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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.

When designing an optimization model for use in a mass casualty event response, it is common to encounter the heavy and considerable demand of injured patients and inadequate resources and personnel to provide patients with care. The purpose of this study is to create a model that is more practical in the real world. So the concept of “predicting the resource and personnel shortages” has been used in this research. Their model helps to predict the resource and personnel shortages during a mass casualty event. In this paper, to deal with the shortages, some temporary emergency operation centers near the hospitals have been created, and extra patients have been allocated to the operation center nearest to the hospitals with the purpose of improving the performance of the hospitals, reducing congestion in the hospitals and considering the welfare of the applicants.

The authors research will focus on where to locate health-care facilities and how to allocate the patients to multiple hospitals to take into view that in some cases of emergency situations, the patients may exceed the resource and personnel capacity of hospitals to provide conventional standards of care.

In view of the fact that the problem is high degree of complexity, two multi-objective meta-heuristic algorithms, including non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA), were proposed to solve the model where their performances were compared in terms of four multi-objective metrics including maximum spread index (MSI), spacing (S), number of Pareto solution (NPS) and CPU run-time values. For comparison purpose, paired t-test was used. The results of 15 numerical examples showed that there is no significant difference based on MSI, S and NPS metrics, and NRGA significantly works better than NSGA-II in terms of CPU time, and the technique for the order of preference by similarity to ideal solution results showed that NRGA is a better procedure than NSGA-II.

The planning horizon and time variable have not been considered in the model, for example, the length of patients’ hospitalization at hospitals.

Presenting an effective strategy to respond to a mass casualty event (natural and man-made) is the main goal of the authors’ research.

This paper strategy is used in all of the health-care centers, such as hospitals, clinics and emergency centers when dealing with disasters and encountering with the heavy and considerable demands of injured patients and inadequate resources and personnel to provide patients with care.

This paper attempts to shed light onto the formulation and the solution of a three-objective optimization model. The first part of the objective function attempts to maximize the covered population of injured patients, the second objective minimizes the distance between hospitals and temporary emergency operation centers and the third objective minimizes the distance between the warehouses and temporary centers.

Health care organizations are accustomed to rapid and often discontinuous environmental change. Even when contemplating large scale change including the decisions to merge or integrate operations, health care managers can draw upon the expertise and advise of peers who have gone through similar experiences. However a bioterror event is a class of change that represents something totally unplanned and for which the industry has little or no experience in confronting. The objective for health care organizations is to mitigate the effects of this type of an event. Specific ideas for taking systems oriented, network-centric approach to disaster planning are provided.

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.

This paper aims to evaluate emergency department (ED) design space planning approaches and draw lessons for developing more resilient and integrated ED guidelines. Two key objectives have been set; these include: exploring potential factors affecting the ED performance, and investigate how ED space planning is addressed internationally through the evaluation of international case studies and design guidelines.

A robust research method has been adopted including comprehensive literature review in addition to 76 case studies from Italy and the USA.

Findings show that the important factors in defining ED space requirements are attendance variability, vulnerable groups and mass casualty events. The study concludes that current design guidelines and approaches need to be updated to meet with the current and future demand by taking into account design performance: effectiveness, efficiency and resilience, to avoid underestimating ED space; and that the US EDs are in a better position, than Italian EDs, to increase capacity when needed.

The contribution of this study is in providing a tangible “understanding” of factors influencing ED design and prepares a firm ground to develop more resilient and integrated design guidelines, able to meet current, exceptional and long-term needs of EDs. The study also shows that research can provide a valuable contribution to improve ED design which needs to feed more in practice to improve design process and guidelines.

Reducing fatalities and increasing the number of students able to remain safe during an active shooter event is paramount to the health and well-being of schools and communities. Yet, methodological limitations and ethical concerns have restricted prior research on security measures during school shooter lockdown drills. This study aims to fill that gap by using virtual reality (VR) to statistically examine the effectiveness of active shooter response protocols in a simulated high school.

Using a full factorial, within-subjects experimental design, this exploratory investigation used VR technology to investigate whether automatic classroom door locks, centralized lockdown notifications and the presence of a school resource officer (SRO) significantly impacted student safety and casualty mitigation. Data were collected from a convenience sample of 37 individuals who volunteered to participate in 24 school shooter scenarios within a simulated virtual environment.

Multiple one-way analysis of variances indicated significant main effects for automatic classroom door locks and SRO presence. Automatic locks yielded faster lockdown response times, and both factors were significantly associated with higher numbers of secured classrooms.

Findings from the current study address the gap in existing literature regarding evidence-based school safety protocols and provide recommendations for using VR simulations to increase preparedness and reduce fatalities during an active school shooter event.

Hospitals recently search for more accurate forecasting systems, given the unpredictable demand and the increasing occurrence of disruptive incidents (mass casualty incidents, pandemics and natural disasters). Besides, the incorporation of automatic inventory and replenishment systems – that hospitals are undertaking – requires developed and accurate forecasting systems. Researchers propose different artificial intelligence (AI)-based forecasting models to predict hospital assets consumption (AC) for everyday activity case and prove that AI-based models generally outperform many forecasting models in this framework. The purpose of this paper is to identify the appropriate AI-based forecasting model(s) for predicting hospital AC under disruptive incidents to improve hospitals' response to disasters/pandemics situations.

The authors select the appropriate AI-based forecasting models according to the deduced criteria from hospitals' framework analysis under disruptive incidents. Artificial neural network (ANN), recurrent neural network (RNN), adaptive neuro-fuzzy inference system (ANFIS) and learning-FIS (FIS with learning algorithms) are generally compliant with the criteria among many AI-based forecasting methods. Therefore, the authors evaluate their accuracy to predict a university hospital AC under a burn mass casualty incident.

The ANFIS model is the most compliant with the extracted criteria (autonomous learning capability, fast response, real-time control and interpretability) and provides the best accuracy (the average accuracy is 98.46%) comparing to the other models.

This work contributes to developing accurate forecasting systems for hospitals under disruptive incidents to improve their response to disasters/pandemics situations.

There is a prevailing assumption in the research literature that disaster exercises produce a wide variety of benefits that promote effective emergency management. Unfortunately, there are few studies available that confirm this assumption. This paper reviews the role of exercises in disaster management and places them within the context of preparedness activities. Within this context, the links among planning, training and exercising are explicated. The potential benefits of exercises are reviewed and hypotheses generated that link exercise experiences with emergency responders’ perceptions of planning adequacy, training adequacy, teamwork, response network effectiveness, equipment adequacy and job risk. The effects of two exercises – one dealing with hazardous materials and one with medical mass casualties – are examined using a quasi‐experimental research design. The subjects were professional firefighters. Results indicated that successful exercises can enhance perceptions of teamwork, training adequacy, response network effectiveness, job risk, and equipment adequacy. The link between exercise participation and perception of planning adequacy was found to be equivocal.

The purpose of this paper is to systematically review published literature for the research question “what issues are considered (and changes made) for vulnerable groups as part of the chemical, biological, radiological, nuclear or explosive (CBRNe) response for casualty collection, decontamination, triage and casualty clearing processes?”.

Seven-stage framework from the PRISMA statement for research question, eligibility (definition), search, identification of relevant papers from title and abstract, selection and retrieval of papers, appraisal and synthesis. Data sources: Medline, Embase, Cochrane Library, Web of Science, Scopus (Elsevier), Chemical Abstracts, Assia (Proquest), Sociological abstracts (Proquest), Cinahl, HMIC, Health business elite, PsycInfo (ebsco), PILOTS (Proquest) and supplemented by other search strategies (e.g. exploding reference lists). The included references were critically appraised using the mixed methods appraisal tool (MMAT).

Results: 1,855 papers were returned from the literature search, of which 221 were screened by abstract and 48 by full paper. In total, 11 papers were included for appraisal, of which three achieved a quality score of 50 per cent or over. The papers were categorised into three phases on CBRNe response; evacuation, triage and decontamination.

The limitations of the search process included the use of emerging exclusion criteria. This may have excluded research that would provide more information in some topic areas but it was felt necessary to set a high publication standard for inclusion to generate trustworthy results and recommendations. The MMAT appraisal tool has been validated for different study types and provided a useful categorisation approach for critical appraisal, albeit resulting in only three included studies. Future reviews could include papers published in a wider range of languages to include research from non-English sources.

These evidence-based results should be used by practitioners to review current operational policies for vulnerable people and plan future improvements. Evacuation accessibility can be described as characteristics for exit, route and obstacles. This takes a systems approach to consider how building planning and layout can have implications for safety critical but low frequency events. Decontamination recommendations include: at least one additional re-robe section per mass decontamination unit and adaptations to the decontamination plan including accessible equipment for non-ambulatory individuals; and additional (specialist) staff in the decontamination team (sign language, interpreters and physical therapists).

Although very little new medium/high quality research is available, the findings are summarised as considerations for building design (route choice and information), communication (including vision, hearing and language differences) and the composition of the response team. It is suggested that evidence-based practice from other care domains could be considered (patient movement and handling) for fire service and ambulance guidelines.