Road safety determinants in low and middle income countries

The effect of Real-Time feedback and incentives on speeding behaviors using Telematics: A randomized controlled trial

Speeding behaviour of drivers is highly correlated to their tangible consequence. Therefore, this study aimed to evaluate the effectiveness of telematics-based feedback and financial incentives in reducing speeding behaviors through a randomized controlled field trial. This randomized controlled trial included four groups of (1) control, (2) information-only, (3) gain-of-reward, and (4) loss-of-reward. While drivers of the control group were unobtrusively monitored using telematics devices, drivers of the information-only group received real-time, weekly, and monthly feedback via text message. In both groups with financial incentives, in addition to receiving feedback, drivers could receive payments at the end of each month based on observed speeding. The primary outcome was the distance traveled at speeds more than 10% (S10 + ) above the posted speed limit as a proportion of the total traveled distance. A total of 397 male taxi drivers consented to participate in the study. After the stratified randomization, the mean age of the participant was 46.0 (95% Confidence Interval: 43.8 to 48.2), 47.0 (44.7 to 49.3), 46.1 (43.7 to 48.5), and 48.8 (46.5 to 51.1) years for the control, the information-only, the gain-of-reward, and the loss-of-reward groups, respectively. The mean S10 + rate per 100 km was 0.9 (0.5 to 1.2) for the control, 0.8 (0.4 to 1.1) for the information-only, 0.7 (0.3 to 1.1) for the gain-of-reward, and 1.3 (0.4 to 2.2) for the loss-of-reward group at the start of intervention. During the intervention phase, the loss-of-reward group with 0.6 (0.5 to 0.7) had the lowest mean of S10 + rate, followed by the gain-of-reward group with 0.8 (0.7 to 0.8). The loss-of-reward and gain-of-reward groups were the most influenced groups by the intervention, with 38.0% (13.2 to 55.7; p-value < 0.01) and 29.4% (2.0 to 49.2; p-value = 0.04) less S10 + rate than the control group, respectively. It was figured out that providing information regarding drivers' behavior without appropriating motives or penalties would have a minuscule impact.In addition, the group of drivers who were treated with instant punishment was the most influenced group by the intervention.

Associations between vision impairment and vision-related interventions on crash risk and driving cessation: systematic review and meta-analysis

OBJECTIVES

To systematically investigate the associations between vision impairment and risk of motor vehicle crash (MVC) involvement, and evaluate vision-related interventions to reduce MVCs.

DESIGN

Medline (Ovid), EMBASE and Global Health electronic databases were systematically searched from inception to March 2022 for observational and interventional English-language studies. Screening, data extraction and appraisals using the Joanna Briggs Institute appraisal tools were completed by two reviewers independently. Where appropriate, measures of association were converted into risk ratios (RRs) or ORs for meta-analysis.

PARTICIPANTS

Drivers of four-wheeled vehicles of all ages with no cognitive declines.

PRIMARY AND SECONDARY OUTCOMES

MVC involvement (primary) and driving cessation (secondary).

RESULTS

101 studies (n=778 052) were included after full-text review. 57 studies only involved older drivers (≥65 years) and 85 were in high-income settings. Heterogeneity in the data meant that most meta-analyses were underpowered as only 25 studies, further split into different groups of eye diseases and measures of vision, could be meta-analysed. The limited evidence from the meta-analyses suggests that visual field defects (four studies; RR 1.51 (95% CI 1.23, 1.85); p<0.001; I2=46.79%), and contrast sensitivity (two studies; RR 1.40 (95% CI 1.08, 1.80); p=0.01, I2=0.11%) and visual acuity loss (five studies; RR 1.21 (95% CI 1.02, 1.43); p=0.03, I2=28.49%) may increase crash risk. The results are more inconclusive for available evidence for associations of glaucoma (five studies, RR 1.27 (95% CI 0.67, 2.42); p=0.47; I2=93.48%) and cataract (two studies RR 1.15 (95% CI 0.97, 1.36); p=0.11; I2=3.96%) with crashes. Driving cessation may also be linked with glaucoma (two studies; RR 1.62 (95% CI 1.20, 2.19); p<0.001, I2=22.45%), age-related macular degeneration (AMD) (three studies; RR 2.21 (95% CI 1.47, 3.31); p<0.001, I2=75.11%) and reduced contrast sensitivity (three studies; RR 1.30 (95% CI 1.05, 1.61); p=0.02; I2=63.19%). Cataract surgery halved MVC risk (three studies; RR 0.55 (95% CI 0.34, 0.92); p=0.02; I2=97.10). Ranibizumab injections (four randomised controlled trials) prolonged driving in persons with AMD.

