Identifying MAIS3+ injury severity collisions in UK Police collision records

Objective This study represents the first stage of a project to identify serious injury, at the level of MAIS3+ (excluding fatal collisions) from within the police collision data. The resulting data will then be used to identify the vehicle drivers concerned and in later studies these will be culpability-scored and profiled to allow targeting of interventions. Method UK Police collision data known as STATS19 for the county of Cambridgeshire (UK) was linked using Stata with Trauma Audit and Research Network (TARN) hospital trauma patient data for the same geographical area for the period April 2012 to March 2017. Linking was two-stage; firstly, a deterministic process followed by a probabilistic process. Results The linked records represent an individual trauma patient from TARN data linked to an individual trauma casualty from STATS19 data. Full collision data for the incident resulting in the trauma casualty was extracted. The resulting subset of collisions has the MAIS3+ injury criteria applied. From the 10,498 recorded collisions the deterministic linking process was successful in linking 257 MAIS3+ trauma patients to collision injury subjects from 232 separate collisions with the probabilistic process linking a further 22 MAIS3+ subjects from 21 collision events. The combined collision data for the 253 collisions involved 434 motor vehicle drivers. Conclusions We produced viable results from the available data to identify MAIS3+ collisions from the overall collision data

Targeting Road Injury Prevention (TRIP): a systems approach to road safety management

Despite the UK having one of the lowest road casualty rates per head of population in the world, more than 1,500 people are killed in road traffic collisions every year, and progress in reducing casualties since 2010 has been limited. Actors in the road safety industry are united in a common goal to reduce road traffic injuries, yet how this should be achieved is debated and current road safety practice does not reflect actions in other safety industries. The main aim of this thesis is to understand how decision-making happens in road safety and, using lessons from research and other safety industries, present opportunities for how road safety can be shaped in the future. This thesis contributes to recent scholarly attempts to introduce system-based approaches to the road safety field by demonstrating the application of one such approach – Systems-Theoretic Accident Method and Processes (STAMP) – in the municipal area of Cambridgeshire, UK.Undertaken from the perspective of a practitioner-researcher, this thesis provides the first practical application of the STAMP method to road safety in the UK. The research includes a review of the existing literature which outlines how thinking towards safety has progressed since the beginning of the 20th Century and highlights the gaps between current road safety practice and that developed in other industries.The STAMP method is applied in three ways. First, to map the actors involved in the industry and the control structure for the road safety management system. This work was then used to identify key actors in the system who were interviewed to understand how decision-making happens and the barriers and facilitators to the use of research evidence in practice. Second, the Casual Analysis based on System Theory (CAST) application of STAMP was used to investigate ten fatal road traffic collisions. Third, the findings from the previous applications were combined in an organisational and social analysis using System-Theoretic Process Analysis (STPA) to generate recommendations to improve practice.This thesis provides further evidence that a research-practice gap exists in the road safety field and that decision-making in the industry is currently rooted in person-based approaches. To address this, the thesis demonstrates that the STAMP method is a valid system-based approach to road safety management at a municipal level and concludes with five high-level recommendations to improve the road safety management system.</p

Learning not blaming: Investigating ten fatal road traffic collisions using STAMP-CAST

There have been strong calls in the research literature for the adoption of system-based approaches to further reduce road casualties. However, person-based approaches remain at the forefront of both national and local-level decision-making around road safety in the UK. Focusing on person-based approaches inhibits learning across the system. Practical examples are needed to support adoption of system-based approaches and ensure safety learning is maximised within the industry.This study builds on previous work (Staton et al., 2022) mapping the control structure for the municipal area of Cambridgeshire, UK. It utilizes a system-based accident investigation method: Causal Analysis based on System Theory (CAST) (Leveson, 2019). The method is based on Rasmussen’s Risk Management Framework and is used to identify weaknesses in the control structure across the entire sociotechnical system. This supports understanding why the collision occurred and prevention of similar future events, rather than apportioning blame. In the study, CAST is used to investigate a random sample of ten fatal collisions that occurred in Cambridgeshire between 2018 and 2020. The investigations were conducted retrospectively using police forensic collision investigation files that had already concluded crown or coroner’s court proceedings.Across all ten collisions investigated, 21 different types of actor were identified across all levels of the system, each of whom played some role in at least one of the collisions. As a result, 49 specific recommendations are made concerning these actor’s roles in preventing future road deaths and serious injuries. In addition, 11 system-wide recommendations are made relating to communication and coordination; the safety information system; safety culture; design of the safety management system; changes and dynamics over time; and economic factors in the system environment.This study demonstrates that the CAST method is a viable tool for learning in the road safety industry and provides a taxonomy of system hazards, alongside the system control structure from Staton et al. (2022), to support any future analysis using this method. The use of CAST identifies the importance of controls within the road transport system and that currently, despite having one of the best road safety records in the world, the existing controls in place in the UK are insufficient to prevent serious injury and death occurring daily and are in danger of being eroded further through a political agenda of deregulation.This study reinforces that road safety requires system-based approaches and the strength of the CAST method in identifying system-wide recommendations which can be used in support of a Safe System approach to provide recommendations across the Safe System pillars

Learning not blaming: Investigating ten fatal road traffic collisions using STAMP-CAST

