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This study focuses on the safety part of the passing manoeuvre. Passing is considered as one of the most complex, unavoidable and challenging manoeuvres on two lane roads. A binary logistic regression model was developed to determine the probability of passing or aborting based on field data. The result shows that the probability of passing is affected by the factors such as speed of passing vehicle, speed of overtaken vehicle, speed of opposing vehicle, clearance time, and the total passing time. Risk assessment is an important aspect which should be addressed while assessing the passing operations. In the present study, a risk chart was developed based on clearance time and vehicle interaction. An overall risk table was developed for all possible combinations of risk. The study revealed that the selected road stretch along NH-66 in Kerala, India is more susceptible to passing crashes due to insufficient clearance time. This paper brings out a rational methodology for calculating a safety measure in terms of risk index factor which could be used in simulation softwares for adequate passing sight distance operational analysis. [ABSTRACT FROM AUTHOR]

The number of deaths due to road accident is increasing day by day and has become an alarming global problem over the decades. India, with her rising motorization is no stranger to this global catastrophe. In this paper two relatively simple yet powerful and versatile techniques for forecasting time series data, autoregressive integrated moving average method (ARIMA) and exponential smoothing method are used to forecast the number of deaths due to road accidents in India from the year 2022-- 2031. The results based on the two methods are compared and it is found that they are in sync with each other and pre-existing literature. Furthermore, this is a unique attempt to use two time series analysis techniques on the same data and carry out a comparative analysis. The data was collected from the annual report of Ministry of Road Transport and Highways, India (2020) and Accidental Deaths & Suicides in India (ADSI) Report of National Crime Record Bureau (2021). After examining all the probable models, it is observed that ARIMA (2, 2, 2) model and exponential smoothing (M, A, N) model are suitable for the given data. Amongst the two, ARIMA (2, 2, 2) model has a lower AIC and BIC value. Thus, this comes out to be the best model as per our model selection criterion. Further, the study also reveals an upward trend of number of road accidental deaths for the upcoming 10 years in India. [ABSTRACT FROM AUTHOR]

This paper presents the analysis of large mining machinery related accidents in Indian opencast coal mines. The trends of coal production, share of mining methods in production, machinery deployment in open cast mines, size and population of machinery, accidents due to machinery, types and causes of accidents have been analysed from the year 1995 to 2008. The scrutiny of accidents during this period reveals that most of the responsible factors are machine reversal, haul road design, human fault, operator's fault, machine fault, visibility and dump design. Considering the types of machines, namely, dumpers, excavators, dozers and loaders together the maximum number of fatal accidents has been caused by operator's faults and human faults jointly during the period from 1995 to 2008. The novel finding of this analysis is that large machines with state-of-the-art safety system did not reduce the fatal accidents in Indian opencast coal mines. [ABSTRACT FROM AUTHOR]

This paper presents a unique hierarchical structure on various occupational health hazards including physical, chemical, biological, ergonomic and psychosocial hazards, and associated adverse consequences in relation to an underground coal mine. The study proposes a systematic health hazard risk assessment methodology for estimating extent of hazard risk using three important measuring parameters: consequence of exposure, period of exposure and probability of exposure. An improved decision making method using fuzzy set theory has been attempted herein for converting linguistic data into numeric risk ratings. The concept of ‘centre of area’ method for generalized triangular fuzzy numbers has been explored to quantify the ‘degree of hazard risk’ in terms of crisp ratings. Finally, a logical framework for categorizing health hazards into different risk levels has been constructed on the basis of distinguished ranges of evaluated risk ratings (crisp). Subsequently, an action requirement plan has been suggested, which could provide guideline to the managers for successfully managing health hazard risks in the context of underground coal mining exercise. [ABSTRACT FROM PUBLISHER]

