Objective: This case report highlights the abuse and dependence potential of Zolpidem and the risk of life-threatening withdrawal symptoms upon abrupt discontinuation. Method: We report a case of Zolpidem dependence which presented with withdrawal symptoms upon abrupt discontinuation. Results: A 32 year old male, who had abused non-benzodiazepine Zolpidem for 6 years presented to the accident and emergency unit with generalized seizures upon stopping Zolpidem ‘cold turkey’. He required admission to the neurology high dependency unit for stabilization of the seizures and was later managed by the addiction team where a tapering dose of benzodiazepine was prescribed. Conclusion: This case demonstrates that non-benzodiazepine agents can cause tolerance and dependence, and thus produce withdrawal symptoms upon discontinuation.
There are a number of validated questionnaires available for the screening of Post-Traumatic Stress Disorder (PTSD), and the PTSD Checklist for Civilians is one of them. However, none was translated into the Malay Language and validated for use in the Malaysian population. The aim of this study is to translate and validate the Malay PTSD Checklist for Civilians (MPCL-C). Methods: The PCL-C was translated into the Malay Language and back-translated. The reliability and validity of the MPCL-C were then determined by administering them to those who presented at the emergency department for motor vehicle accident at least one month before. Results: The MPCL-C has good face and content validity. In terms of reliability, it is also good, with Chronbach’s alpha values of 0.90, 0.77, 0.75 and 0.74 for the full scale, re-experiencing, avoidance and arousal domains respectively. Conclusions: The MPCL-C is a valid and reliable instrument to screen for PTSD in motor vehicle accident victims for the studied population.
Level crossings are amongst the most complex of road safety issues, due to the addition of rail infrastructure, trains and train operations. The differences in the operational characteristics of different warning devices together with varying crossing, traffic or/and train characteristics, cause different driver behaviour at crossings. This paper compares driver behaviour towards two novel warning devices (rumble strips and in-vehicle audio warning) with two conventional warning devices (flashing light and stop sign) at railway level crossings using microsimulation modelling. Two safety performance indicators directly related to collision risks, violation and time-to-collision, were adopted. Results indicated the active systems were more effective at reducing likely collisions compared to passive devices. With the combined application of driving simulation and traffic microsimulation modelling, traffic safety performance indicators for a level crossing can be estimated. From these, relative safety comparisons for the different traffic devices are derived, or even for absolute safety evaluation with proper calibration from field investigations.
This paper uses data from an observational study, conducted at access points in straight sections of primary roads in Malaysia in 2012, to investigate the effects of motorcyclists' behavior and road environment attributes on the occurrence of serious traffic conflicts involving motorcyclists entering primary roads via access points. In order to handle the unobserved heterogeneity in the small sample data size, this study applies mixed effects logistic regression with multilevel bootstrapping. Two statistically significant models (Model 2 and Model 3) are produced, with 2 levels of random effect parameters, i.e. motorcyclists' attributes and behavior at Level 1, and road environment attributes at Level 2. Among all the road environment attributes tested, the traffic volume and the speed limit are found to be statistically significant, only contributing to 26-29% of the variations affecting the traffic conflict outcome. The implication is that 71-74% of the unmeasured or undescribed attributes and behavior of motorcyclists still have an importance in predicting the outcome: a serious traffic conflict. As for the fixed effect parameters, both models show that the risk of motorcyclists being involved in a serious traffic conflict is 2-4 times more likely if they accept a shorter gap to a single approaching vehicle (time lag <4s) and in between two vehicles (time gap <4s) when entering the primary road from the access point. A road environment factor, such as a narrow lane (seen in Model 2), and a behavioral factor, such as stopping at the stop line (seen in Model 3), also influence the occurrence of a serious traffic conflict compared to those entering into a wider lane road and without stopping at the stop line, respectively. A discussion of the possible reasons for this seemingly strange result, including a recommendation for further research, concludes the paper.
Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes.
Road safety barriers protect vehicles from roadside hazards by redirecting errant vehicles in a safe manner as well as providing high levels of safety during and after impact. This paper focused on transition safety barrier systems which were located at the point of attachment between a bridge and roadside barriers. The aim of this study was to provide an overview of the behavior of transition systems located at upstream bridge rail with different designs and performance levels. Design factors such as occupant risk and vehicle trajectory for different systems were collected and compared. To achieve this aim a comprehensive database was developed using previous studies. The comparison showed that Test 3-21, which is conducted by impacting a pickup truck with speed of 100 km/h and angle of 25° to transition system, was the most severe test. Occupant impact velocity and ridedown acceleration for heavy vehicles were lower than the amounts for passenger cars and pickup trucks, and in most cases higher occupant lateral impact ridedown acceleration was observed on vehicles subjected to higher levels of damage. The best transition system was selected to give optimum performance which reduced occupant risk factors using the similar crashes in accordance with Test 3-21.
This study presents an analysis of crash characteristics of motorcyclists who sustained spinal injuries in motorcycle crashes. The aim of the study is to identify the salient crash characteristics that would help explain spinal injury risks for motorcyclists. Data were retrospectively collected from police case reports that were archived at MIROS from year 2005 to 2007. The data were categorized into two subcategories; the first group was motorcycle crashes with spinal injury (case) and the second group was motorcycle crashes without spinal injury (control). A total of 363 motorcyclists with spinal injury and 873 motorcyclists without spinal injury were identified and analyzed. Descriptive analysis and multivariate analysis were performed in order to determine the odds of each characteristic in contributing to spinal injury. Single vehicle crash, collision with fixed objects and crash configuration were found to have significant influence on motorcyclists in sustaining spinal injury (p<0.05). Although relatively few than other impact configurations, the rear-end impacted motorcyclist shows the highest risk of spinal injury. Helmets have helped to reduce head injury but they did not seem to offer corresponding protection for the spine in the study. With a growing number of young motorcyclists, further efforts are needed to find effective measures to help reduce the crash incidents and severity of spinal injury. In sum, the study provides some insights on some vital crash characteristics associated with spinal injury that can be further investigated to determine the appropriate counter-measures and prevention strategies to reduce spinal injury.
The benefit of wearing a rear seatbelt in reducing the risk of motor vehicle crash-related fatalities and injuries has been well documented in previous studies. Wearing a seatbelt not only reduces the risk of injury to rear-seat passengers, but also reduces the risk of injury to front-seat occupant who could be crushed by unbelted rear-seat passengers in a motor vehicle crash. Despite the benefits of wearing a rear seatbelt, its rate of use in Malaysia is generally low. The objective of this study was to identify factors that are associated with the wearing of a seatbelt among rear-seat passengers in Malaysia. Multinomial logistic regression analysis of the results of a questionnaire survey of 1651 rear-seat passengers revealed that rear-seat passengers who were younger, male, single and less educated and who had a perception of a low level of legislation enforcement, a lower risk-aversion and less driving experience (only for passengers who are also drivers) were less likely to wear a rear seatbelt. There was also a significant positive correlation between driver seatbelt and rear seatbelt-wearing behaviour. This implies that, in regards to seatbelt-wearing behaviour, drivers are more likely to adopt the same seatbelt-wearing behaviour when travelling as rear-seat passengers as they do when driving. These findings are crucial to the development of new interventions to increase the compliance rate of wearing a rear seatbelt.
Fatigue-related crashes have long been the topic of discussion and study worldwide. The relationship between fatigue-related crashes and time of day is well documented. In Malaysia, the possibility of banning express buses from operating during the early-hours of the morning has emerged as an important consideration for passenger safety. This paper highlights the findings of an impact assessment study. The study was conducted to determine all possible impacts prior to the government making any decision on the proposed banning. This study is an example of a simple and inexpensive approach that may influence future policy-making process. The impact assessment comprised two major steps. The first step involved profiling existing operation scenarios, gathering information on crashes involving public express buses and stakeholders' views. The second step involved a qualitative impact assessment analysis using all information gathered during the profiling stage to describe the possible impacts. Based on the assessment, the move to ban early-hour operations could possibly result in further negative impacts on the overall road safety agenda. These negative impacts may occur if the fundamental issues, such as driving and working hours, and the need for rest and sleep facilities for drivers, are not addressed. In addition, a safer and more accessible public transportation system as an alternative for those who choose to travel at night would be required. The proposed banning of early-hour operations is also not a feasible solution for sustainability of express bus operations in Malaysia, especially for those operating long journeys. The paper concludes by highlighting the need to design a more holistic approach for preventing fatigue-related crashes involving express buses in Malaysia.
Most highly motorized countries in the world have implemented different speed limits for light weight and heavy weight vehicles. The heavy vehicle speed limit is usually chosen to be lower than that of passenger cars due to the difficulty for the drivers to safely maneuver the heavy vehicle at high speed and greater impact during a crash. However, in many cases, the speed limit for heavy vehicle is set by only considering the vehicle size or category, mostly due to simplicity in enforcement. In this study, traffic and vehicular data for all vehicle types were collected using a weigh-in-motion system installed at Federal Route 54 in Malaysia. The first finding from the data showed that the weight variation for each vehicle category is considerable. Therefore, the effect of gross vehicle weight (GVW) and category of heavy vehicle on free flow speed and their interaction were analyzed using statistical techniques. Empirical analysis results showed that statistically for each type of heavy vehicle, there was a significant relationship between free flow speed of a heavy vehicle and GVW. Specifically, the results suggest that the mean and variance of free flow speed decrease with an increase GVW by the amount unrelated to size and shape for all GVW range. Then, based on the 85th percentile principle, the study proposed a new concept for setting the speed limit for heavy vehicle by incorporating GVW where a different speed limit is imposed to the heavy vehicle, not only based on vehicle classification, but also according to its GVW.
Recent empirical research has found that there is an inverted U-shaped or Kuznets relationship between income and motor vehicle crash (MVC) deaths, such that MVC deaths increase as national income increases and decrease after reaching a critical level. Corruption has been identified as one of the underlying factors that could affect this relationship, primarily by undermining institutional development and effective enforcement schemes. The total effect of corruption can be decomposed into two components, a direct and an indirect effect. The direct effect measures the immediate impact of corruption on MVC deaths by undermining effective enforcement and regulations, while the indirect effect captures the impact of corruption on hindering increases in per capita income and the consequent impact of reduced income on MVC deaths. By influencing economic growth, corruption can lead to an increase or decrease in MVC deaths depending on the income level. Using data from 60 countries between 1982 and 2003, these effects are estimated using linear panel and fixed effects negative binomial models. The estimation results suggest that corruption has different direct effects for less developed and highly developed countries. It has a negative (decreasing) effect on MVC deaths for less developed countries and a positive (increasing) effect on MVC deaths for highly developed countries. For highly developed countries, the total effect is positive at lower per capita income levels, but decreases with per capita income and becomes negative at per capita income levels of about US$ 38,248. For less developed countries, the total effect is negative within the sample range and decreases with increased per capita income. In summary, the results of this study suggest that reduction of corruption is likely a necessary condition to effectively tackle road safety problems.
Malaysia has strict laws requiring seat belt use by all vehicle occupants. However, neither passive devices nor inertial reel belts are mandated. Seat belt usage was investigated among 60 taxicab drivers in Kuala Lumpur, Malaysia, in 1993. Although all drivers appeared to be restrained during an initial curb-side inspection, 60% did not fasten the latch. There was no statistical difference between ethnic groups. Curb-side estimates of restraint use may overestimate actual usage, resulting in falsely low estimates of effectiveness. Requiring inertial reel belts, which would retract if not latched, could greatly increase actual restraint use. This may be cost effective for developing nations.
