要进行工程治理。     

Risk assessment in work environments: modeling and simulation

The paper proposes a characterization of risks and a service‐oriented prototype to face risky situations in work environments, such as in industrial plants or building construction areas. A risk is the overture of emergencies that produce human and/or material damages. Therefore, it is particularly critical to identify and manage risks to avoid their evolution into emergencies. In this paper, we outline the technological features of a risk environment and propose a risk model and a service‐based simulation prototype aimed to improve safety in work environments. We discuss engineering issues concerning risk modeling and management. Furthermore, we propose a risk management system solution and its related implemented prototype composed of services able to detect and also to prevent the occurrence of risk conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Crowdsourcing roles,methods and tools for data-intensive disaster management

Mobile technologies, web-based platforms, and social media have transformed the landscape of disaster management by enabling a new generation of digital networks to produce, process, and analyse georeferenced data in real time. This unprecedented convergence of geomobile technologies and crowdsourcing methods is opening up multiple forms to participate in disaster management tasks. Based on empirical research, this paper first proposes a conceptualisation of crowdsourcing roles and then analyses methods and tools based on a combination of two variables: (i) types of data being processed; (ii) involvement of the crowds. The paper also surveys a number of existing platforms and mobile apps leveraging crowdsourcing in disaster and emergency management with the aim to contribute to the discussion on the advantages and limits of using crowdsourcing methods and tools in these areas.     

Disincentives for communicating risk: a risk paradox

Problems with the risk management in medium to large software projects have been well documented. For major software projects to be completed successfully, an open and cooperative attitude towards risk must be maintained. Despite this significant incentive, project stakeholders frequently conceal risks. This article identifies reasons in three key areas for such behaviour, and suggests approaches that reduce the motivation for this behaviour thereby providing a basis for effective risk management. Examples drawn from a study, undertaken by the authors, of a medium-sized industry project are used to illustrate many of these issues.     

Human error risk management methodology for safety audit of a large railway organisation

This paper considers the application of the human error risk management for engineering systems (HERMES) methodology for safety assessment studies. The application concerns the recurrent safety audits (RSA) of a large organisation in the domain of railway transportation systems. The objective of the study was the identification of the most relevant areas of intervention for improving safety and reliability of the service.

The methodology has been applied to the whole organisation and its working processes. Specific attention was paid to train drivers. A number of critical indicators of safety and recurrent safety audit matrices were identified, which enabled the assessment of the safety level of the organisation and the generation of safety recommendations.

The application of HERMES to this case study shows that the methodology is applicable in practice and can give valuable and significant results.