Considering the high burden of injuries, the Health Authority - Abu Dhabi developed a draft electronic and paper-based injury and poisoning notification system (IPNS) to generate better data on the nature and severity of injuries. The pilot testing and evaluation of IPNS was conducted with the specific objectives to (1) identify the characteristics of injury cases, (2) explore potential risk factors, (3) illustrate the nature and type of data, and (4) the working mechanism of data collection. Data were collected from selected hospitals on patient demographics, injury information and clinical assessment. Descriptive, bivariate and multivariate analyses were conducted. Of 4226 injury cases, nearly three-fourths were male, majority were non-UAE nationals, and the mean age was 21.9. Multivariate findings suggested that compared to UAE nationals, non-UAE nationals were 27% more likely to experience fatal, severe or moderate injuries (p= 0.01). Individuals with health insurance were 31% less likely to suffer a fatal, severe or moderate injury compared to those having no health insurance (p< 0.001). This is the first systematically standardised collection of injury data across three facilities in Abu Dhabi, and provides initial information on characteristics and injury risk factors that will help identify the need for evidence-based intervention for injury prevention and control. [ABSTRACT FROM PUBLISHER]

Strengthening crash surveillance is an urgent priority for road safety in low- and middle-income countries. We reviewed the online availability and completeness of First Information Reports (FIRs; police reports) of road traffic crashes in India. We developed a relational database to record information extracted from FIRs, and implemented it for one state (Chhattisgarh, 2017–2019). We found that FIRs can be downloaded in bulk from government websites of 15 states and union territories. Another 14 provide access online but restrict bulk downloading, and 7 do not provide online access. For Chhattisgarh, 87% of registered FIRs could be downloaded. Most FIRs reported the date, time, collision-type, and vehicle-types, but important crash characteristics (e.g. infrastructure attributes) were missing. India needs to invest in building the crash surveillance capacity for research and safety management. However, in the interim, maintaining a national database of a sample of FIRs can provide useful policy guidance. [ABSTRACT FROM AUTHOR]

Spousal physical violence (PV) against women is considered to be major health issue in developing countries. Lifetime physical violence is a composite outcome consists of hit, kick, beat, slap and threatened with weapon, perpetrated by the husband. The study aims to examine changes in prevalence and specific risk factors for PV from 1998 to 2016 in India. This study analyzed data from a cross sectional epidemiological survey in 1998–1999, NFHS-3 (2005–2006) and NFHS-4 (2015–2016) data. There was a significant decline of about 10% (95% CI: 8.8%–11.1%) in PV. Major risk factors for change in PV were husband's use of alcohol, illiteracy and socio-economic status of the household. The Protection of Women from Domestic Violence Act may have played a role in reducing the PV. Even though there was a decline in PV, actions have to be implemented from the root level to ensure women empowerment. [ABSTRACT FROM AUTHOR]

Traffic fatalities from 2015 to 2019 in Uttar Pradesh (UP), India show that pedestrians and cyclists have the largest share of total road fatalities. This study analyzed the pedestrian's perceptions of risk in the medium-sized city-Bulandshahr-UP, India regarding the traffic and road features. Perception of risk provides important information in identifying potential risks and explaining travel choices by pedestrians. The study locations were selected based on identified blackspots i.e. clustering of actual fatal crashes during 2015–2019 in UP. The types of locations at the blackspots were intersections below flyover, four-way signalized intersections, midblocks and foot of flyovers. An empirical analysis is presented in the study by taking pedestrians' ranking of the selected risk factors like traffic speed, free left turn at intersections, unmarked crosswalks, median width, traffic volume and the number of lanes and using the Rank-ordered logit model. Traffic speed and median width were ranked as the two highest risk factors by pedestrians. The results also indicated that increased numbers of lanes are more likely to be perceived riskier by older age groups of pedestrians and females at intersections below flyovers and midblocks. A comparison of different locations shows that all the factors were significant at four-way signalized intersections, indicating more perceived risk by pedestrians at intersections. These significant results can be used by practitioners to design safer intersections and midblocks at selected locations for pedestrians in UP, India. [ABSTRACT FROM AUTHOR]

