Safer Roads Owing to Higher Gasoline Prices: How Long It Takes

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Road traffic mortality in Iran: longitudinal trend and seasonal analysis, March 2011-February 2020

Road traffic mortalities (RTMs) and injuries are among the leading causes of human fatalities worldwide, particularly in low-and middle-income countries like Iran. Using an interrupted time series analysis, we investigated three interventional points (two government-mandated fuel price increases and increased traffic ticket fines) for their potential relation to RTMs. Our findings showed that while the overall trend of RTMs was decreasing during the study period, multiple individual provinces showed smaller reductions in RTMs. We also found that both waves of government-mandated fuel price increases coincided with decreases in RTMs. However, the second wave coincided with RTM decreases in a smaller number of provinces than the first wave suggesting that the same type of intervention may not be as effective when repeated. Also, increased traffic ticket fines were only effective in a small number of provinces. Potential reasons and solutions for the findings are discussed in light of Iran's Road Safety Strategic Plan.

Modelling the effects of fuel price changes on road traffic collisions in the European Union using panel data

Road deaths globally have steadily climbed in recent years with the increase in motorisation. Yet in many economically developed countries they have actually fallen. Explanations for this reduction include the role of improved vehicle and highway design, better enforcement and the impact of the economic downturn, whilst there is also some evidence that microeconomic factors like changes in road fuel prices could be contributing to this situation. This paper investigates the effects of fuel prices on road collision frequency in countries where fuel prices are relatively high. Monthly panel data from 28 EU member states from 2005 to 2018 was analysed for both petrol and diesel prices, and for fatalities, total injury collisions and total collisions using: 1) random effect negative binomial (RENB); and 2) population-averaged negative binomial using generalised estimating equations (GEE). The findings indicate that higher fuel prices lead to lower road traffic deaths, injury collisions and overall collisions across all 28 EU member states. Thus, for every 10 percent increase in fuel prices, there will be a 2.6 percent and 2.2 percent reduction in fatalities for petrol and diesel models, respectively. Similarly, total collisions fall by 1.4 percent for petrol and 1.2 for diesel models, and total casualties fall by 1.6 percent for petrol and 1.4 percent for diesel with every 10 percent rise in fuel price. These results could be due to drivers reducing speed to achieve better fuel efficiency and to people driving less to save money - in particular younger, riskier drivers - hence reducing exposure. These findings suggest that policies replacing petrol and diesel vehicles with alternative fuel sources over the next 20 years could have negative repercussions for road safety if not adequately considered.

Do higher fuel prices help reduce road traffic accidents?

Road traffic accidents have decreased in most developed nations over the last decade. This has been attributed to improvements in vehicle and road design, medical technology and care, and driver education and training. Recent evidence however indicates that fuel price changes also have a significant impact on road traffic accidents through other mediating factors such as reductions in driver exposure through less car travel and more fuel-efficient driving e.g. speed reduction on high-speed roads. So far though, no study has examined the effects of changing fuel prices on road traffic accidents in a country such as Great Britain where fuel prices are kept artificially high for public policy reasons. Consequently, this study was designed to quantify the effects of fuel price on road traffic accident frequency through changes and adjustments in travel behaviour. For this purpose, weekly fuel prices (between 2005-2015) have been used to study the effects on road traffic accidents using the Prais-Winsten model of first order autoregressive (AR1) and the Box and Jenkins seasonal autoregressive integrated moving average models (SARIMA). The study found that with every 1% increase in fuel price there is a 0.4% reduction in the number of fatal road traffic accidents. In light of this, one concern raised was that recent UK government plans to phase out petrol and diesel vehicles by 2040 may also risk a rise in fatal road traffic accidents, and hence this will need to be addressed.

Texting-While-Driving Bans and Motor Vehicle Crash-Related Emergency Department Visits in 16 US States: 2007-2014

OBJECTIVES

To examine the impact of state texting bans on motor vehicle crash (MVC)-related emergency department (ED) visits.

METHODS

We used ED data from 16 US states between 2007 and 2014. We employed a difference-in-difference approach and conditional Poisson regressions to estimate changes in counts of MVC-related ED visits in states with and without texting bans. We also constructed age cohorts to explore whether texting bans have differential impacts by age group.

RESULTS

On average, states with a texting ban saw a 4% reduction in MVC-related ED visits (incidence rate ratio = 0.96; 95% confidence interval = 0.96, 0.97). This equates to an average of 1632 traffic-related ED visits prevented per year in states with a ban. Both primary and secondary bans were associated with significant reductions in MVC-related visits to the ED regardless of whether they were on all drivers or young drivers only. Individuals aged 64 years and younger in states with a texting ban saw significantly fewer MVC-related ED visits following its implementation.