There have been strong calls in the research literature for the adoption of system-based approaches to further reduce road casualties. However, person-based approaches remain at the forefront of both national and local-level decision-making around road safety in the UK. Focusing on person-based approaches inhibits learning across the system. Practical examples are needed to support adoption of system-based approaches and ensure safety learning is maximised within the industry. This study builds on previous work (Staton et al., 2022) mapping the control structure for the municipal area of Cambridgeshire, UK. It utilizes a system-based accident investigation method: Causal Analysis based on System Theory (CAST) (Leveson, 2019). The method is based on Rasmussen’s Risk Management Framework and is used to identify weaknesses in the control structure across the entire sociotechnical system. This supports understanding why the collision occurred and prevention of similar future events, rather than apportioning blame. In the study, CAST is used to investigate a random sample of ten fatal collisions that occurred in Cambridgeshire between 2018 and 2020. The investigations were conducted retrospectively using police forensic collision investigation files that had already concluded crown or coroner’s court proceedings. Across all ten collisions investigated, 21 different types of actor were identified across all levels of the system, each of whom played some role in at least one of the collisions. As a result, 49 specific recommendations are made concerning these actor’s roles in preventing future road deaths and serious injuries. In addition, 11 system-wide recommendations are made relating to communication and coordination; the safety information system; safety culture; design of the safety management system; changes and dynamics over time; and economic factors in the system environment. This study demonstrates that the CAST method is a viable tool for learning in the road safety industry and provides a taxonomy of system hazards, alongside the system control structure from Staton et al. (2022), to support any future analysis using this method. The use of CAST identifies the importance of controls within the road transport system and that currently, despite having one of the best road safety records in the world, the existing controls in place in the UK are insufficient to prevent serious injury and death occurring daily and are in danger of being eroded further through a political agenda of deregulation. This study reinforces that road safety requires system-based approaches and the strength of the CAST method in identifying system-wide recommendations which can be used in support of a Safe System approach to provide recommendations across the Safe System pillars.</p

Targeting Road Injury Prevention

Prior to 2012 the UK saw a sustained reduction in road casualties where deaths from road collisions nearly halved. However, since then there has been a general plateauing of road deaths per year and incidents of serious injuries have also followed this trend. In 2018, 6.5% of all national killed and seriously injured casualties were fatalities, but in Cambridgeshire it was 7.6%. Additionally, the rate in 2018 for fatalities per 100,000 population in Great Britain was 2.8 for Cambridgeshire this rate was 5.9. The Cambridgeshire and Peterborough Road Safety Partnership sought to explore new ways that road safety interventions can be delivered to reduce serious and fatal injuries resulting from collisions. The notion being to target specific drivers who are responsible for the collisions based on geodemographic profiles. This study is a proof-of-concept study exploring the available data and methods involved to enable routine use of geodemographic profiling in road safety interventions.</div

A high‐quality reference genome for Fraxinus pennsylvanica for ash species restoration and research.

Green ash (Fraxinus pennsylvanica) is the most widely distributed ash tree in North America. Once common, it has experienced high mortality from the non‐native invasive emerald ash borer (EAB; Agrilus planipennis). A small percentage of native green ash trees that remain healthy in long‐infested areas, termed “lingering ash,” display partial resistance to the insect, indicating that breeding and propagating populations with higher resistance to EAB may be possible. To assist in ash breeding, ecology and evolution studies, we report the first chromosome‐level assembly from the genus Fraxinus for F. pennsylvanica with over 99% of bases anchored to 23 haploid chromosomes, spanning 757 Mb in total, composed of 49.43% repetitive DNA, and containing 35,470 high‐confidence gene models assigned to 22,976 Asterid orthogroups. We also present results of range‐wide genetic variation studies, the identification of candidate genes for important traits including potential EAB‐resistance genes, and an investigation of comparative genome organization among Asterids based on this reference genome platform. Residual duplicated regions within the genome probably resulting from a recent whole genome duplication event in Oleaceae were visualized in relation to wild olive (Olea europaea var. sylvestris). We used our F. pennsylvanica chromosome assembly to construct reference‐guided assemblies of 27 previously sequenced Fraxinus taxa, including F. excelsior. Thus, we present a significant step forward in genomic resources for research and protection of Fraxinus species

Short-term cognitive conspicuity training does not improve driver detection of motorcycles at road junctions: A reply to Crundall, Howard & Young (2017)

A common cause of road accidents is driver failure to perceive an approaching motorcycle. In a lab-based study, we investigated whether a simple naturalistic training intervention designed to increase the cognitive conspicuity of motorcycles could improve drivers’ recognition of approaching motorcycles. Experienced drivers completed a series of motorcycle search tasks (training condition) or passively viewed scenes from nature (control) prior to performing a vehicle recognition task from the perspective of a driver approaching a T-junction. Results confirm established findings that drivers perform poorly at recognising motorcycles compared to cars, especially at far distances. However, motorcycle search training had no effect on driver accuracy in recognising approaching vehicles. Training lead to increased response times for recognising approaching cars relative to motorcycles, which could suggest a more thorough consideration of the road scene following training. We conclude that using motorcycle search training to raise the cognitive conspicuity of motorcycles is not effective in increasing their detection from a single delivery of training. Focusing on increasing motorcyclist visibility may be a more effective way to improve driver responses to motorcycles at junctions