Emergency Response Facilities Research Articles

Experience Sharing in Participating in the Environmental Safety Consultation Program—Tainan Hospital, Ministry of Health and Welfare

<p>本文分享財團法人醫院評鑑暨醫療品質策進會推動「環境安全諮詢計畫」，由兩位國內專家輔導委員及一位國外ACHSI輔導委員以緊急應變計畫、建築與設備、管理機制三大方面進入輔導過程，本文大致分享以國內醫療機構面臨機構建築設備老舊維護困難，在既有建築物空間規劃設計上，防災及疏散因應措施相較薄弱，如何以合宜的因應措施及編列合理改善預算，提升環境安全及災害應變能力，保障人員安全與健康，維持醫療正常營運及財產損害控管。</p> <p> </p><p>This manuscript shares the experience of participating in the “Environmental Safety Consultation Program” promoted by the Joint Commission of Taiwan. The program was guided by two domestic expert advisors and one international advisor from the Australian Council on Healthcare Standards International, focusing on three major aspects: emergency response plans, architecture and facilities, and management mechanisms. This manuscript broadly discusses how healthcare institutions in Taiwan, facing challenges with the maintenance of outdated buildings and facilities, and weak disaster prevention and evacuation measures due to existing architectural and spatial planning, can implement suitable response measures and allocate reasonable budgets for improvements. The goals are to enhance environmental safety and disaster response capabilities, ensure the safety and health of personnel, maintain normal medical operations, and manage property damage.</p> <p> </p>

Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure

In this study, we address a dynamic network design problem pertaining to the distribution of essential supplies during the post-disaster response phase. We present a two-stage, stochastic multi-period model that minimizes both expected unmet demand and costs associated with operating emergency response facilities and distributing relief supplies, taking into account evolving road conditions as well as the closure and relocation of temporary relief facilities. To address the computational intractability inherent in large-scale mixed-integer linear programming (MILP), we implement an accelerated branch-and-Benders-cut algorithm, facilitating efficient problem-solving processes. We validate this approach through extensive numerical analysis and its application to a real-world scenario, demonstrating its superiority over deterministic methods, especially when considering the trade-off between nominal operational costs and out-of-sample reliability. Results show that dynamically adjusting the number of operating facilities and their locations may enhance cost efficiency while decreasing unmet demand during the relief delivery process as the transportation network changes with time. Additionally, we show that utilizing stochastic models for decision-making can substantially hedge against demand uncertainty, both in meeting demand and reducing operational costs. However, the benefits of stochastic solutions diminish as the disruption rate increases.

A mixed integer programming approach to improve oil spill response resource allocation in the Canadian arctic

Determining proper locations to establish emergency response facilities is a critical strategic element of pollution preparedness and response planning for oil spills in remote areas. Many location-allocation models are available in the literature, but Arctic contexts such as remoteness and environmental sensitivities are still inadequately investigated while building optimization models. A Mixed Integer Programming (MIP) based optimization model is developed to devise a location-allocation problem: maximizing weighted spill coverage considering spill size, environmental sensitivity, and response time. Strategic decisions - e.g. allocation of stockpiling resources to resource stations and which response stations to open - are incorporated into the model as decision variables. Input parameters of the model are estimated using numerical and geospatial data of potential oil spills and response stations. The model is illustrated for hypothetical oil spill scenarios in the Canadian Arctic. The model provides optimal allocation of resources and recommends best-suited locations to build response facilities. Data visualization tools including Network Diagrams and sensitivity analysis on different model configurations, show the adequacy of the proposed mathematical modelling approach to solve the given problem. Multiple facility locations have been compared to cover all possible oil spills along Arctic shipping routes, further revealing a few better locations considering realistic constraints. Decision makers can use such optimization modelling information – e.g., how many stations to build in the Arctic to adequately cover potential oil spills – to aid strategic decision-making of maritime shipping.