Railway level crossings are amongst the most complex of road safety control systems, due to the conflicts between road vehicles and rail infrastructure, trains and train operations. Driver behaviour at railway crossings is the major collision factor. The main objective of the present paper was to evaluate the existing conventional warning devices in relation to driver behaviour. The common conventional warning devices in Australia are a stop sign (passive), flashing lights and a half boom-barrier with flashing lights (active). The data were collected using two approaches, namely: field video recordings at selected sites and a driving simulator in a laboratory. This paper describes and compares the driver response results from both the field survey and the driving simulator. The conclusion drawn is that different types of warning systems resulted in varying driver responses at crossings. The results showed that on average driver responses to passive crossings were poor when compared to active ones. The field results were consistent with the simulator results for the existing conventional warning devices and hence they may be used to calibrate the simulator for further evaluation of alternative warning systems.
Matched MeSH terms: Accidents, Traffic/prevention & control
Alcohol is a global risk factor for road trauma. Although drink driving has received most of the scholarly attention, there is growing evidence of the risks of alcohol-impaired walking. Alcohol-impaired pedestrians are over-represented in fatal crashes compared to non-impaired pedestrians. Additionally, empirical evidence shows that alcohol intoxication impairs road-crossing judgements. Besides some limited early research, much is unknown about the global prevalence and determinants of alcohol-impaired walking. Understanding alcohol-impaired walking will support health promotion initiatives and injury prevention. The present investigation has three aims: (1) compare the prevalence of alcohol-impaired walking across countries; (2) identify international groups of pedestrians based on psychosocial factors (i.e., Theory of Planned Behaviour (TPB) and perceptions of risk); and (3) investigate how segments of pedestrians form their intention for alcohol-impaired walking using the extended TPB (i.e. subjective norm, attitudes, perceived control, and perceived risk). A cross-sectional design was applied. The target behaviour question was "have you been a pedestrian when your thinking or physical ability (balance/strength) is affected by alcohol?" to ensure comparability across countries. Cluster analysis based on the extended TPB was used to identify groups of countries. Finally, regressions were used to predict pedestrians' intentions per group. A total of 6,166 respondents (Age M(SD) = 29.4 (14.2); Males = 39.2%) completed the questionnaire, ranging from 12.6% from Russia to 2.2% from Finland. The proportion of participants who reported never engaging in alcohol-impaired walking in the last three months ranged from 30.1% (Spain) to 83.1% (Turkey). Four groups of countries were identified: group-1 (Czech Republic, Spain, and Australia), group-2 (Russia and Finland), group-3 (Japan), and group-4 (final ten countries including Colombia, China, and Romania). Pedestrian intentions to engage in alcohol- impaired walking are predicted by perceptions of risk and TPB-psychosocial factors in group-1 and group-4. Favourable TPB-beliefs and low perceived risk increased alcohol-impaired walking intentions. Conversely, subjective norms were not significant in group-2 and only perceived risk predicted intention in group-3. The willingness of pedestrians to walk when alcohol-impaired differs significantly across the countries in this study. Perceived risk was the only common predictor among the 16 countries.