CONCLUSION

Impaired vision identified through a variety of measures is associated with both increased MVC involvement and cessation. Cataract surgery can reduce MVC risk. Despite literature being highly heterogeneous, this review shows that detection of vision problems and appropriate treatment are critical to road safety.

PROSPERO REGISTRATION NUMBER

CRD42020172153.

River dataset as a potential fluvial transportation network for healthcare access in the Amazon region

Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

A Survey of Traumatic Brain Injuries from Road Traffic Collisions in a Lower Middle-Income Country

The burden of traumatic brain injury (TBI) from road traffic collisions (RTCs) is great in low-and middle-income countries (LMICs) due to shortfalls in preventative measures, and the lack of relevant, accurate data collection. To address this gap, we sought to study the epidemiology of TBI from RTCs in two LMIC neurosurgical centres in order to identify factors amenable to preventative strategies. A prospective survey of all adult and paediatric cases of TBI from RTCs admitted to Northwest General Hospital (NWGH) and Hayatabad Medical Complex (HMC) over a four-week period was carried out. Data on patient demographics, risk factors, injury details, pre-hospitalisation details, admission details and post-acute care was collected and analysed. A total of 68 patients were included in the study. 18 (26%) of the patients were male and in the 30 to 39 age group. Fifty-two percent were two-wheeler riders and/or passengers. 51 (75%) of the RTCs occurred between 12 noon and 12 midnight and in rural areas (66.2%). The most commonly documented risk factor that led to the RTC was speeding (35.3%). Pre-hospital care was either absent or undocumented. Up to two-thirds of patients were not direct transfers, and most were transported in private vehicles (48.5%) arriving later than an hour after injury (94.1%). Less than half with documented disabilities were referred for rehabilitation (38.5%). There are still gaps in the prevention of TBI from RTCs and in relevant data collection. Data collection systems must be strengthened, and further exploratory research carried out in order to improve the prevention of TBI from RTCs.

Characteristics, likelihood and challenges of road traffic injuries in China before COVID-19 and in the postpandemic era

Through a review of previous studies, this paper analysed the epidemiological characteristics and attempts to determine the various trends of road traffic injuries (RTIs) in China before and after the coronavirus disease 2019 (COVID-19). This paper proposed effective measures and suggestions for responding to RTIs in China. Moreover, this paper aimed to provide some references for studies on RTIs in the future. According to a reference review, 50 articles related to RTIs were published and viewed in the China National Knowledge Infrastructure (CNKI), Wanfang database, Weipu (VIP) database and PubMed/MEDLINE database. Articles were selected according to the exclusion and inclusion criteria and then classified and summarized. Regarding cases, RTIs in China were highest in summer, autumn, and in rural areas and lowest in February. Men, elderly individuals and people living in rural areas were more susceptible to RTIs. In addition, thanks to effective and proactive policies and measures, the number of RTIs and casualties in China has substantially decreased, while there has been a growing number of traffic accidents along with the increase in nonmotor vehicles. However, it is worth noting that the number of RTIs obviously fell during the COVID-19 pandemic due to traffic lockdown orders and home quarantine policies. Nevertheless, accidents related to electric bicycles increased unsteadily because of the reduction in public transportation use at the same time. The factors that cause RTIs in China can be divided into four aspects: human behaviours, road conditions, vehicles and the environment. As a result, measures responding to RTIs should be accordingly proposed. Moreover, the road traffic safety situation in developing countries was more severe than that in developed countries. RTIs in China showed a downward trend attributed to road safety laws and various policies, and the downward trend was more significant during the COVID-19 pandemic owing to traffic lockdowns and home quarantine measures. It is urgent and necessary to promote road traffic safety, reduce injuries, and minimize the burden of injuries in developing countries.

