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Geographic information for the home address of the accident casualty is obtained from the home-address post-code for each casualty. This allows the STATS 19 data base, the UK police system for reporting accidents, for the former Lothian Region in Scotland, 1990 to 1992, to be linked to social and economic indicators in the 1991 UK census and to the corresponding digitised boundaries at the smallest census geographical level (Output Areas, OAs) and post-code sector level in Scotland. For each post-code sector Standardised Casualty Ratio (SCR) which is commonly used in epidemiology to study rare diseases is calculated from the ratio of the number of casualties observed to that expected in the area. Adjusted SCRs are calculated, they are the ratios of the numbers of casualties predicted by social and economic factors that are measured at the census using Poisson regression to the expected numbers. Empirical Bayes Estimates (EMEs) are applied to prevent the results from areas with small populations being shown as too extreme. Results from the analysis indicate that accident risk to residents from deprived areas is high compared with those from affluent areas. Finally maps that can be used to identify areas in Lothian where there is relatively high SCRs are presented.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

The purpose of this paper is to propose a new casualty scheduling optimisation problem and to effectively treat casualties in the early stage of post-earthquake relief.

Different from previous studies, some new characteristics of this stage are considered, such as the grey uncertainty information of casualty numbers, the injury deterioration and the facility disruption scenarios. Considering these new characteristics, we propose a novel casualty scheduling optimisation model based on grey chance-constrained programming (GCCP). The model is formulated as a 0–1 mixed-integer nonlinear programming (MINP) model. An improved particle swarm optimisation (PSO) algorithm embedded in a grey simulation technique is proposed to solve the model.

A case study of the Lushan earthquake in China is given to verify the effectiveness of the model and algorithm. The results show that (1) considering the facility disruption in advance can improve the system reliability, (2) the grey simulation technology is more suitable for dealing with the grey uncertain information with a wider fluctuation than the equal-weight whitening method and (3) the authors' proposed PSO is superior to the genetic algorithm and immune algorithm.

The casualty scheduling problem in the emergency recovery stage of post-earthquake relief could be integrated with our study to further enhance the research value of this paper.

Considering the facility disruption in advance is beneficial to treat more patients. Considering the facility disruption in the design stage of the emergency logistics network can improve the reliability of the system.

(1) The authors propose a new casualty scheduling optimisation problem based on GCCP in the early stage of post-earthquake relief. The proposed problem considers many new characteristics in this stage. To the best of the authors' knowledge, the authors are the first to use the GCCP to study the casualty scheduling problem under the grey information. (2) A MINP model is established to formulate the proposed problem. (3) An improved integer-encoded particle swarm optimisation (PSO) algorithm embedded grey simulation technique is designed in this paper.

Mass casualty incidents are characterised by an immediate, unforeseen and unquantifiable surge in demand for ambulance services which soon becomes apparent and will exceed any “local” resources available. Casualties require the correct treatment, promptly, at an appropriate resource without incurring any further harm. In the absence of firm operational guidelines, this paper provides templates for ambulance commanders both at call centre and on-site to approach the management of mass casualty incidents.

Desk research indicated that there were both guidelines on how various elements of the emergency services should work together plus academic papers on techniques to adopt in mass casualty situations. Standing orders or written protocols for ambulance commanders, however, provide little or no specific guidance or an outline plan upon how they should command in a mass casualty situation. Following analysis of relevant public enquiry reports and discussions with ambulance commanders and using the materials from desk research, a four-stage approach was devised for testing using retrospective analysis from field and desktop exercises.

To have confidence, each commander needs simple digital real-time templates from which they understand their role and how the overall plan defines priorities with the greatest need. A plan should cover call-centre and on-site operations including a basic operational checklist from start to finish; resource structure and inter-relationships; sources and availability of resources plus information and control procedures to impose limited quality control procedures.

The design and implementation of digital templates to provide minute-by-minute visibility to all commanders which have not been recorded before. Such templates give commanders confidence to determine, locate and call forward relevant resources to attend casualties in order of priority of need. Time-lapsed records are useful not just in the minute-by-minute decision processes but also for critical organisational learning and in any post-event review by either a coroner or lawyers at a public enquiry.

The purpose of this paper is to statistically assess the effects of the design factors including usage of data-driven decision support tool (DST), classification of patients (triage), prioritization based on vital scores of patients, number of ambulances and hospital selection rules, on the casualty transportation system’s performance in large-scale disasters. Besides, a data-driven DST for casualty transportation is proposed to enhance the casualty survival and ambulance transportation times during the disaster response stage.

In this study, the authors applied simulation and statistical analysis to evaluate the effects of usage of data-driven DST, classification of patients (triage), prioritization of the patients based on vital scores, number of ambulances and hospital selection rules, on the patient survival and transportation time of the casualty transportation system. An experimental design was made, and 16 scenarios were formulated. Simulation models were developed for all scenarios. The number of unrecoverable casualties and time-spent by the casualties until arriving at the hospital was observed. Then, a statistical analysis was applied to the simulation results, and significant factors were determined.

Utilization of the proposed DST was found to improve the casualty transportation and coordination performance. All main effects of the design factors were found statistically significant for the number of unrecoverable casualties. Besides, for the Time spent Until Arrival of T1-Type Casualty at the Hospital, all of the main factors are significant except the number of ambulances. Respiratory rate, pulse rate, motor response score priority and hospital selection rule based on available hospital capacities must be considered to reduce the number of unrecoverable casualties and time spent until arrival of the casualties at the hospitals.