Un-signalized intersections in India witnessed the maximum number of crashes and fatalities in 2019. The nature of the crash investigation is still largely reactive, where the need for accurate and reliable crash data for effective safety diagnosis is pivotal. In India, crash records are unscientific, and critical details are missing. Therefore, a proactive approach using surrogate safety measures is more promising and prudent in analyzing traffic safety. The present study investigates and models crossing conflicts at un-signalized intersections under mixed traffic conditions. Traffic video data for 14 un-signalized intersections (eight un-signalized three-legged intersections and six un-signalized four-legged intersections) were collected under normal weather conditions. The crossing conflicts were identified and characterized as critical and noncritical conflicts based on the values of post-encroachment time (PET). Conflicts with PET values between −1 s and 1 s were identified as critical conflicts. The observation revealed the existence of both positive and negative PET values. The investigation revealed that crossing conflicts with negative PET values are riskier and more unsafe than conflicts with positive ones. Therefore, the crossing conflicts with positive and negative PETs were modeled separately. The positive and negative PET-based critical crossing conflicts are modeled as a function of traffic flow and intersection geometry-related characteristics using truncated negative binomial regression under a full Bayesian modeling framework. K-fold cross-validation with fivefold was employed to calibrate the model, and RMSE was used to find the best model. The modeling results revealed that the volume and traffic composition of the offending and conflicting stream and intersection geometry significantly influence the number of positive and negative PET-based critical crossing conflicts. The developed models can interest engineers and safety experts to analyze traffic safety and identify critical intersections in urban road networks. [ABSTRACT FROM AUTHOR]

Road traffic injuries cost countries 3% of their annual GDP. In developing countries like India, every year around 150,000 people die on roads. The type of vehicles involved in a crash contribute majorly to the outcome of casualty (injury/death). Barring few studies, literature are less regarding the role of vehicle as perpetrator and victim on road crash fatalities. Historical crash data has been used in the present study to examine the role of vehicles (both as perpetrator & victim). The study reveals that victim's effect is more as compared to perpetrator/accused for determining the outcome of crash. Heavy vehicles as perpetrator, and self-hitting vehicles along with pedestrians as victims have higher fatality rates. Binary logistic regression and artificial neural network (ANN) has been utilized for developing prediction models. Binary logistic model predicted around 75% of outcomes correctly with default cut-off value (0.5). However, based on reported crash data, where 19% of total crashes lead to deaths, 0.19 has been proposed as cut-off value which increases the accuracy of the predictions. Accuracy of ANN technique directly depends on the number of crashes reported for a definite pair of perpetrator and victim and the type of validation technique used (Holdback/K-Fold) along with the type of hidden layer chosen for the study based on different types of sigmoid activation function. ROC curves in ANN suggest that the analysis can predict 75% of the outcomes which can be increased by deleting the pairs of vehicles which are present/have occurred in very less number. A comparison has been made between the two techniques based on their advantages and limitations. The developed models can be used as safety indicators based on composition of traffic flow on urban roads. [ABSTRACT FROM AUTHOR]

In India, over 25,000 pedestrian fatalities occur due to road crashes every year. While several studies have identified possible causative factors that contribute to these fatalities, little is known about how pedestrians perceive their surrounding environment. This study attempts to bridge this gap by analysing the pedestrian perception of the built environment and traffic-related aspects considering urban roads (arterial and sub-arterial). Fourteen parameters were selected to assess pedestrian perception, and four factors were derived through factor analysis. The obtained factor scores were then subjected to two-step cluster analysis to determine whether pedestrian perception is different for people from different socio-economic demographics with varying travel behaviour. Based on the results obtained from the descriptive analysis, the respondents were most satisfied with the 'quality of streetlights at sidewalks' and 'visibility/sight distances', while they were most dissatisfied with 'pedestrian volume at sidewalks' and 'lighting facilities at crossings'. From the cluster analysis, it can be summarized that female pedestrians walk less frequently than males and perceive a higher probability of collision or near-collision incidents against male pedestrians. The study findings can aid the policymakers in the assessment of the pedestrian perception of the existing road infrastructure and suggest improvements to ensure pedestrian safety. [ABSTRACT FROM AUTHOR]

