Modelling the blast environment and relating this to clinical injury: experience from the 7/7 inquest

Injury modelling for strategic planning in protecting the national infrastructure from terrorist explosive events

Terrorist events in the form of explosive devices have occurred and remain a threat currently to the population and the infrastructure of many nations worldwide. Injuries occur from a combination of a blast wave, energised fragments, blunt trauma and burns. The relative preponderance of each injury mechanism is dependent on the type of device, distance to targets, population density and the surrounding environment, such as an enclosed space, to name but a few. One method of primary prevention of such injuries is by modification of the environment in which the explosion occurs, such as modifying population density and the design of enclosed spaces. The Human Injury Predictor (HIP) tool is a computational model which was developed to predict the pattern of injuries following an explosion with the goal to inform national injury prevention strategies from terrorist attacks. HIP currently uses algorithms to predict the effects from primary and secondary blast and allows the geometry of buildings to be incorporated. It has been validated using clinical data from the '7/7' terrorist attacks in London and the 2017 Manchester Arena terrorist event. Although the tool can be used readily, it will benefit from further development to refine injury representation, validate injury scoring and enable the prediction of triage states. The tool can assist both in the design of future buildings and methods of transport, as well as the situation of critical emergency services required in the response following a terrorist explosive event. The aim of this paper is to describe the HIP tool in its current version and provide a roadmap for optimising its utility in the future for the protection of national infrastructure and the population.

Environment at the time of injury determines injury patterns in pelvic blast

The use of explosives by terrorists, or during armed conflict, remains a major global threat. Increasingly, these events occur in the civilian domain, and can potentially lead to injury and loss of life, on a very large scale. The environment at the time of detonation is known to result in different injury patterns in casualties exposed to blast, which is highly relevant to injury mitigation analyses. We describe differences in pelvic injury patterns in relation to different environments, from casualties that presented to the deployed UK military hospitals in Iraq and Afghanistan. A casualty on foot when injured typically sustains an unstable pelvic fracture pattern, which is commonly the cause of death. These casualties die from blood loss, meaning treatment in these should focus on early pelvic haemorrhage control. In contrast, casualties injured in vehicle present a different pattern, possibly caused by direct loading via the seat, which does not result in pelvic instability. Fatalities in this cohort are from injuries to other body regions, in particular the head and the torso and who may require urgent neurosurgery or thoracotomy as life-saving interventions. A different strategy is therefore required for mounted and dismounted casualties in order to increase survivors.

Modelling primary blast lung injury: current capability and future direction

Primary blast lung injury frequently complicates military conflict and terrorist attacks on civilian populations. The fact that it occurs in areas of conflict or unpredictable mass casualty events makes clinical study in human casualties implausible. Research in this field is therefore reliant on the use of some form of biological or non-biological surrogate model. This article briefly reviews the modelling work undertaken in this field until now and describes the rationale behind the generation of an in silico physiological model.

40 years of terrorist bombings - A meta-analysis of the casualty and injury profile

INTRODUCTION

Terrorists have used the explosive device successfully globally, with their effects extending beyond the resulting injuries. Suicide bombings, in particular, are being increasingly deployed due to the devastating effect of a combination of high lethality and target accuracy. The aim of this study was to identify trends and analyse the demographics and casualty figures of terrorist bombings worldwide.

METHODS

Analysis of the Global Terrorism Database (GTD) and a PubMed/Embase literature search (keywords "terrorist", and/or "suicide", and/or "bombing") from 1970 to 2014 was performed.

RESULTS

58,095 terrorist explosions worldwide were identified in the GTD. 5.08% were suicide bombings. Incidents per year are increasing (P<0.01). Mean casualty statistics per incidents was 1.14 deaths and 3.45 wounded from non-suicide incidents, and 10.16 and 24.16 from suicide bombings (p<0.05). The kill:wounded ratio was statistically higher in suicide attacks than non-suicide attacks, 1:1.3 and 1:1.24 respectively (p<0.05). The Middle East witnessed the most incidents (26.9%), with Europe (13.2%) ranked 4th. The literature search identified 41 publications reporting 167 incidents of which 3.9% detailed building collapse (BC), 60.8% confined space (CS), 23.5% open space (OS) and 11.8% semi-confined space (SC) attacks. 60.4% reported on suicide terrorist attacks. Overall 32 deaths and 180 injuries per incident were seen, however significantly more deaths occurred in explosions associated with a BC. Comparing OS and CS no difference in the deaths per incident was seen, 14.2(SD±17.828) and 15.63 (SD±10.071) respectively. However OS explosions resulted in significantly more injuries, 192.7 (SD±141.147), compared to CS, 79.20 (SD±59.8). Extremity related wounds were the commonest injuries seen (32%).

DISCUSSION/CONCLUSION

Terrorist bombings continue to be a threat and are increasing particularly in the Middle East. Initial reports, generated immediately at the scene by experienced coordination, on the type of detonation (suicide versus non-suicide), the environment of detonation (confined, open, building collapse) and the number of fatalities, and utilising the Kill:Wounded ratios found in this meta-analysis, can be used to predict the number of casualties and their likely injury profile of survivors to guide the immediate response by the medical services and the workload in the coming days.