设施遭恐怖袭击的风险分析方法探讨

“9.11”事件以来 ,恐怖袭击的威胁引起各国政府、媒体和公众的广泛关注 ,预测和减缓恐怖袭击的风险成为安全科学的新课题。笔者依据经典的风险理论 ,探究易受攻击性和损失严重性的概念及其表征参数 ,并通过易受攻击性和损失严重性等级矩阵确定设施遭恐怖袭击的风险水平。     

The contribution of traumatic brain injury to the medical and economic outcomes of motor vehicle-related injuries in Ohio

Objective

To describe traumatic brain injury (TBI) among injured roadway users. Aim 1 assessed the association of age, gender, alcohol/drug use, safety equipment use, type of roadway user, metropolitan area, and primary payer with motor vehicle-related TBI outcome. Aim 2 assessed the relationship of motor vehicle-related TBI and risk/protective factors with medical and economic outcomes.

Methods

Population-level hospital and trauma databases from the Ohio Hospital Association and Ohio Department of Public Safety, respectively, were probabilistically linked for 2003 through 2006. Injured roadway users (motor vehicle occupants, motorcyclists, bicyclists, pedestrians, and others) were assessed for TBI, ventilator use, intensive care unit (ICU) admission, injury severity score (ISS), need for rehabilitation, death, and total hospital charges.

Results

The odds of a motor vehicle-related TBI were greater among those not using safety equipment (OR = 1.56). The interactions of alcohol/drug use by gender and of alcohol/drug use by location were significant. Sustaining a TBI increased the odds of requiring ventilation (OR = 3.66), being admitted to the ICU (OR = 2.51), having a high ISS (OR = 4.24), requiring rehabilitation (OR = 2.22), or death (OR = 2.52). When compared with a non-TBI, total hospital charges increased by a factor of 1.35 for a TBI. Hospital charges were $46,441 on average for individuals who sustained a TBI, whereas mean hospital charges were $32,614 for patients with a non-TBI.

Conclusions

Among injured roadway users, individuals who sustain a TBI are more likely to require extensive medical care and have injuries resulting in death.

Impact on industry

Prevention strategies aimed at reducing alcohol use and increasing safety device use should be encouraged to reduce the burden of TBI.     

Study of the severity of industrial accidents with hazardous substances by historical analysis

This paper studies the levels of risk in industrial facilities where hazardous substances are used, evaluating the influence of certain variables on the severity of the accidents that have occurred until now. It makes use of the incidents recorded in the July 2001 version of the MHIDAS database. This study reveals that accidents in developed countries are less severe than those that occur in other geographical areas. Also, it establishes the influence on the severity (number of fatalities) of this kind of incident of certain factors: the type of incident and the type and amount of substance involved. Lastly, the extent to which current facilities comply to the risk tolerance criteria in various countries is evaluated with regards to incidents involving explosions.     

Injury severity analysis of accidents involving young male drivers in Great Britain

Introduction

Young male drivers are over-represented in traffic accidents; they were involved in 14% of fatal accidents from 1991 to 2003 while holding only 8% of all drivers licenses in the UK. In this study, a subset of the UK national road accident data from 1991 to 2003 has been analyzed. The primary aim is to determine how to best use monetary and progressive resources to understand how road safety measures will reduce the severity of accidents involving young male drivers in both London and Great Britain.

Method

Ordered probit models were used to identify specific accident characteristics that increase the likelihood of one of three categorical outcomes of accident severity: slight, serious, or fatal.

Results

Characteristics found to lead to a higher likelihood of serious and fatal injuries are generally similar across Great Britain and London but are different from those predicted to lead to a higher likelihood of slight injuries. Those characteristics predicted to lead to serious and fatal injuries include driving in darkness, between Friday and Sunday, on roads with a speed limit of 60 mph, on single carriageways, overtaking, skidding, hitting an object off the carriageway, and when passing the site of a previous accident. Characteristics predicted to lead to slight injuries include driving in daylight, between Monday and Thursday, on roads with a speed limit of 30 mph or less, at a roundabout, waiting to move, and when an animal is on the carriageway.

Impact on Industry

These results aid the selection of policy options that are most likely to reduce the severity of accidents involving young male drivers.     

Exploring the severity of bicycle–vehicle crashes using latent class clustering approach in India

IntroductionBicyclists are vulnerable users in the shared asset like roadways. However, people still prefer to use bicycles for environmental, societal, and health benefits. In India, the bicycle plays a role in supporting the mobility to more people at lower cost and are often associated with the urban poor. Bicyclists represents one of the road user categories with highest risk of injuries and fatalities. According to the report by the Ministry of Road Transport and Highways (Accidents, 2017) in India, there is a sharp increase in the number of fatal victims for bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2,585 in 2016 to 3,559 in 2017, a 37.7% increase. Method: Few studies have only investigated the crash risk perceived by the bicyclists while interacting with other road users. The present paper investigates the injury severity of bicyclists in bicycle-vehicle crashes that occurred in the state of Tamilnadu, India during the nine year period (2009–2017). The analyses demonstrate that dividing bicycle-vehicle collision data into five clusters helps in reducing the systematic heterogeneity present in the data and identify the hidden relationship between the injury severity levels of bicyclists and cyclists demographics, vehicle, environmental, temporal cause for the crashes. Results: Latent Class Clustering (LCC) approach was used in the present study as a preliminary tool for the segmentation of 9,978 crashes. Later, logistic regression analysis was used to identify the factors that influence bicycle crash severity for the whole dataset as well as for the clusters that were obtained from the LCC model. Results of this study show that combined use of both techniques reveals further information that wouldn’t be obtained without prior segmentation of the data. Few variables such as season, weather conditions, and light conditions were significant for certain clusters that were hidden in the whole dataset. This study can help domain experts or traffic safety researchers to segment traffic crashes and develop targeted countermeasures to mitigate injury severity.     

The impact of environmental, vehicle and driver characteristics on injury severity in older drivers hospitalized as a result of a traffic crash

INTRODUCTION: Compared to younger age groups, older people are more likely to be seriously injured or to die as a result of a traffic crash. METHOD: The aim of the study is to examine the impact of environmental, vehicle, crash, and driver characteristics on injury severity in older drivers involved in traffic crashes by using recently linked police crash records and hospitalization data from New South Wales, Australia. The severity of injury resulting from traffic crashes was measured using the International Classification of Diseases, 10th revision (ICD-10) Injury Severity Score (ICISS). RESULTS: Multivariate analysis identified rurality, presence of complex intersections, road speed limit, driver error, speeding, and seat belt use as independent predictors of injury severity in older people. The type of intersection configuration explained over half of the observed variations in injury severity. IMPACT ON INDUSTRY: Environmental modification such as intersection treatments might contribute to a decrease in the severity of injury in older people involved in road crashes.     

矿井火灾严重程度评价

频发的矿井火灾造成了重大的人员伤亡和财产损失。对矿井生产安全的风险评价是提高其本质安全程度、减少事故发生的重要手段。笔者通过对矿井火灾燃烧过程与烟流在井巷里流动过程的分析,建立了矿井火灾烟流最高温度、烟流氧气浓度以及污染区域井巷烟流温度的数学模型;给出了用矿井火灾烟流污染范围、烟流中氧气浓度、烟流温度组成的矿井火灾严重程度评价模型;建立了火灾严重程度评价模型的特征线解算方法;并对一个9个分支的矿井通风网络进行了评价计算。