Single-vehicle crashes are of major concern in both developed as well as in Low Middle Income Countries due to the severity of injuries, particularly fatal accidents. In India, a significant proportion of crashes are single-vehicle crashes. The vehicles which are involved in accidents due to causes such as self skidding, hitting stationary objects, trees that are simply contributed by the drivers themselves are referred to as out-of-control single-vehicle crashes. The main objective of this study is to evaluate the risk factors associated with single-vehicle motorcycle collisions in Tamilnadu, India and identifies the unique characteristics and injury outcomes associated with these collisions. Crash dataset for the present study was prepared from the police-reported crashes for the past nine years that occurred within the state of Tamilnadu between 2009 and 2017. The identified contributory factors which influence injury severity include driver characteristics, crash-related factors, traffic-related factors, vehicle and environment-related factors. In this study, injury severity is classified into three categories, i.e. fatal, serious, and minor injuries. Since the outcome of the injury severity could be measured on an ordinal scale, a discrete ordered outcome model, an ordered logit model is applied. To summarise the results, thirteen of the studied factors are found to have a significant influence on the injury severity of drivers. Results show that the likelihood of fatal injuries increases in crashes where motorcyclists hit stationary fixed objects, hit trees, ran-off road, inclement weather conditions, urban areas. It is also found that winter season, north districts of Tamilnadu, single and two-lane roads, highways, village roads and, other district roads, daylight conditions, drivers who are younger and working-age group, overtaking from left, taking u-turn are associated with less likelihood of fatal crashes. To increase the overall safety of the roads, targeted countermeasures may be designed in light of injury severity of the drivers with respect to single-vehicle crashes also. This study provides useful insights for reducing injury severity in single-vehicle motorcycle crashes. [ABSTRACT FROM AUTHOR]

Injuries are a major public health concern, affect the most productive age group i.e. (15–60 years) and increases disability adjusted life years (DALYs) and results in a huge financial burden on the household. Disease burden is represented by DALYs and economic burden represents the out of pocket (OOP) and catastrophic health expenditure (CHE). We examined the burden of injury and its impact on household financial burden among the working population (15–60 years) in India. We used data on National and State Level DALYs for Injuries for 2017 from the published National Disease Burden Estimate (NBE, 2019) Study. The cost of treatment was extracted from 75th round of the National Sample Survey Organization (NSSO, 2017–18). DALYs is the sum of YLLs and YLDs. OOPEs were estimated as a per episode of hospitalization expenses after reimbursement and CHE was defined as out of pocket expenditure exceeding 10% of household consumption expenditure. Accidental injuries particularly road traffic injuries have higher DALY rates among 15–60 years in India (1288 DALYs per 100,000). However, the mean OOPE was found to be higher due to intentional self-harm. Persons suffering from injury in states like Punjab, Haryana, UP, Gujarat, Karnataka and Andhra Pradesh approached private facilities more compared to public facilities. Whereas, people from states like Jammu and Kashmir, Orissa, West Bengal, North East availed public facilities more than private. OOPE was found to be five times more in private facilities than in public. The households who sought treatment in private facilities were faced 3 times more to Catastrophic expenditure than those who took the treatment in public hospital of any injury. The present study indicated high DALYs, OOPE and % CHE for injury in India. Higher proportion of households were pushed to catastrophic expenditure due to high OOPE of injury treatment. Disease and economic burden due to road traffic injury and fall was found to be high as compared to other injuries. Our study strengthens the need for executing effective financial protection approach in India like PM-JAY, to minimize the financial burden incurred due to injuries in India. [ABSTRACT FROM AUTHOR]