Implementation of Emergency Response System in Elementary School as an Effort to Increase Safety Culture from an Early Age

Children are included in a vulnerable group that must be protected, both from the threat of natural disasters, non-natural disasters or social disasters. School is a place for children to spend a lot of time. Disaster events can occur anywhere and at any time, including at school and during school hours, so schools must have an adequate emergency response system to ensure the safety of all its citizens. The purpose of this study is to identify problems that exist in schools related to the implementation of the disaster response system and formulate indicators for the initiation of initial activities for implementing the emergency response system in elementary school. The research design uses a qualitative descriptive research. The results of identifying problems in Elementary School Y show that school has not implemented an emergency response and disaster mitigation system, but teachers' knowledge regarding multi-hazard mitigation is also still low. The conclusions obtained are that schools can apply initial activity initiation indicators for the implementation of an emergency response system including: preparation of an emergency response team complete with duties and roles, preparation of SOPs for emergency response at school, training and simulation of disaster mitigation, preparation of evacuation maps, installation of evacuation directions, determination gathering points, emergency response signs, installation of emergency response facilities at least Light Fire Extinguishers/APAR and instructions for their use, as well as developing a network of cooperation with related parties.

Design of humanitarian supply chain system by applying the general two-stage network DEA model

PurposeThe recent COVID-19 outbreak and severe natural disasters make the design of the humanitarian supply chain network (HSCN) a crucial strategic issue in a pre-disaster scenario. The HSCN design problem deals with the location/allocation of emergency response facilities (ERFs). This paper aims to propose and demonstrate how to design an efficient HSCN configuration under the risk of ERF disruptions.Design/methodology/approachThis paper considers four performance measures simultaneously for the HSCN design by formulating a weighted goal programming (WGP) model. Solving the WGP model with different weight values assigned to each performance measure generates various HSCN configurations. This paper transforms a single-stage network into a general two-stage network, treating each HSCN configuration as a decision-making unit with two inputs and two outputs. Then a two-stage network data envelopment analysis (DEA) approach is applied to evaluate the HSCN schemes for consistently identifying the most efficient network configurations.FindingsAmong various network configurations generated by the WGP, the single-stage DEA model does not consistently identify the top-ranked HSCN schemes. In contrast, the proposed transformation approach identifies efficient HSCN configurations more consistently than the single-stage DEA model. A case study demonstrates that the proposed transformation method could provide a more robust and consistent evaluation for designing efficient HSCN systems. The proposed approach can be an essential tool for federal and local disaster response officials to plan a strategic design of HSCN.Originality/valueThis study presents how to transform a single-stage process into a two-stage network process to apply the general two-stage network DEA model for evaluating various HSCN configurations. The proposed transformation procedure could be extended for designing some supply chain systems with conflicting performance metrics more effectively and efficiently.

Resilience Assessment for the Northern Sea Route Based on a Fuzzy Bayesian Network

The safety level of the northern sea route (NSR) is a common concern for the related stakeholders. To address the risks triggered by disruptions initiating from the harsh environment and human factors, a comprehensive framework is proposed based on the perspective of resilience. Notably, the resilience of NSR is decomposed into three capacities, namely, the absorptive capacity, adaptive capacity, and restorative capacity. Moreover, the disruptions to the resilience are identified. Then, a Bayesian network (BN) model is established to quantify resilience, and the prior probabilities of parent nodes and conditional probability table for the network are obtained by fuzzy theory and expert elicitation. Finally, the developed Bayesian networkBN model is simulated to analyze the resilience level of the NSR by back propagation, sensitivity analysis, and information entropy analysis. The general interpretation of these analyses indicates that the emergency response, ice-breaking capacity, and rescue and anti-pollution facilities are the critical factors that contribute to the resilience of the NSR. Good knowledge of the absorptive capacity is the most effective way to reduce the uncertainty of NSR resilience. The present study provides a resilience perspective to understand the safety issues associated with the NSR, which can be seen as the main innovation of this work.

