The importance of a common understanding in emergency management

An emergency situation brings together individuals belonging to many different organizations, representing different organizational cultures including different usage of language. In this paper we propose that a common understanding is vital in managing emergency situations. Firstly, a simple emergency situation is presented where one of the causes for increased damage was simply due to a misunderstanding of language. Secondly, we propose a theoretical framework of how different organization cultures with their different uses of language can be integrated on the terminological level where the communication takes place. Thirdly, the presented example is reviewed. We show how situations such as the one in our example can be analyzed by means of the theoretical framework. Finally, we present the findings from a Delphi study conducted in Finland, which support the central thesis, i.e. the importance of a common understanding in emergency situations, and we propose using the Delphi method to find the critical domains in the flow of information between the different actors involved in disaster management.     

Humanistic and economic impacts of hepatitis C infection in the United States

Abstract

Objective:

Prior research examining the effect of hepatitis C virus (HCV) on health-related quality of life (HRQoL) and healthcare costs is flawed because non-patient controls were not adequately comparable to HCV patients. The current study uses a propensity score matching methodology to address the following research question: is the presence of diagnosed hepatitis C (HCV) associated with poorer health-related quality of life (HRQoL) and greater healthcare resource use?

Methods:

Using data from the 2009 US National Health and Wellness Survey, patients who reported a HCV diagnosis (n?=?695) were compared to propensity-matched controls (n?=?695) on measures of HRQoL and healthcare resource use. All analyses applied sampling weights to project to the US population.

Results:

HCV patients reported significantly lower levels of HRQoL relative to the matched-control group, including the physical component score (39.6 vs. 42.7, p?<?0.0001) and health utilities (0.63 vs. 0.66, p?<?0.0001). The number of emergency room visits (0.59 vs. 0.44, p?<?0.05) and physician visits (7.7 vs. 5.9, p?<?0.05) in the past 6 months were significantly higher for the HCV group relative to matched controls.

Conclusion:

The results of this study suggest that HCV represents a substantial burden on patients by having a significant and clinically-relevant impact on key dimensions of HRQoL as well as on utilization of healthcare resources, the latter of which would result in increased direct medical costs.

Limitations:

Due to limitations of the internet survey approach (e.g., inability to confirm HCV diagnosis), future research is needed to confirm these findings.     

A multi-stage stochastic programming approach for pre-positioning of relief supplies considering returns

A dynamic pre-positioning problem is proposed to efficiently respond to victims’ need for relief supplies under uncertain and dynamic demand in humanitarian relief. The problem is formulated as a multi-stage stochastic programming model that considers pre-positioning with the dynamic procurement and return decisions about relief supplies over a time horizon. To validate the advantages of dynamic pre-positioning, three additional pre-positioning strategies are presented: pre-positioning with one-time procurement and without returns, pre-positioning with one-time procurement and returns, and pre-positioning with dynamic procurement and without returns. Using data from real-world disasters in the United States in the Emergency Events Database, we present a numerical analysis to study the applicability of the proposed models. We develop a sample average approximation approach to solving the proposed model in large-scale cases. Our main contribution is that we integrate dynamic procurement and return strategies into pre-positioning to decrease both costs and shortage risks in uncertain and dynamic contexts. The results illustrate that dynamic pre-positioning outperforms the other three strategies in cost savings. It also indicates that a higher return price is particularly helpful for decreasing unmet demand. The proposed models can help relief agencies evaluate and choose the solutions that will have the greatest overall effectiveness in the context of different relief practices.     