A major limitation of road injury research in low- and-middle income countries is the lack of consistent data across the settings, such as traffic counts, to measure traffic risk. This study presents a novel method in which traffic volume of heavy vehicles – trucks and buses – is estimated by identifying these vehicles from satellite imagery of Google Earth. For Rajasthan state in India, a total of ∼44,000 such vehicles were manually identified and geo-located on national highways (NHs), with no distinction made between trucks and buses. To estimate population living in proximity to NHs, defined as those living within 1 km buffer of NH, we geocoded ∼45,000 villages and ∼300 cities using Google Maps Geocoding Application Programming Interface (API). We fitted a spatio-temporal Bayesian regression model with the number of road deaths at the district level as the outcome variable. We found a strong Pearson correlation of 0.84 (p < 0.001) between Google Earth estimates of heavy vehicles and freight vehicle counts reported by a national-level study for different road sections. The regression results show that the volume of heavy vehicles and rural population in proximity to highways are positively associated with fatality risk in the districts. These effects have been estimated after controlling for other modes of travel. [ABSTRACT FROM AUTHOR]

Ensuring optimum safety in schools to prevent injuries and promote safety of children is a mandate by the Constitution of India. However, there is limited evidence regarding safety and injury prevention in schools. This safety appraisal was conducted on a sample of 131 schools, selected by stratified random sampling in Bengaluru and Kolar districts in India. Trained investigators collected data using smart phone-assisted interview, observational methods and record review between 1 January and 31 March 2019. Safety was assessed across the domains of macro areas (policy, guidelines, committee, budget, coordination and training), physical infrastructure, road and transport safety, fire safety and first-aid services. Safety level (%) at each school was computed based on scores obtained in each domain. Overall safety level was at 50.8% of the assessment criteria and was relatively better in private schools (54%). Most schools scored less than 30% in domains of transport safety, fire safety and macro areas. Results highlight the need for implementing and augmenting safety measures in schools. [ABSTRACT FROM AUTHOR]

In developing countries, pedestrian safety is an issue of major concern. Although an extensive body of literature is available on the identification of elements related to the pedestrian's risk; the studies are primarily conducted in urban areas of developed countries. The findings from these studies may only be partially relevant to the cities of an emerging country such as India. The present study analyzes historical crash records obtained from the "Kolkata Police" and identifies the risk factors at the road network level for the hazardous corridors posing a high risk to the pedestrians. The study findings reveal that pedestrians' fatalities at intersections are associated with a high vehicular volume, higher pedestrian-vehicular interaction, high approach speed, overtaking tendency of vehicles, certain land-use type, encroachment of footpath, inadequate sight distance, inaccessible pedestrian crosswalk, wider minor carriageway, the absence of a pedestrian signal head, and lack of enforcement. On the other hand, the models outcomes reveal that pedestrians' fatalities at midblock road segments are associated with low pedestrian volume, high approach speed, overtaking tendency of the vehicle, encroachment of footpath, on-street parking, wider road width, certain land-use type, inadequate sight distance, insufficient lighting, and inadequate pavement markings. [ABSTRACT FROM AUTHOR]

Pedestrian safety is of growing concern with an increasing number of traffic accidents, especially in developing economies like India. In 2017, there were 20,457 pedestrian fatalities in India. Pedestrian crashes have also become a key concern in the state of Tamilnadu, India, due to the high percentage of deaths. If the available datasets are large and complex, identifying key factors is a challenging task. In this study, Multiple Correspondence Analysis (MCA), an exploratory data analysis technique was used to explore the roadway, traffic, crash, and pedestrian-related variables influencing pedestrian crashes. This study used the data from Government of Tamilnadu Road Accident Traffic Management System (RADMS) database, to analyse accident data of nine years (2009-2017) related to pedestrian crashes. The results of the study show that crashes occurring on the express highways on a multilane road are often associated with hit-and-run behaviour among drivers. Factors such as lighting conditions, location, pedestrian behaviour, crossings, and physical separation are also significantly contributing to pedestrian crashes. The key advantage of MCA is that it identifies a possible association between various contributing factors. The findings from this study will be useful for state transport authorities to improve countermeasures for mitigating pedestrian crashes and fatalities. [ABSTRACT FROM AUTHOR]