Motorcyclists are particularly vulnerable to injury in crashes with heavy vehicles due to substantial differences in vehicle mass, the degree of protection and speed. There is a considerable difference in height between motorcycles and trucks; motorcycles are viewed by truck drivers from downward angles, and shorter distances between them mean steeper downward angles. Hence, we anticipated that the effects of motorcycle conspicuity treatments would be different for truck drivers. Therefore, this study aims to evaluate the effects of motorcycle conspicuity treatments on the identification and detection of motorcycles by truck drivers. Two complementary experiments were performed; the first experiment assessed the impact of motorcycle sensory conspicuity on the ability of un-alerted truck drivers to detect motorcycles, and the second experiment assessed the motorcycle cognitive conspicuity to alerted truck drivers. The sensory conspicuity was measured in terms of motorcycle detection rates by un-alerted truck drivers when they were not anticipating a motorcycle within a realistic driving scene, while the cognitive conspicuity was determined by the time taken by alerted truck drivers to actively search for a motorcycle. In the first experiment, the participants were presented with 10 pictures and were instructed to report the kinds of vehicles that were presented in the pictures. Each picture was shown to the participants for 600ms. In the second experiment, the participants were presented with the same set of pictures and were instructed to respond by clicking the right button on a mouse as soon as they detected a motorcycle in the picture. The results indicate that the motorcycle detection rate increases, and the response time to search for a motorcycle decreases, as the distance between the targeted motorcycle and the viewer decreases. This is true regardless of the type of conspicuity treatment used. The use of daytime running headlights (DRH) was found to increase the detection rate and the identification of a motorcycle by a truck driver at a farther distance, but effect deteriorates as the distance decreases. The results show that the detection rate and the identification of a motorcyclist wearing a black helmet with a reflective sticker increases as the distance between the motorcycle and the truck decreases. We also found that a motorcyclist wearing a white helmet and a white outfit is more identifiable and detectable at both shorter and longer distances. In conclusion, although this study provides evidence that the use of appropriate conspicuity treatments enhances motorcycle conspicuity to truck drivers, we suggest that more attention should be paid to the effect of background environment on motorcycle conspicuity.
Failure in making the correct judgment about the intention of an approaching vehicle at a junction could lead to a collision. This paper investigated the impact of dynamic information on drivers' judgments about the intentions of approaching cars and motorcycles, and whether a valid or invalid signal was provided was also manipulated. Participants were presented with videoclips of vehicles approaching a junction which terminated immediately before the vehicle made any manoeuvre, or images of the final frame of each video. They were asked to judge whether or not the vehicle would turn. Drivers were better in judging the manoeuvre of approaching vehicles in dynamic than static stimuli, for both vehicle types. Drivers were better in judging the manoeuvre of cars than motorcycles for videos, but not for photographs. Drivers were also better in judging the manoeuvre of approaching vehicles when a valid signal was provided than an invalid signal, demonstrating the importance of providing a valid signal while driving. However, drivers were still somewhat successful in their judgments in most of the conditions with an invalid signal, suggesting that drivers were able to focus on other cues to intention. Finally, given that dynamic stimuli more closely reflect the demands of real-life driving there may be a need for drivers to adopt a more cautious approach while inferring a motorcyclist's intentions.
According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables.
Road safety in rural mountainous areas is a major concern as mountainous highways represent a complex road traffic environment due to complex topology and extreme weather conditions and are associated with more severe crashes compared to crashes along roads in flatter areas. The use of crash modelling to identify crash contributing factors along rural mountainous highways suffers from limitations in data availability, particularly in developing countries like Malaysia, and related challenges due to the presence of excess zero observations. To address these challenges, the objective of this study was to develop a safety performance function for multi-vehicle crashes along rural mountainous highways in Malaysia. To overcome the data limitations, an in-depth field survey, in addition to utilization of secondary data sources, was carried out to collect relevant information including roadway geometric factors, traffic characteristics, real-time weather conditions, cross-sectional elements, roadside features, and spatial characteristics. To address heterogeneity resulting from excess zeros, three specialized modelling techniques for excess zeros including Random Parameters Negative Binomial (RPNB), Random Parameters Negative Binomial - Lindley (RPNB-L) and Random Parameters Negative Binomial - Generalized Exponential (RPNB-GE) were employed. Results showed that the RPNB-L model outperformed the other two models in terms of prediction ability and model fit. It was found that heavy rainfall at the time of crash and the presence of minor junctions along mountainous highways increase the likelihood of multi-vehicle crashes, while the presence of horizontal curves along a steep gradient, the presence of a passing lane and presence of road delineation decrease the likelihood of multi-vehicle crashes. Findings of this study have significant implications for road safety along rural mountainous highways, particularly in the context of developing countries.