Emergency response facility location in transportation networks: A literature review

Emergency response activity relies on transportation networks. Emergency facility location interacts with transportation networks clearly. This review is aimed to provide a combined framework for emergency facility location in transportation networks. The article reveals emergency response activities research clusters, issues, and objectives according to keywords co-occurrence analysis. Four classes of spatial separation models in transportation networks, including distance, routing, accessibility, and travel time are introduced. The stochastic and time-dependent characteristics of travel time are described. Travel time estimation and prediction method, travel time under emergency vehicle preemption, transportation network equilibrium method, and travel time in degradable networks are demonstrated. The emergency facilities location models interact with transportation networks, involving location-routing model, location models embedded with accessibility, location models embedded with travel time, and location models employing mathematical program with equilibrium constraints are reviewed. We then point out the-state-of-art challenges: ilities-oriented, evolution landscape and sequential decision modelling, data-driven optimization approach, and machine learning-based algorithms. • Emergency response facility location problem in transportation networks is reviewed for taxonomy purpose. • Travel time estimation and forecast methods in various scenarios are summarized. • Emergency facility location models in transportation networks are summarized and categorized. • Ilities-oriented, sequential decision modeling, data-driven optimization, and machine learning algorithm are to be studied.

An integer L-shaped algorithm for the integrated location and network restoration problem in disaster relief

Being prepared for potential disaster scenarios enables government agencies and humanitarian organizations to respond effectively once the disaster hits. In the literature, two-stage stochastic programming models are commonly employed to develop preparedness plans before anticipated disasters. These models can be very difficult to solve as the complexity increases with several sources of uncertainty and interdependent decisions. In this study, we propose an integer L-shaped algorithm to solve the integrated location and network restoration model, which is a two-stage stochastic programming model determining the number and locations of the emergency response facilities and restoration resources under uncertainty. Our algorithm accommodates the second-stage binary decision variables which are required to indicate undamaged and restored roads of the network that can be used for relief distribution. Our computational results show that our algorithm outperforms CPLEX for the larger number of disaster scenarios as the solution time of our algorithm increases only linearly as the number of scenarios increases.

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

AbstractRecently, locating emergency response facilities has been drawing increasing attention with the highly strategic nature of terrorist attacks. To this end, we present a game‐theoretic approach for the location of terror response facilities when both disruption risk and hidden information are taken into account. The game is described as a two‐stage game, in which the first stage allows the State, that is, defender, to locate the terror response facilities, including disclosed and undisclosed facilities, and assign them to the attacked city, while the second stage allows the terrorist, that is, attacker, to select one city to attack with partial information about facility location and assignment. We propose a mixed integer bi‐level nonlinear programming formulation, and in response, a heuristic algorithm is developed to find the equilibrium solution. Extensive computational tests on both synthetic data and a real‐world dataset of provincial capital cities in China demonstrate the effectiveness of the developed algorithm.

Leveraging lessons learned to prevent future disasters\u2014insights from the 2013 Colombia-US binational exchange

In 2013, scientists implemented a binational exchange for emergency planners and responders in communities near Nevado del Ruiz in Colombia and volcanoes of the Cascade Range of the United States (US). This program was designed to promote understanding of volcanic disasters and effective mitigation options, motivate participants to strengthen emergency planning efforts, and promote trust-building among participants. The 2013 Binational Exchange was funded by the Volcano Disaster Assistance Program (VDAP), a joint U.S. Geological Survey (USGS)—U.S. Agency for International Development (USAID) program.During a week-long visit to Colombian emergency response agencies, Nevado del Ruiz, and lahar-destroyed ruins of the city of Armero and the region of Viejo Rio Claro, US participants became familiar with Colombian counterparts who have had recent and frequent experiences addressing volcanic crises. Aging survivors and authorities of the Nevado del Ruiz catastrophe of 1985 gave participants first-hand accounts, and ideas for improved preparedness and response. While in the US, Colombian participants observed emergency response capabilities and facilities, and received training in systems of incident command. Colombians made presentations to the US public and officials about the similarities of lahar risks in both nations.This article describes the 2013 Binational Exchange as an experiential learning event and uses results of post-exchange discussions and interviews as evidence of steps achieved within the learning process. Six years hence, this article provides examples of progress with volcano hazards mitigation in both nations. The article offers the binational exchange model as an effective tool that employs both experiential learning and socialization of participants to create a highly motivating and effective learning environment.

Integrating location and network restoration decisions in relief networks under uncertainty

Prepositioning emergency relief items in emergency response facilities before an anticipated disaster is a common strategy to increase the effectiveness of relief distribution. In this paper, we assume that relief distribution activities are hampered due to damaged roads, which can be restored by repair teams using restoration equipment. We propose a two-stage stochastic programming model integrating facility location and network restoration decisions. Our integrated model decides on the location of restoration equipment prior to the disaster in addition to the facility location decisions. Moreover, decisions related to relief item distribution and network restoration are made jointly after the disaster for each disaster scenario. We capture uncertainty in the network availability by incorporating the repair times required to restore the damaged roads. To solve our integrated model efficiently, we develop a sample average approximation method with concentration sets motivated by Rosing and ReVelle’s (1997) Heuristic Concentration. These concentration sets are comprised of promising locations identified by information obtained from disaster scenarios. We limit our solution space in the first stage to concentration sets to reduce the problem size without sacrificing the solution quality significantly. Our computational results show significant improvement in unmet demand and cost measures by integrating location and network restoration models.

Humanitarian supply chain network design using data envelopment analysis and multi-objective programming models

Emergency events such as natural disasters or terrorist attacks seem to occur anywhere and tend to increase. This paper studies a humanitarian supply chain network (HTSCN) design problem in a pre-disaster scenario, which consists of finding the optimal emergency response facility (ERF) locations and allocation scheme of humanitarian supplies through ERFs, where all ERFs are under the risk of disruptions. Naturally, this type of design problem should deal with multiple goals. An innovative two-step framework of designing efficient HTSCN by combining multi-objective programming (MOP) models with data envelopment analysis (DEA) is proposed. A case study using the historical data on the disasters in South Carolina, USA is presented to illustrate the effectiveness and efficiency of the proposed combining framework. The case study demonstrates that the proposed procedure would help practitioners and researchers generate a finer evaluation of efficiency and would provide a benchmarking methodology for designing HTSCN system. [Received: 22 October 2017; Revised: 9 April 2018; Revised: 15 October 2018; Revised: 22 December 2018; Accepted: 26 January 2019]

Single-level LRP Problem of Emergency Logistics System Considering Demand Priority

Once a public emergency occurs, it will cause serious human casualties and property losses to human society. If timely and effective rescue measures are not adopted, the consequences will be disastrous. Therefore, it is necessary to establish a sound and effective emergency rescue system. In this paper, we establish an open emergency response facility positioning and emergency relief transportation model based on the characteristics of demand points, vehicle service capabilities, soft time windows, damage of road network and other constraints. The non-dominated sorting genetic algorithm was applied in this article. Finally, the simulation verified the rationality and the effectiveness of the model and the algorithm.

Measuring the accessibility of critical facilities in the presence of hurricane-related roadway closures and an approach for predicting future roadway disruptions

Roadway closures magnify the adverse effects of disasters on people since any type of such disruption increases the emergency response travel time (ERTT), which is of central importance for the safety and survival of the affected people. Especially in the State of Florida, high winds due to hurricanes, such as the Hurricane Hermine, lead to notable roadway disruptions and closures that compel special attention. As such, in this paper, the accessibility of emergency response facilities, such as police stations, fire stations and hospitals in the City of Tallahassee, the capital of Florida, was extensively studied using real-life data on roadway closures during Hurricane Hermine. A new metric, namely Accessibility Decrease Index, was proposed, which measures the change in ERTT before and in the aftermath of a hurricane such as Hermine. Results clearly show those regions with reduced emergency response facility accessibility and roadways under a disruption risk in the 1-week window after Hermine hit Tallahassee. City officials can pinpoint these critical locations for future improvements and identify those critical roadways, which are under a risk of disruption due to the impact of the hurricane. This information can be utilized to improve emergency response plans by improving the roadway infrastructure and providing alternative routes to public.