Despite strong advocacy, the UN Decade of Action for Road Safety (2011-2020) is ending with most low- and middle-income countries (LMICs) no closer to the Sustainable Development Goals target of reducing traffic mortality by half. In contrast, most high-income countries (HICs) have seen large benefits in recent decades from large-scale safety interventions. We aimed to assess how much LMICs would benefit from interventions that address six key risk factors related to helmet use, seatbelt use, speed control, drink driving, and vehicle design for safety of occupants and pedestrians. We use a comparative risk assessment framework to estimate mortality and health loss (disability adjusted life years lost, DALYs) that would be averted if these risks were reduced through intervention. We estimate effects for six countries that span all developing regions: China, Colombia, Ethiopia, India, Iran, and Russia. We find relatively large benefits (27% reductions in road traffic deaths and DALYs) from speed control in all countries, and about 5%-20% reductions due to other interventions depending on who is at risk in each country. To achieve larger gains, LMICs would need to move beyond simply learning from HICs and undertake new research to address risk factors particularly relevant to their context. [ABSTRACT FROM AUTHOR]

Injury has been increasing exponentially, especially in children, and it has become a public health concern. The present study was conducted with the objective of determining the prevalence and profile of unintentional injury among children of 1-5-year age group in a rural community of India and also to find out the predictors. Primary caregiver was interviewed by using a structured interview schedule. Parent supervisory behaviour was assessed using Parent Supervision Attributes Profile Questionnaire (PSAPQ), and child injury risk-taking behaviour was assessed by using injury behaviour checklist (IBC). Children encountered any unintentional injury event during last three-month period were 261 (62.7%). PSAPQ score was significantly higher in those parents where children had no episode of injury compared to others. Among four components of the PSAPQ, protectiveness (p = 0.049) and risk tolerance (p = 0.001) score had significant positive association with the incidence of unintentional injury. Binary multivariable logistic regression technique had found that age of the child, gender, primary care giver, birth order of the baby, the number of siblings, social class and IBC score has significant association with history of unintentional injury. There is utmost need for the development of effective programmes and training strategies to prevent unintentional injury among under-five children in future. [ABSTRACT FROM AUTHOR]

Background: Time to hospital after a road traffic crash (RTC) plays a vital role in determining the outcome for crash victims. In Delhi, there are seven designated trauma centres where crash victims are typically taken, which may not be nearest hospital. We compare the transport time access (crash to hospital) depending on whether the victim is transported to a designated trauma centre or the nearest hospital. Data and methods: For each RTC geocoded manually from police records, the nearest hospital and the designated trauma centre is identified using Google Maps places nearby Search API and guidelines. Travel time matrix is generated between RTC's and identified hospitals using Google maps distance matrix API. Index accounting inter-district differences is developed. Results and conclusions: The network of designated trauma centres in New Delhi is located such that they can be accessed within 45 min of most crashes while nearest hospital within 30 min. As a result, the vast majority of crash victims are likely to receive timely care if they are rapidly transferred to either of these caregivers. However, for the most severely injured and time-sensitive cases, bypassing nearest hospital for trauma care, could substantially improve survival outcomes. [ABSTRACT FROM AUTHOR]

Urban intersections in India constitute a significant share of pedestrian fatalities. However, model-based prediction of pedestrian fatalities is still in a nascent stage in India. This study proposes an artificial neural network (ANN) technique to develop a pedestrian fatal crash frequency model at the intersection level. In this study, three activation functions are used along with four different learning algorithms to build different combinations of ANN models. In each of these combinations, the number of neurons in the hidden layer is varied by trial and error method, and the best results are considered. In this way, 12 sets of pedestrian fatal crash predictive models are developed. Out of these, Bayesian Regularization Neural Network consisting of 13 neurons in the hidden layer with 'hyperbolic tangent-sigmoid' activation function is found to be the best-fit model. Finally, based on sensitivity analysis, it is found that the 'approaching speed' of the motorized vehicle has the most significant influence on the fatal pedestrian crashes. 'Logarithm of average daily traffic' (ADT) volume is found to be the second most sensitive variable. Pedestrian-vehicular interaction concerning 'pedestrian-vehicular volume ratio' and lack of 'accessibility of pedestrian cross-walk' are found to be approximately as sensible as 'logarithm of ADT'. [ABSTRACT FROM AUTHOR]

