Pattern extraction for high-risk accidents in the construction industry: a data-mining approach

Accidents involving falls and falling objects (group I) are highly frequent accidents in the construction industry. While being hit by a vehicle, electric shock, collapse in the excavation and fire or explosion accidents (group II) are much less frequent, they make up a considerable proportion of severe accidents. In this study, multiple-correspondence analysis, decision tree, ensembles of decision tree and association rules methods are employed to analyse a database of construction accidents throughout Iran between 2007 and 2011. The findings indicate that in group I, there is a significant correspondence among these variables: time of accident, place of accident, body part affected, final consequence of accident and lost workdays. Moreover, the frequency of accidents in the night shift is less than others, and the frequency of injury to the head, back, spine and limbs are more. In group II, the variables time of accident and body part affected are mostly related and the frequency of accidents among married and older workers is more than single and young workers. There was a higher frequency in the evening, night shifts and weekends. The results of this study are totally in line with the previous research.     

Quality of life improvements after sports injury

Traffic accidents and their health consequences are a major public health problem in industrialized countries. In addition to being the first cause of death of children up to the age of 14 years, they are also responsible for considerable morbidity. Persistent lesions and more or less disabling sequelae are the lot of a certain number of causalities. In this study, we took stock of all of the information about functional impairment following injuries sustained in traffic accidents that is available in Belgium. We described the ‘itineraries’ of traffic accident patients and identified the potential sources of data. We then analyzed the available and accessible data. Our study shows that we do not have any directly usable data in Belgium that can yield a measure of the public health impact of traffic accidents in terms of temporary and permanent disabilities. Very partial information exists in the country's various institutions and insurance companies, but this information is not suitable for use in a public health approach aimed at quantifying the importance of a health problem and its course over time. We do not feel that the country's main disability measurement tool (BOBI), which is used notably by the insurance companies, attuned to the everyday reality that is experienced by people whose functional abilities have been reduced in the wake of a traffic accident. Given this lack of data, priority should be given to initiating the routine collection of such information or at least to quantifying post-traffic accident disabilities by following up a cohort of traffic accident victims.     

Occupational accidents in the Finnish local government sector: Utilisation of national statistics

Occupational accidents in the Finnish local government sector in 2004 are analysed by gender, age and occupation class in order to identify particular risk groups. The accident data are compared with data concerning the number of employees, using frequency distributions and accident incidence rates. The possibilities of providing occupation class-specific accident incidence rates are also discussed. According to the results, commuting accidents are more common and severe in the local government sector than in general in Finland. In the local public sector occupational accidents more often involved women than men. Compared to other age groups and occupational classes, occupational accidents are more common in the age band of 45–54 and in the occupational class of medical and nursing work. However, compared to the employees' data, men and younger employees had an increased workplace accident risk, while women and older employees had an increased risk of commuting accidents. The highest accident incidence rate was in farming and animal husbandry work. Currently, the calculation of occupation class-specific accident incidence rates is difficult. Improving the consistency of the occupation classifications used in the various data sources would facilitate more reliable calculation of rates.     

Occupational accidents in the Finnish local government sector: utilisation of national statistics

Occupational accidents in the Finnish local government sector in 2004 are analysed by gender, age and occupation class in order to identify particular risk groups. The accident data are compared with data concerning the number of employees, using frequency distributions and accident incidence rates. The possibilities of providing occupation class-specific accident incidence rates are also discussed. According to the results, commuting accidents are more common and severe in the local government sector than in general in Finland. In the local public sector occupational accidents more often involved women than men. Compared to other age groups and occupational classes, occupational accidents are more common in the age band of 45-54 and in the occupational class of medical and nursing work. However, compared to the employees' data, men and younger employees had an increased workplace accident risk, while women and older employees had an increased risk of commuting accidents. The highest accident incidence rate was in farming and animal husbandry work. Currently, the calculation of occupation class-specific accident incidence rates is difficult. Improving the consistency of the occupation classifications used in the various data sources would facilitate more reliable calculation of rates.     

Loglinear model for analysis of cross-tabulated coal mine injury data

Mine accidents/injuries can be cross-classified against the variables of interest in a contingency table and their associations can be assessed through aggregate statistics. However, there is a need to develop a coherent and structured procedure for analysis of accident data, which will allow one to identify associations between two or more variables multivariately. In this study, the loglinear model, which has been proposed as a mathematical representation of the contingency table, was applied to accident data from a group of coal mines to assess the associations/interactions between two or more variables multivariately through their main and interaction effects. The case study results revealed that the variables ‘occupation’ and ‘workplace location’ were highly associated with degree of injury. It was also clearly indicated that the workers with more than 20 years of experience exhibited high injury rate patterns. While designing training programs for miners, focused attention should be given to specific categories of workers to reduce accident/injuries at the case study mines.     