Reliable maximin–maxisum locations for maximum service availability on tree networks vulnerable to disruptions

In this era of ubiquitous networks that become increasingly vulnerable to disruptions, network reliability has emerged as a critical issue in their design and operation. Businesses and individuals become ever more dependent on networks and demand reliable delivery of critical services every time. This paper finds Pareto optimal locations for a single facility on an existing tree network that maximizes service availability to customers by considering both the average and the lowest level of service delivery with respect to all customers. Examples are the location of decision entities on information infrastructures, servers or databases on computer networks, control systems on telecommunication networks, critical information on social networks, supply centers on supply chain networks, and location of emergency response facilities to intentional or natural disasters. Model properties are identified in decision and objective space and used to develop an efficient algorithm for finding the efficient and the non-dominated sets. Numerical examples are provided to illustrate the algorithm and to show special conditions for the efficient and non-dominated sets to be continuous.

Determining the Optimal Location of Terror Response Facilities Under the Risk of Disruption

The highly strategic nature of terrorist attacks has often frustrated attempts at locating emergency response facilities. To better determine the optimal location of such facilities, we present a leader-follower game between State and Terrorist by considering facility failures. The first stage of the game allows State to make a facility location decision and facility assignment to the attacked city, while the second stage allows Terrorist to select one city to attack after observing the State's strategy. The game is translated into a minmaxmin problem, and a population-based heuristic algorithm is proposed to solve it. We evaluate the performance of both model and heuristic by using an emergency example. Our results indicate that the proposed algorithm is able to generate suitable facility location solutions, allowing us to deploy resources more efficiently during a terrorist attack to where they are needed.

Analysis of essential facilities and occupancy class for earthquake preparedness in Dhaka City

A major earthquake has been forecast for Bangladesh in the near future due to its position at the junction of three continental plates. Should an earthquake occur, it is expected to be devastating, particularly in the capital city of Dhaka, due to a large number of high-rise buildings constructed on relatively unstable ground and the high population density of the metropolitan area. In this paper, we use statistical methods to identify correlations among the occupancy classes, essential facilities, and population density in both of Dhaka North City Corporation (DNCC) and Dhaka South City Corporation (DSCC). Correlation analysis shows that medical care and emergency response are positively weak correlated in DNCC but negatively correlated in the residential areas in DSCC. Multiple regression analysis indicates that the potential to efficiently respond to a disaster is relatively low concerning the emergency response and medical care facilities in both of DNCC and DSCC area.

Impact of ICT in Rural Development: Perspective of Developing Countries

Information and communication technology (ICT) can be thought of as an umbrella under which there reside communication system, device and applications. Main importance of ICT is given to its ability to provide greater access to information and communication to the populations and the quality of service provided than the technological backbone required. Rural development includes economic betterment of people as well as greater social transformation to eliminate poverty, ignorance and inequality of opportunities. In developing countries a large number of people are resident of rural area, thus rural development program is a necessary aspect. Use of information and communication technology can contribute a lot in socioeconomic development of rural area. In the current communication we have mainly focused on rural education, agriculture, health care facility, disaster and emergency response and E-governance facility in rural areas of developing countries.

Emergency response facilities including primary and secondary prevention strategies across 79 professional football clubs in England

AimTo assess the emergency response planning and prevention strategies for sudden cardiac arrest (SCA) across a wide range of professional football clubs in England.MethodsA written survey was sent to all...

An Integrated Framework for Allocation of New Emergency Response Facilities in Developing Nations

Developing countries are majorly resource-constrained societies which do not have the financial power to invest in meeting all infrastructure needs. Although there are multiple types of emergency response systems (ERS), the most important ones are the basic essentials—fire, medical and police. Along with emergency response planning for man-made emergencies in an urban scenario, there is a gap in the recent literature about integration of basic ERS into a single framework. We propose a novel framework that first evaluates the existing ERS in place and then provides solutions for improvement with the inclusion of additional facilities at optimal locations. Keeping in mind dynamic congestion patterns and land use resource constraints in different areas of the urban space, the proposed facilities are labeled as either permanent or floating. We also propose three different schemes, each with two competing strategies that cater to a specific type of constraint common to developing nations. Through comparison of system performance metrics like first response time, area coverage, and average response time, the ERS pre- and post-implementation of the framework are compared to check for degree of improvement. A case study of the framework is shown using the city of Chandigarh in India as an example. The framework proposed in the paper takes into account the growth and compactness of urban spaces and can be used to continually assess and improve ERS in mixed use urban spaces after fixed periods of time.