Road safety has emerged as a global concern, and bus stops are the major points of concern as they act as interfaces where pedestrians interact with transit vehicles. In order to achieve a safe and sustainable infrastructure at bus stops, it is necessary to assess safety level of bus stops and suggest safety improvement measures. The present work aims to investigate whether design and management deficiencies of bus stops have any effect on safety of passengers and pedestrians. It is also aimed to develop a pro-active approach for evaluating safety level of bus stops by identifying design and management deficiencies. The methodology includes (i) identification of unsafe acts and causal factors at bus stops, (ii) classification of causal factors under design and management deficiencies, (iii) estimation of weightage of causal factors, (iv) fuzzy evaluation of bus stops, (v) calculation of safety levels of bus stops, and (vi) validation of the methodology using crash data. While a combination of Fuzzy AHP and RIDIT analysis was used to estimate the weightage of causal factors, a fuzzy-scoring-based expert field investigation was carried out to assess design and management deficiencies of bus stops. The methodology was applied to evaluate the safety level of bus stops located along a major urban corridor in Kolkata, India. [ABSTRACT FROM AUTHOR]

Economic loss due to traffic accidents is noticeable in India; however, the country lacks research works to estimate the magnitude. This study is an attempt through a Stated Preference (SP) survey to know how users value safety and how much they are willing to pay (WTP) for a safer road facility to reduce the risk of their involvement in road traffic accidents. The survey was conducted for two-wheeler riders of selected roads in Calicut City. Attributes selected for SP experimental design includes travel time, travel cost and traffic accidents per year and Binary Logit model was used to determine the WTP values. It was observed that travel cost, accident rate of the route selected, age, occupation, personal income and number of household members have significant impact on the decision-making process. WTP value of a road accident for a two-wheeler user was found to be Rs 0.53/person/trip. [ABSTRACT FROM AUTHOR]

Hierarchical clustering analysis framework is developed to identify benchmark and critical regions for effective road safety strategies. The regions are grouped based on agglomeration coefficient of mutually exclusive crash causation parameters. Subsequently, regions from groups with lower than a threshold index value are selected as benchmark for the poorly performing critical counterparts. Euclidean distance-based Ward's, median and centroid clustering techniques are explored through a case study of Indian states and Union Territories. As per data between 2006 and 2015, fatal crash percentages of driving under influence of drug and alcohol, excessive speeding, vehicle malfunction and road conditions related crash causation parameters, severity index and its growth rate are assessed based on respective threshold values of 6.35%, 43.28%, 2.42%, 1.79%, 26.7 and 3.1%. These are the national average of respective indices. It demonstrated the unique application of hierarchical clustering analysis in benchmark and critical region identification. [ABSTRACT FROM AUTHOR]

Large integrated steel plants employ an effective safety management system and gather a significant amount of safety-related data. This research intends to explore and visualize the rich database to find out the key factors responsible for the occurrences of incidents. The study was carried out on the data in the form of investigation reports collected from a steel plant in India. The data were processed and analysed using some of the quality management tools like Pareto chart, control chart, Ishikawa diagram, etc. Analyses showed that causes of incidents differ depending on the activities performed in a department. For example, fire/explosion and process-related incidents are more common in the departments associated with coke-making and blast furnace. Similar kind of factors were obtained, and recommendations were provided for their mitigation. Finally, the limitations of the study were discussed, and the scope of the research works was identified. [ABSTRACT FROM AUTHOR]