Social inequalities in injury risk in Wales,U.K.

Road traffic accident data in Nigeria generally lack exact coordinate information. Accident analysis is, therefore, restricted to aggregate data on trends, magnitude and temporal dimensions. This article addresses the road accident problem in Jos between 1995 and 1999 through a road profiling approach. Results show that four gateway routes, seven multilane roadways (including two gateway routes) and seven road intersections accounted for 84% of all traffic accidents, 84% of injured casualties and 88% of fatalities. This approach allows for quantification of impacts of controlling for accidents by deliberate profiling of roads for close monitoring and policing. For example, reducing accident counts and fatalities by 50% each on gateway routes will amount to ～35 and 40% reduction in accident and fatality counts, respectively. Countermeasures must consider these roadways and intersections as important inputs in their accidents and casualty reduction targets.     

Swing accidents within the European region

Abstract

This study was conducted to gain greater awareness and understanding of the issues and events which lead to swing accidents; in particular, to provide indices for determining preventive measures concerning swing accidents by means of analyzing accident data. A secondary objective was to find out the potential use for data collected by means of the European Home and Leisure Accident Surveillance System (EHLASS)

All twelve Member States of the European Community in 1993 were asked for information on accidents involving swings recorded by EHLASS. Eight countries provided information on a total of more than 5,000 accidents. Based on this information it was concluded that every year in the European Community about 70,000 people have to be treated at an Accident and Emergency Department for an injury due to a swing, i.e. eleven victims per 10,000 children up to fifteen years of age. On average, half of the accidents involving playground equipment refer to swings. Swing accidents result in general in more severe injuries (based on the proportion of hospital admissions and fractures) than other home and leisure accidents recorded by EHLASS. Three quarters of the accidents refer to falls from a height. The location varies largely from country to country. The most common injuries are arm fractures and contusions of the head. The paper also goes into the differences noted for the countries included in the analyses. It is concluded that accidents involving swings result in severe injuries and form a serious problem, especially for children up to fifteen years of age. Many similarities between the countries were noted, except for the location of the accident. EHLASS has a considerable potential to make a substantial contribution to consumer safety in Europe     

A review of traffic safety status in Abu Dhabi city,UAE (2008–2013)

Large numbers of traffic accidents were experienced on the road networks of Arab Gulf Countries including United Arab Emirates (UAE). This had resulted in enormous loss of lives and economy. This article through using Abu Dhabi city, UAE capital as a case study is aiming to understand the reasons behind such safety problem through analysing a large accidents data-set extending over the period from 2008 to 2013. The traffic accidents data-set was obtained from Abu Dhabi traffic police department records and covers wide range of accident's attributes. A wide spectrum of accident attributes was analysed in the paper including but not limited to the time of accident, accident location, type of accident, reasons behind the accident, driver characteristics, road conditions, and many other accident attributes. A specific reasoning for each of these attributes was given by authors. Furthermore, recommendations to enhance the safety levels were introduced.     

Exploring safety impacts of pedestrian-crossing configurations at signalized junctions on urban roads with public transport routes

This study explored the impacts of pedestrian-crossing configurations and other design features, on accident occurrences at signalized junctions situated on central public transport routes (PTRs) of urban arterials. Statistical tests and negative-binomial regression models were applied to identify factors affecting accidents and to examine accident numbers of the PTR junctions as opposed to comparison-sites. At the PTR junctions, a consistent impact of pedestrian-crossing configurations on accidents was found, where a gradated-crossing with mixed-shifting is the least safe. Four-legged junctions tend to higher accident numbers relative to the three-legged junctions. PTR junctions are characterized by higher accident numbers, related to comparison-sites, when controlling for other design characteristics. The study findings may assist in selecting preferable design solutions while planning PTR.     

Bayesian hierarchical statistics for traffic safety modelling and forecasting

Abstract

Road traffic accidents (RTAs) represent a serious problem globally causing losses in many ways. Gulf Cooperation Council (GCC) countries have a high rate of RTAs compared to other high-income countries. In this study, a Bayesian hierarchical model was utilized for accident counts forecasting in Abu Dhabi, United Arab Emirates. This work will help traffic planners and decision makers to enhance road safety levels and decrease accident fatality rate. Accidents data along 5 years from 2008 to 2012 at 143 road sites in Abu Dhabi with 5,511 accidents were used. The proposed model considered a number of covariates; speed limit, type of road, number of lanes, type of area, weather, time, surface condition and seat belt usage. Five sites with the highest numbers of accidents were studied. Year 2012 was used to validate predictions. The model prediction accuracy was 72%.     

Analyses of non-fatal accidents in an opencast mine by logistic regression model – a case study

Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.     

A risk assessment study on accidents at French level crossings using Bayesian belief networks

Level crossing (LX) safety continues to be one of the most critical issues for railways despite an ever increasing focus on improving design and practices. In the present paper, a framework of probabilistic risk assessment and improvement decision based on Bayesian belief networks (PRAID-BBN) is proposed. The developed framework aims to analyse various impacting factors which may cause LX accidents, and quantify the contribution of these factors so as to identify the crucial factors which contribute most to the LX accidents. A detailed statistical analysis is first carried out based on the accident/incident data. A BBN risk model is established according to the statistical results. Then, we apply the PRAID-BBN framework on the basis of the accident/incident data provided by SNCF, the French national railway operator. The main outputs of our study are conducive to efficiently focusing on the effort/budget to make LXs safer.     

Risk assessment of maintenance operations: the analysis of performing task and accident mechanism

Maintenance operations cover a great number of occupations. Most small and medium-sized enterprises lack the appropriate information to conduct risk assessments of maintenance operations. The objective of this research is to provide a method based on the concepts of task and accident mechanisms for an initial risk assessment by taking into consideration the prevalence and severity of the maintenance accidents reported. Data were gathered from 11,190 reported accidents in maintenance operations in the manufacturing sector of Andalusia from 2003 to 2012. By using a semi-quantitative methodology, likelihood and severity were evaluated based on the actual distribution of accident mechanisms in each of the tasks. Accident mechanisms and tasks were identified by using those variables included in the European Statistics of Accidents at Work methodology. As main results, the estimated risk of the most frequent accident mechanisms identified for each of the analysed tasks is low and the only accident mechanisms with medium risk are accidents when lifting or pushing with physical stress on the musculoskeletal system in tasks involving carrying, and impacts against objects after slipping or stumbling for tasks involving movements. The prioritisation of public preventive actions for the accident mechanisms with a higher estimated risk is highly recommended.     

Retrospective research into accidents

Abstract

In retrospective research into accidents, a victim's or spectator's account of what happened may differ from what actually occurred, as a consequence of memory processes. It seems that, due to limited time and money resources, current insights in retrospective research are not always fully employed in accident research. This paper demonstrates how existing insights into the collection of retrospective data can be incorporated in accident research, and illustrates how this actually works out in practice.

A review of the literature shows that various precautions can be taken to minimize the influences of memory processes. These precautions have been included in the development of a method of accident investigation. Accidents (n=42) were studied in a video-recorded reconstruction on the site, followed by an open interview using a checklist. The accident data have been examined with respect to indications for bias. The findings show that the demonstrations may differ from the unknown actual occurrences, for example, because people were still wearing bandages at the time of investigation on the site. Interference by video- and sound-recordings appears to be limited. Analysis of within-subject differences in repeated demonstrations of the accident shows that more than half of the subjects display differences in the three demonstrations.

The limitations and benefits of the method developed are discussed in relation to conventional methods of accident research, such as mail questionnaires and telephone interviews. The paper concludes with a plea for the inclusion of empirical analyses or at least a discussion of possible bias in findings from accident research.     

Victims of road accidents with serious injuries and dependence on some individual,climatic and infrastructure factors on federal highways in Brazil

Abstract

Road or urban traffic accidents in Brazil have a large presence in external causes of mortality. The main goal of this study is to discover significant factors in the incidence of accidents on Brazilian highways based on a database with information on each person injured on federal highways in Brazil reported by the Federal Highway Police. Some factors are considered in the study as cause of the accident, type of accident, stage of the day, weather condition, highway type, highway facility, age of the victim, gender of the victim and type of vehicle. From the obtained results of chi-square tests and logistic regression models, it was observed statistical dependence (p?<?0.05) of the occurrence of injured people with serious injuries and the factors cause of the accident, type of accident, day, highway type and vehicle type. Considering the dead victims, the covariates age, time of day, highway type, highway facility, gender and type of vehicle showed significance (p?<?0.05). These results are of great interest for authorities to increase road enforcement, improve highway facilities and target the production of vehicles with better safety standards.     

Investigation of adolescent accident predictive variables in hilly regions

The study aims to determine the significant personal and environmental factors in predicting the adolescent accidents in the hilly regions taking into account two cities Hamirpur and Dharamshala, which lie at an average elevation of 700--1000 metres above the mean sea level (MSL). Detailed comparisons between the results of 2 cities are also studied. The results are analyzed to provide the list of most significant factors responsible for adolescent accidents. Data were collected from different schools and colleges of the city with the help of a questionnaire survey. Around 690 responses from Hamirpur and 460 responses from Dharamshala were taken for study and analysis. Standard deviations (SD) of various factors affecting accidents were calculated and factors with relatively very low SD were discarded and other variables were considered for correlations. Correlation was developed using Kendall's-tau and chi-square tests and factors those were found significant were used for modelling. They were – the victim's age, the character of road, the speed of vehicle, and the use of helmet for Hamirpur and for Dharamshala, the kind of vehicle involved was an added variable found responsible for adolescent accidents. A logistic regression was performed to know the effect of each category present in a variable on the occurrence of accidents. Though the age and the speed of vehicle were considered to be important factors for accident occurrence according to Indian accident data records, even the use of helmet comes out as a major concern. The age group of 15–18 and 18–21 years were found to be more susceptible to accidents than the higher age groups. Due to the presence of hilly area, the character of road becomes a major concern for cause of accidents and the topography of the area makes the kind of vehicle involved as a major variable for determining the severity of accidents.     

Safety evaluation model of urban cross-river tunnel based on driving simulation

Currently, Shanghai urban cross-river tunnels have three principal characteristics: increased traffic, a high accident rate and rapidly developing construction. Because of their complex geographic and hydrological characteristics, the alignment conditions in urban cross-river tunnels are more complicated than in highway tunnels, so a safety evaluation of urban cross-river tunnels is necessary to suggest follow-up construction and changes in operational management. A driving risk index (DRI) for urban cross-river tunnels was proposed in this study. An index system was also constructed, combining eight factors derived from the output of a driving simulator regarding three aspects of risk due to following, lateral accidents and driver workload. Analytic hierarchy process methods and expert marking and normalization processing were applied to construct a mathematical model for the DRI. The driving simulator was used to simulate 12 Shanghai urban cross-river tunnels and a relationship was obtained between the DRI for the tunnels and the corresponding accident rate (AR) via a regression analysis. The regression analysis results showed that the relationship between the DRI and the AR mapped to an exponential function with a high degree of fit. In the absence of detailed accident data, a safety evaluation model based on factors derived from a driving simulation can effectively assess the driving risk in urban cross-river tunnels constructed or in design.     

Road accidents involving bicycles: configurations and injuries

This study analyzed the most common types of accident involving bicycles and compared the frequency of injuries. The data source was the database of German In-Depth Accident Study (GIDAS). Cases consist of bicycles and their riders involved in accidents between 2000 and 2010. In most collisions, the bicycle impacted with a car. The percentage of injured bicyclists was higher in collisions with a heavy vehicle and decreased when the bicycle impacted with lighter vehicles. A high percentage of injured bicyclists in single accidents was observed; the most severe injury was more frequently to head and extremities. Accidents involving a car and a bicycle with the right of way in a bicycle path represented about 20% of involved and injured bicyclists. The ten most frequent configurations represented about 60% of involved and injured bicyclists. These results contribute to understand the dangerous scenarios for bicyclists and to suggest preventive actions.     

Safety concerns related to modular/prefabricated building construction

The US construction industry annually experiences a relatively high rate of fatalities and injuries; therefore, improving safety practices should be considered a top priority for this industry. Modular/prefabricated building construction is a construction strategy that involves manufacturing of the whole building or some of its components off-site. This research focuses on the safety performance of the modular/prefabricated building construction sector during both manufacturing and on-site processes. This safety evaluation can serve as the starting point for improving the safety performance of this sector. Research was conducted based on Occupational Safety and Health Administration investigated accidents. The study found 125 accidents related to modular/prefabricated building construction. The details of each accident were closely examined to identify the types of injury and underlying causes. Out of 125 accidents, there were 48 fatalities (38.4%), 63 hospitalized injuries (50.4%), and 14 non-hospitalized injuries (11.2%). It was found that, the most common type of injury in modular/prefabricated construction was ‘fracture’, and the most common cause of accidents was ‘fall’. The most frequent cause of cause (underlying and root cause) was ‘unstable structure’. In this research, the accidents were also examined in terms of corresponding location, occupation, equipment as well as activities during which the accidents occurred. For improving safety records of the modular/prefabricated construction sector, this study recommends that future research be conducted on stabilizing structures during their lifting, storing, and permanent installation, securing fall protection systems during on-site assembly of components while working from heights, and developing training programmes and standards focused on modular/prefabricated construction.