CONCLUSIONS

Our findings suggest that states' efforts to curb distracted driving through texting bans and decrease its negative consequences are associated with significant decreases in the incidence of ED visits that follow an MVC.

Impact of vision 2030 on traffic safety in Saudi Arabia

Background and objectives

Road traffic accident (RTA) in the Kingdom of Saudi Arabia (KSA) is the first and major cause of death. The primary objective of this paper is to investigate the impact of Saudi Vision 2030 on road traffic safety. The Vision 2030 programs lead to the implementation of two crucial steps. The first step was to introduce value-added tax (VAT), and the second step was to increase fuel prices. The effect of these two steps on RTAs, injuries, and fatalities is determined and evaluated in this study.

Research methods

The data of RTAs, injuries, and fatalities in the last three decades before implementing VAT and before increasing fuel prices were collected and analyzed. A short-term effect of fuel prices was evaluated using the data of 3 months after each increase in fuel price. The results of RTA before the increase in fuel prices were compared with those of RTAs after the increase in fuel prices. Time series autoregressive and t-test were used to analyze the significant differences in the results.

Results and discussion

The results show that RTAs have increased continuously during the last 30 years until the increase in fuel prices. A short-term effect of Vision 2030 and economic transformation were evaluated using RTA data before and after the increase in fuel prices. The remarkable decline in the number of RTAs, injuries, and fatalities after fuel prices increased was recorded.

Conclusion

Despite all the core issues implementing to reduce RTAs, such as traffic law enforcement, RTAs in the KSA increase and become the first cause of death in the country. Vision 2030 leads to an increase in gasoline prices and the implementation of VAT. The increase in gasoline prices contributes to a short-term decrease in RTAs, injuries, and fatalities by 22.4%, 21.9%, and 14.1%, respectively, while intermediate-term decrease in RTAs and road traffic fatalities is by 72892 and 1842, respectively. The decrease in RTAs may be attributed to the reduction in unnecessary trips and slower and careful driving by people to decrease fuel consumption. Statistical analyses performed using time series and t-test confirmed the significant effect of fuel prices on reducing RTAs.

The impact of retail beverage service training and social host laws on adolescents' DUI rates in San Diego County, California

INTRODUCTION

Driving under the influence (DUI) citations are still a serious concern among drivers aged 16-20 years and have been shown to be related to increased risk of fatal and nonfatal crashes. A battery of laws and policies has been enacted to address this concern. Though numerous studies have evaluated these policies, there is still a need for comprehensive policy evaluations that take into account a variety of contextual factors. Previous effort by this research team examined the impact of 20 minimum legal drinking age-21 laws in the state of California, as they impacted alcohol-related crash rates among drivers under 21 years of age while at the same time accounting for alcohol and gas taxes, unemployment rates, sex distribution among drivers, and sobriety checkpoints. The current research seeks to expand this evaluation to the county level (San Diego County). More specifically, we evaluate the impact of measures subject to county control such as retail beverage service (RBS) laws and social host (SH) laws, as well as media coverage, city employment, alcohol outlet density, number of sworn officers, alcohol consumption, and taxation policies, to determine the most effective point of intervention for communities seeking to reduce underage DUI citations.

METHODS

Annual DUI citation data (2000 to 2013), RBS and SH policies, and city-wide demographic, economic, and environmental information were collected and applied to each of the 20 cities in San Diego County, California. A structural equation model was fit to estimate the relative contribution of the variables of interest to DUI citation rates.

RESULTS

Alcohol consumption and alcohol outlet density both demonstrated a significant increase in DUI rates, whereas RBS laws, SH laws, alcohol tax rates, media clusters, gas tax rates, and unemployment rates demonstrated significant decreases in DUI rates.

CONCLUSIONS

At the county level, although RBS laws, SH laws, and media efforts were found to contribute to a significant reduction in DUI rates, the largest significant contributors to reducing DUI rates were alcohol and gas taxation rates. Policy makers interested in reducing DUI rates among teenagers should examine these variables within their specific communities and consider conducting community-specific research to determine the best way to do so. Future efforts should be made to develop models that represent specific communities who are interested in reducing DUI rates among drivers aged 16-20 years.

Methodological development for selection of significant predictors explaining fatal road accidents

Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures.