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\"The volume investigates to what extent the international and European Union legal frameworks applicable to Chemical, Biological and Radio-Nuclear (CBRN) events are adequate to face current challenges. It is innovative in many aspects: it adopts an all-hazard approach to CBRN risks, focusing on events of intentional, accidental and natural origin; it explores international obligations according to the four phases of the emergency cycle, including prevention, preparedness, response and recovery; and it covers horizontal issues such as protection of human rights, international environmental law, new technologies, the role of private actors, as well as enforcement mechanisms and remedies available to victims. The book thus offers a new way of looking at the applicable rules of international law in this field\"-- Provided by publisher.

To treat many patients despite lacking personnel resources, triage is important in disaster medicine. Various triage algorithms help but often are used incorrectly or not at all. One potential problem-solving approach is to support triage with Smart Glasses. In this study, augmented reality was used to display a triage algorithm and telemedicine assistance was enabled to compare the duration and quality of triage with a conventional one. A specific Android app was designed for use with Smart Glasses, which added information in terms of augmented reality with two different methods-through the display of a triage algorithm in data glasses and a telemedical connection to a senior emergency physician realized by the integrated camera. A scenario was created (ie, randomized simulation study) in which 31 paramedics carried out a triage of 12 patients in 3 groups as follows: without technical support (control group), with a triage algorithm display, and with telemedical contact. A total of 362 assessments were performed. The accuracy in the control group was only 58%, but the assessments were quicker (on average 16.6 seconds). In contrast, an accuracy of 92% (P=.04) was achieved when using technical support by displaying the triage algorithm. This triaging took an average of 37.0 seconds. The triage group wearing data glasses and being telemedically connected achieved 90% accuracy (P=.01) in 35.0 seconds. Triage with data glasses required markedly more time. While only a tally was recorded in the control group, Smart Glasses led to digital capture of the triage results, which have many tactical advantages. We expect a high potential in the application of Smart Glasses in disaster scenarios when using telemedicine and augmented reality features to improve the quality of triage.

\"Bill Browning heads the trauma unit at San Francisco's busiest emergency room, SF General. With his ex-wife and daughters in London, he immerses himself in his work and lives for rare visits with his children. A rising star at her teaching hospital, UCSF at Mission Bay, Stephanie Lawrence has two young sons, a frustrated stay-at-home husband, and not enough time for any of them. Harvard-educated Wendy Jones is a dedicated trauma doctor at Stanford, trapped in a dead-end relationship with a married cardiac surgeon. And Tom Wylie's popularity with women rivals the superb medical skills he employs at his Oakland medical center, but he refuses to let anyone get too close, determined to remain unattached forever. These exceptional doctors are chosen for an honor and a unique project: to work with their counterparts in Paris in a mass-casualty training program. As professionals, they will gain invaluable knowledge from the program. When an unspeakable act of mass violence galvanizes them into action, their temporary life in Paris becomes a stark turning point: a time to face harder choices than they have ever made before - with consequences that will last a lifetime\" -- Front jacket flap.

Stories of the missing offer profound insights into the tension between how political systems see us and how we see each other. The search for people who go missing as a result of war, political violence, genocide, or natural disaster reveals how forms of governance that objectify the person are challenged. Contemporary political systems treat persons instrumentally, as objects to be administered rather than as singular beings: the apparatus of government recognizes categories, not people. In contrast, relatives of the missing demand that authorities focus on a particular person: families and friends are looking for someone who to them is unique and irreplaceable. InMissing, Jenny Edkins highlights stories from a range of circumstances that shed light on this critical tension: the aftermath of World War II, when millions in Europe were displaced; the period following the fall of the World Trade Center towers in Manhattan in 2001 and the bombings in London in 2005; searches for military personnel missing in action; the thousands of political \"disappearances\" in Latin America; and in more quotidian circumstances where people walk out on their families and disappear of their own volition. When someone goes missing we often find that we didn't know them as well as we thought: there is a sense in which we are \"missing\" even to our nearest and dearest and even when we are present, not absent. In this thought-provoking book, Edkins investigates what this more profound \"missingness\" might mean in political terms.

Background Effective preparedness to respond to mass casualty incidents and disasters requires a well-planned and integrated effort by all involved professionals, particularly those who are working in healthcare, who are equipped with unique knowledge and skills for emergencies. This study aims to investigate and evaluate the level of knowledge and skills related to mass casualty and disaster management in a cohort of healthcare professionals. Methods A cross-sectional brief study was conducted using a validated and anonymous questionnaire, with a sample of 134 employees at a clinical hospital in Lublin, Poland. Results The findings of this study may indicate a need for standardization of training for hospitals employees. It also suggests a knowledge gap between different professional groups, which calls for adjusting such general training, to at least, the weakest group, while special tasks and mission can be given to other groups within the training occasion. Conclusion Pre-Training gap analyses and identification of participants’ competencies and skills should be conducted prior to training in mass casualty incidents and disasters. Such analyses provides an opportunity to develop training curriculum at various skill and knowledge levels from basic to advance. All training in mass casualty incidents and disasters should be subject to ongoing, not just periodic, evaluation, in order to assess continued competency.