In this study, the factors that significantly affect the performance of the casualty transportation system were revealed, by simulation and statistical analysis, based on an expected earthquake case, in a metropolitan city. Besides, it was shown that using a data-driven DST that tracks victims and intends to support disaster coordination centers and medical staff performing casualty transportation significantly improves survival rate of the victims and time to deliver the casualties. This research considers the whole systems’ components, contributes to developing the response stage operations by filling gaps between using the data-driven DST and casualty transportation processes.

When modeling environmental jolts from terrorist attacks, various aspects should be analyzed in order to properly present an accurate configuration. The following article discusses how asymmetrical warfare has an impact on the outcomes of a terrorist attack. The several dimensions of terrorist attacks can be extracted to deduce the ways that asymmetrical warfare can damage the health care system. The article will relate real life terrorist attacks and hypothetical scenarios to better inform the reader about the weak attacking the strong, and then explain how this relates to health care providers.

The tragic events of 11 September 2001 have caused people in all walks of life around the world to pause and reflect about what is important to them. With the World Trade Center, one of the icons of global capitalism and New York’s skyline, reduced to a heap of burned and twisted rubble at ‘Ground Zero’ in lower Manhattan, the world of commercial real estate is undergoing a time of reflection in the wake of these unbelievable events. While the catalyst for this time of reflective analysis was at the same time both horrific and compelling, the careful consideration of relevant lease issues and of the need for disaster recovery planning that has resulted will help everyone to be better prepared for unexpected events of any kind in the future. The purpose of this paper is to identify three standard lease provisions that have always been important, but now bear even closer scrutiny in the aftermath of the catastrophic losses of 11 September. These provisions are: Casualty; Interruption or Unavailability of Services; and Insurance. Most form leases contain provisions that address these subjects and raise various issues that are ripe for re‐examination. This paper discusses how such issues might be analysed (or re‐analysed) in the aftermath of this senseless tragedy. Please note that the legal conclusions, practices and norms outlined in this paper are generalised from a United States perspective and, as such, the norms and potential solutions may vary in other countries and on a case‐by‐case basis within a country. Further, the starting point and, often, the ending point in the analysis of any leasing issue is the specific language of the lease, which itself is subject to any applicable laws of the relevant legal jurisdiction. It is important to consider the issues and analysis discussed in this paper in light of the specific market norms and laws of the jurisdiction which are applicable.

Decontamination following chemical, biological, radiological and nuclear (CBRN)/Hazmat incidents is a critical activity carried out in order to mitigate and contain the risk posed by any hazardous materials involved. Human behaviour plays a crucial role in such incidents, as casualties will have little understanding of the situation they find themselves in, leading to uncertainty in what actions to take. This will result in very difficult circumstances within which first responders must operate. However, the importance of human behaviour appears to be a fundamental element being missed in the preparation, training and planning assumptions being made by emergency services and planners in preparation for these events.

This paper looks to understand the scope of this omission by reviewing relevant literature on the subject and engaging with Fire and Rescue Service personnel and managers in the UK. This study utilised semi-structured interviews with 10 Fire and Rescue Service Mass Decontamination Operatives, four Fire and Rescue Service Hazardous Material Advisers and three Fire and Rescue Service Strategic Officers participating. These interviews were then analysed using a thematic framework to identified key themes from the research which were then validated using two independent researchers to provide an inter-rater reliability measure. Finally, a follow-up validation questionnaire was also developed to test the validity of the themes identified and this was completed by another with 36 Fire and Rescue Service Mass Decontamination Operatives.

Both the literature review and interviews undertaken with emergency responders and mangers demonstrated the crucial importance of accounting for behavioural aspects in these situations especially in regards to the likely levels of compliance to be expected by responders and the potential problem of casualties not remaining at the scene of an incident to undergo decontamination.

This research identifies a number of key themes so far not recognized through any other research and in doing so offers insights into potential flaws in the UK Fire and Rescue Service response planning for CBRN/Hazmat incidents requiring mass decontamination. It is intended that this research will inform further study into the areas identified in order to ensure gaps in planning, training and strategies for mass decontamination operations can be more fully informed and if required allow for a more effective response.

The proliferation of terrorism worldwide raises the risk that terrorist strategies could evolve from conventional methods (e.g. suicide attacks) to biological, chemical and even radioactive and nuclear attacks (commonly abbreviated as CBRN) which are potentially much more dangerous. The authors make three contributions toward a better understanding of this risk and how it responds to counterterrorism measures.

The authors develop a game that captures the terrorists’ potential strategic substitution between conventional and CBRN-type attacks; the authors calibrate the parameters of the game to real data using a novel calibration method and a partially unique dataset; they estimate the heavy-tailed distribution of attack severity and thus the probability of a successful attack, the underlying effort to launch an attack and the intrinsic difficulty of launching different types of attacks.

The authors find that in equilibrium, CBRN attacks, though less likely and more difficult to execute, are more deadly. In the end, the trade-off between, on one hand, the greater difficulty of carrying out a CBRN attack, and on the other, the greater deadliness of such an attack, points to a level of optimal counterterrorism spending by governments that weighs toward defending against CBRN attacks. The authors discuss these results and compare them with the actual level of counterterrorism spending by the US Government.

The framework of the game allows for substitution between the conventional and CBRN weapon types. These aspects of this paper, together with the unique calibration methodology, and the use of some unique terrorism data for the first time, are what distinguish this work from similar game theoretic papers in this area.