大型铁路客运枢纽设施应急能力匹配度研究

借鉴国内外学者在大型铁路客运枢纽的设施应急能力方面的研究成果,从应急能力与需求匹配度、节点设施匹配度、疏散流线匹配度3个方面,对大型铁路客运枢纽设施应急能力的匹配度进行研究,阐述应急能力与需求匹配度、节点设施匹配度和疏散流线匹配度的概念与测度方法。在此基础上,建立优化模型,在满足疏散流线安全时间的要求下,使大型铁路客运枢纽设施整体协调匹配。     

Surviving organizational disasters

Man-made and natural disasters are becoming increasingly common in today's world. Among other entities, companies should be concerned because these impact organizational survival, disrupting the lives and functioning of employees, suppliers, customers, and organizational infrastructure. If the present trend continues, the Federal Emergency Management Agency is on track to declare 30% more disasters in 2010 than in 2009. Organizational disasters are crises in the extreme. While the crisis management literature provides a useful foundation for planning for internal organizational threats, it does not adequately address larger external threats brought about by disasters. With this gap in mind, we herein present a framework for planning for man-made or natural disasters: continuity of operations planning (COOP). Continuity of operations planning is a tool that aids organizations in staying in business under extreme circumstances. Although continuity of operations planning is not an entirely new practice, many small and medium-sized firms are reluctant to engage in this type of planning. To highlight the value of the process, this article provides examples of organizational disasters, alongside a simplified method for developing an effective continuity of operations plan.     

新西兰地震应急管理给我国的借鉴

地震作为自然灾害的一种,从古至今不可避免的发生着,不断的给人类的生活造成损害。因为地震是不可预测的自然运动。这往往带来的灾害是毁灭性的。人类在地震面前能做的微乎其微,但是,如何完善应对机制能决定着人类在地震面前能挽回多少损失,挽回多少生命。     

A minimum expected response model: Formulation, heuristic solution, and application

Responding to true emergencies in the shortest possible time saves lives, prevents permanent injuries and reduces suffering. Most covering models consider an emergency cover if an ambulance is available within a given time or distance threshold. From a modeling perspective, shorter or longer responses within this threshold are all tallied as covered; conversely, the emergencies immediately outside the threshold are considered uncovered. However, if the shorter responses are given more weight along with the volume of such incidents, while still meeting system-wide coverage requirements, both customers and providers can benefit from reduced response times. We formulate a model to determine the locations for a given set of ambulances to minimize the system-wide expected response distances while meeting coverage requirements. We solve the model with a heuristic search algorithm and present computational and comparative statistics using data from an existing Emergency Medical Services agency.     

突发事件对我国铁路客运量的干预特征研究

基于新冠肺炎疫情等突发事件对人们日常生活出行的影响,结合X-13ARIMASEATS季节调整模型的自动识别最优ARIMA模型和检测突发事件离群值功能,使用脉冲函数和阶梯函数设计基于离群值的突发事件的干预变量,构建铁路客运量的时间序列ARIMAX干预模型,对铁路客运量近年受到的SARS疫情、铁路客票实名制政策和新冠肺炎疫情等突发事件的冲击趋势进行干预比较分析。结果显示,SARS和新冠肺炎疫情对铁路客运量冲击较大,SARS疫情在冲击滞后的第5~6期铁路客运量基本得到恢复,新冠肺炎疫情对铁路客运量冲击一直在持续中,铁路客运实名制政策实施社会性较强,冲击具有波动性和不稳定性特征,持续时间较短;相对季节调整模型的趋势分析优势,干预模型拟合预测精度显著高于季节调整模型,预测显示我国铁路客运量在缓慢持续回暖中。     

突发事件下应急救援服务供应链的协同优化研究

本文注重结合应急救援服务供应链和应急管理的特点,基于协同网络和服务供应链各方找出其中的规律进行分析;并依据应急救援服务供应链各方之间利润需求和协同努力程度及协同关系的不同,提出了应急救援服务供应链协同优化模型的基本设计思路;通过构建应急救援服务供应链协同优化模型和数值分析,得出其服务运作协同的最终目的是在合理的集成运作成本条件下,快速响应突发事件下的需求者,最大限度地满足应急服务需求,从而实现应急救援服务供应链整体效益的最大化.     

民用建筑电气消防设计常见问题研究

根据现行的有关强制性国家标准、规范的规定,建筑电气消防设计中常见的几个问题,诸如:有关规范、标准不会应用,概念模糊、条理不清,消防规范中有许多条款规定得不详细,在执行规范时有许多的疑惑,系统图与平面图不一致,有漏项,设计很不完善等等。必须寻求解决办法,才能有效地保证建筑物和人民生命财产安全。