Sara L Wattenbarger Department of Emergency Medicine, University of South Alabama, Mobile, AL, USACorrespondence: Sara L Wattenbarger, Email swattenbarger@health.southalabama.eduBackground: Mass casualty incidents present significant challenges to healthcare systems, necessitating effective triage and response from emergency personnel. Unfortunately, emergency medicine residents have reported discomfort with disaster preparation and lack of confidence at the prospect of responding to large-scale mass casualty incidents. Mass casualty preparation exercises are often costly, time-consuming to plan, and resource prohibitive, complicating disaster training initiatives for emergency medicine residency programs. We implemented and evaluated a novel training exercise geared toward improving resident comfort levels in utilizing the START (Simple Triage and Rapid Treatment) and JumpSTART triage algorithms that incorporated easily acquired materials and required limited faculty time commitment.Methods: We staged two small-scale mass casualty exercises in May 2023 and December 2024 utilizing moulaged dolls and props designed to mimic a disaster scene. Dolls were equipped with QR codes linked to short vignettes including vital signs and relevant clinical information. Residents were instructed to assign a triage designation based on the information provided and input their response into Google Forms. Once submitted, participants received immediate feedback regarding the accuracy of their response, along with an explanation of why they were or were not correct.Results: A total of thirteen residents for the first, and twelve residents for the second exercise implementation participated, completing pre- and post-intervention surveys to evaluate their comfort with mass casualty scenarios using the START triage system. Results indicated a 66% increase (first implementation) and 55% increase (second implementation) in the likelihood of residents feeling “mostly” or “very” comfortable post-exercise. Participants rated the teaching quality and instructional tools as “excellent”.Conclusion: Resident confidence in responding to mass casualty incidents improved post-exercise via the use of a cost-effective and easily replicable mass casualty triage training model, circumventing the need for costly simulation equipment and extensive faculty involvement.Keywords: disaster, mass casualty incident, mass casualty triage, emergency medicine

Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts. Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event. We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.

Mass shooting episodes have increased over recent decades and received substantial media coverage. Despite the potentially widespread and increasing mental health impact of mass shootings, no efforts to our knowledge have been made to review the empirical literature on this topic. We identified 49 peer-reviewed articles, comprised of 27 independent samples in the aftermath of 15 mass shooting incidents. Based on our review, we concluded that mass shootings are associated with a variety of adverse psychological outcomes in survivors and members of affected communities. Less is known about the psychological effects of mass shootings on indirectly exposed populations; however, there is evidence that such events lead to at least short-term increases in fears and declines in perceived safety. A variety of risk factors for adverse psychological outcomes have been identified, including demographic and pre-incident characteristics (e.g., female gender and pre-incident psychological symptoms), event exposure (e.g., greater proximity to the attack and acquaintance with the deceased), and fewer psychosocial resources (e.g., emotion regulation difficulties and lower social support). Further research that draws on pre-incident and longitudinal data will yield important insights into the processes that exacerbate or sustain post-incident psychological symptoms over time and provide important information for crisis preparedness and post-incident mental health interventions.

Immersive virtual reality (iVR) has emerged as a training method to prepare medical first responders (MFRs) for mass casualty incidents (MCIs) and disasters in a resource-efficient, flexible, and safe manner. However, systematic evaluations and validations of potential performance indicators for virtual MCI training are still lacking. This study aimed to investigate whether different performance indicators based on visual attention, triage performance, and information transmission can be effectively extended to MCI training in iVR by testing if they can discriminate between different levels of expertise. Furthermore, the study examined the extent to which such objective indicators correlate with subjective performance assessments. A total of 76 participants (mean age 25.54, SD 6.01 y; 45/76, 59% male) with different medical expertise (MFRs: paramedics and emergency physicians; non-MFRs: medical students, in-hospital nurses, and other physicians) participated in 5 virtual MCI scenarios of varying complexity in a randomized order. Tasks involved assessing the situation, triaging virtual patients, and transmitting relevant information to a control center. Performance indicators included eye-tracking-based visual attention, triage accuracy, triage speed, information transmission efficiency, and self-assessment of performance. Expertise was determined based on the occupational group (39/76, 51% MFRs vs 37/76, 49% non-MFRs) and a knowledge test with patient vignettes. Triage accuracy (d=0.48), triage speed (d=0.42), and information transmission efficiency (d=1.13) differentiated significantly between MFRs and non-MFRs. In addition, higher triage accuracy was significantly associated with higher triage knowledge test scores (Spearman ρ=0.40). Visual attention was not significantly associated with expertise. Furthermore, subjective performance was not correlated with any other performance indicator. iVR-based MCI scenarios proved to be a valuable tool for assessing the performance of MFRs. The results suggest that iVR could be integrated into current MCI training curricula to provide frequent, objective, and potentially (partly) automated performance assessments in a controlled environment. In particular, performance indicators, such as triage accuracy, triage speed, and information transmission efficiency, capture multiple aspects of performance and are recommended for integration. While the examined visual attention indicators did not function as valid performance indicators in this study, future research could further explore visual attention in MCI training and examine other indicators, such as holistic gaze patterns. Overall, the results underscore the importance of integrating objective indicators to enhance trainers' feedback and provide trainees with guidance on evaluating and reflecting on their own performance.

In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a promising future, offering potential improvements in processes such as triage, decision support, and resource optimization. However, the effectiveness of AI is heavily reliant on the availability of quality data. Currently, MCI data are scarce and difficult to obtain, as critical information regarding patient demographics, vital signs, and treatment responses is often missing or incomplete, particularly in the prehospital setting. Although the NIGHTINGALE (Novel Integrated Toolkit for Enhanced Pre-Hospital Life Support and Triage in Challenging and Large Emergencies) project is actively addressing these challenges by developing a comprehensive toolkit designed to support first responders and enhance data collection during MCIs, significant work remains to ensure the tools are fully operational and can effectively integrate continuous monitoring and data management. To further advance these efforts, we provide a series of recommendation, advocating for increased European Union funding to facilitate the generation of diverse and high-quality datasets essential for training AI models, including the application of transfer learning and the development of tools supporting data collection during MCIs, while fostering continuous collaboration between end users and technical developers. By securing these resources, we can enhance the efficiency and adaptability of AI applications in emergency care, bridging the current data gaps and ultimately improving outcomes during critical situations.