The existing literature in road safety revealed that the relationship between motorcycle deaths and per-head income follows a Kuznets or reverse U-curve pattern, whereby motorcycle deaths incline at lower income levels but decline once the per-head income has exceeded a threshold level. The same reverse U-curve relationship was also observed between per-head income and other road injury-related variables, including road deaths, road injuries, as well as road deaths to road injuries ratio. Evidence showed that motorcycles and passenger cars are the dominant vehicle modes and contributed significantly to global road deaths. The main objective of this study is to examine the relationship between the motorcycle deaths to passenger car deaths (MDC) ratio and per-head Gross Domestic Product (GDP). Examining the relationship between the MDC ratio and GDP per capita can be effective in understanding the relative change between motorcycle and passenger car deaths at different economic development stages, as well as identifying appropriate preventive measures. We apply a panel linear regression analysis on a panel of 38 countries over the period 1965-2013. Result demonstrated that there is a reverse U-curve relationship between the MDC ratio and the logarithm of GDP per capita. This implies that, at lower levels of GDP per capita, motorcycle deaths were more prevalent than passenger car deaths, whereas as the level of GDP per capita rises, passenger car deaths became relatively prevalent than motorcycle deaths. Moreover, there is a reverse U-shaped relationship between motorcycle ownership to passenger car ownership ratio (MPC) and the MDC ratio, while a U-shaped relationship exists between relative growth in higher mobility roads as compared to higher accessibility roads (MPA) and the MDC ratio. Based on our results, policies and interventions to reduce motorcycle and passenger car deaths were suggested in the conclusion of the paper.
Most of the decisions taken to improve road safety are based on accident data, which makes it the back bone of any country's road safety system. Errors in this data will lead to misidentification of black spots and hazardous road segments, projection of false estimates pertinent to accidents and fatality rates, and detection of wrong parameters responsible for accident occurrence, thereby making the entire road safety exercise ineffective. Its extent varies from country to country depending upon various factors. Knowing the type of error in the accident data and the factors causing it enables the application of the correct method for its rectification. Therefore there is a need for a systematic literature review that addresses the topic at a global level. This paper fulfils the above research gap by providing a synthesis of literature for the different types of errors found in the accident data of 46 countries across the six regions of the world. The errors are classified and discussed with respect to each type and analysed with respect to income level; assessment with regard to the magnitude for each type is provided; followed by the different causes that result in their occurrence, and the various methods used to address each type of error. Among high-income countries the extent of error in reporting slight, severe, non-fatal and fatal injury accidents varied between 39-82%, 16-52%, 12-84%, and 0-31% respectively. For middle-income countries the error for the same categories varied between 93-98%, 32.5-96%, 34-99% and 0.5-89.5% respectively. The only four studies available for low-income countries showed that the error in reporting non-fatal and fatal accidents varied between 69-80% and 0-61% respectively. The logistic relation of error in accident data reporting, dichotomised at 50%, indicated that as the income level of a country increases the probability of having less error in accident data also increases. Average error in recording information related to the variables in the categories of location, victim's information, vehicle's information, and environment was 27%, 37%, 16% and 19% respectively. Among the causes identified for errors in accident data reporting, Policing System was found to be the most important. Overall 26 causes of errors in accident data were discussed out of which 12 were related to reporting and 14 were related to recording. "Capture-Recapture" was the most widely used method among the 11 different methods: that can be used for the rectification of under-reporting. There were 12 studies pertinent to the rectification of accident location and almost all of them utilised a Geographical Information System (GIS) platform coupled with a matching algorithm to estimate the correct location. It is recommended that the policing system should be reformed and public awareness should be created to help reduce errors in accident data.