A prospective analysis of 104 patients (outdoor and indoor) with manja (powdered glass coated kite string) injury from January 2011 to January 2015 was carried out at Civil Hospital Ahmedabad. All patients were analysed for mode and severity of injury, site of injury, associated injuries, activity being performed when injury occurred, the clinical diagnosis and treatment required. Analysis of collected data revealed that majority of the injuries occurred while driving or in pedestrians with the neck being the most commonly affected body part. Males were more commonly affected with most of the victims in the age group of 16–45 years. Injuries sustained while driving tended to be more severe. All injuries were recorded in the month of January. No deaths were reported, but potentially fatal injuries did occur. Most of the injuries were superficial and could be prevented or mitigated by either protective clothing or by use of protective devices on vehicles, which should be implemented to reduce the morbidity of such injuries in the future. There were no ethical issues or vested interests associated with the study. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

Road traffic injuries (RTIs) are a leading public health problem and the understanding of RTIs in rural India is limited. The present report documents the burden, pattern, characteristics and outcomes of RTIs in a rural district of India using combined data sources: police and hospital. RTIs contributed for 38% of fatal and 39% of non-fatal injuries with an annual mortality rate of 18.1/100,000 population/year. Young males were affected most and two-wheeler users and pedestrians were involved in 45% and 20% of fatal crashes, respectively. Nearly half (51%) of fatal RTIs occurred on national highways of the district; 46% died immediately at the site. Among those hospitalised, 20% were under the influence of alcohol while use of helmets and seat belts was <5%. Trauma care was deficient in the district leading to greater number of referrals. Road safety should be given high importance in rural India with a focus on safe roads, safe vehicles and safe people along with trauma care. [ABSTRACT FROM AUTHOR]

Injuries now rank among the leading causes of morbidity and mortality the world over. Injuries are steadily increasing in developing countries like India. Systematic and scientific efforts in injury prevention and control are yet to begin in India. Data on injuries are very essential to plan preventive and control measures. The objective of this study is to know the profile of the injury cases admitted to M S Ramaiah hospital, Bangalore, India, using a cross-sectional study design for six months, i.e. from Oct 2008 to April 2009. The mean age of the study population was 35.3 years (SD = 15.38), 69.1% were injured in road traffic accidents (RTA), 28.7% due to falls and 2.2% due to burns. Nearly 14.4% were under the influence of alcohol. Nearly 73.6% of RTA cases were two-wheeler users, 48.5% had not followed sign boards and 56.5% had not obeyed the one-way rules, 63.5% of the two-wheeler users did not use helmets. Also, 38% of two wheelers had two pillion riders, whereas 57% of four-wheeler users had not used a seat belt. Among falls, 58% occurred at home, 49% occurred due to slippery surface. Road traffic accidents were the most common cause for injuries, in which two wheelers were most commonly involved. Strict enforcement of traffic rules and education on road safety are very essential to prevent injuries. [ABSTRACT FROM AUTHOR]

This article reports the results of 100% household injury surveillance project conducted over a 1-year period in nine contiguous villages with a total population of 22,883 persons in north India. Fourteen trained field workers did the health and injury survey by visiting 16-20 households every day. In this article, we document the epidemiology of injuries among children in rural households. A person was considered injured if the injury prevented the victim from continuing a normal daily routine as understood by the family and the victim. A total of 2029 injury cases were recorded. Children in the age group 0-14 years accounted for 611 (30%) of all injury cases of which 42% were injured at home (28% for >14 years), 35% on roads (30% for >14 years), 8% on farms (31% for >14 years) and 6% on playgrounds. The maximum number of injuries was due to falls (35%). Eighty per cent of the injuries were minor (Abbreviated Injury Scale (AIS) 1), 18% were moderate or serious (AIS 2-3); none were severe (AIS 4) and one child had a critical injury (AIS 5). The injury rates per 100,000 children in different age groups were 5354, 6962 and 8060 for 0-4, 5-9 and 10-14 years per year. [ABSTRACT FROM AUTHOR]