Identifying high crash risk segments in rural roads using ensemble decision tree-based models

Traffic safety forecast models are mainly used to rank road segments. While existing studies have primarily focused on identifying segments in urban networks, rural networks have received less attention. However, rural networks seem to have a higher risk of severe crashes. This paper aims to analyse traffic crashes on rural roads to identify the influencing factors on the crash frequency and present a framework to develop a spatial-temporal crash risk map to prioritise high-risk segments on different days. The crash data of Khorasan Razavi province is used in this study. Crash frequency data with the temporal resolution of one day and spatial resolution of 1500 m from loop detectors are analysed. Four groups of influential factors, including traffic parameters (e.g. traffic flow, speed, time headway), road characteristics (e.g. road type, number of lanes), weather data (e.g. daily rainfall, snow depth, temperature), and calendar variables (e.g. day of the week, public holidays, month, year) are used for model calibration. Three different decision tree algorithms, including, Decision Tree (DT), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) have been employed to predict crash frequency. Results show that based on the traditional evaluation measures, the XGBosst is better for the explanation and interpretation of the factors affecting crash frequency, while the RF model is better for detecting trends and forecasting crash frequency. According to the results, the traffic flow rate, road type, year of the crash, and wind speed are the most influencing variables in predicting crash frequency on rural roads. Forecasting the high and medium risk segment-day in the rural network can be essential to the safety management plan. This risk will be sensitive to real traffic data, weather forecasts and road geometric characteristics. Seventy percent of high and medium risk segment-day are predicted for the case study.

The economic burden of open tibia fractures: A systematic review

BACKGROUND

Open tibia fractures are a common injury following road traffic collisions and place a large economic burden on patients and healthcare systems. Summarising their economic burden is key to inform policy and help prioritise treatment.

METHODS

All studies were identified from a systematic search of Medline, Embase and the Cochrane Central Register of Controlled Trials. We included any human with a diagnosed open tibia fracture, following any intervention. The primary outcome was any costs reported or patient return to work status. Secondary outcomes included average length of stay, wage loss, absenteeism and complications such as infection, amputation and nonunion. Data was extracted and we performed a descriptive narrative summary.

RESULTS

We reviewed 1,204 studies from our searches. A total of 34 studies were included from 14 different countries. The average age was 37.7 years old and 76% of the patients were male. 6.5% were Gustilo I, 12% Gustilo II and 82% Gustilo III. Initial direct hospitalisation costs were reported to be between £356 to £126,479 with an average length of stay of 56 days (3.1-244). 89% of participants were working pre-injury, 60% fully returned to work, 17% returned to work part time or changed profession and 22% did not return to work at one-year. The most common complications reported were 22% infection, 11% nonunion and 16% amputation. Mean follow-up duration for the studies was 25 months.

CONCLUSION

The economic burden of open tibia fractures varies greatly, but it is costly for both hospitals and patients. The current evidence is predominantly from high-income countries (HICs), especially the USA. Further research is required to investigate the costs of open tibia fractures using validated costing tools, especially in low-income countries (LICs), to help inform and direct policy.

Prevention of road traffic collisions and associated neurotrauma in Colombia: An exploratory qualitative study

INTRODUCTION

Neurotrauma is an important but preventable cause of death and disability worldwide, with the majority being associated with road traffic collisions (RTCs). The greatest burden is seen in low -and middle- income countries (LMICs) where variations in the environment, infrastructure, population and habits can challenge the success of conventional preventative approaches. It is therefore necessary to understand local perspectives to allow for the development and implementation of context-specific strategies which are effective and sustainable.

METHODS

This study took place in Colombia where qualitative data collection was carried out with ten key informants between October and November 2019. Semi-structured interviews were conducted and explored perceptions on RTCs and neurotrauma, preventative strategies and interventions, and the role of research in prevention. Interview transcripts were analysed by thematic analysis using a framework approach.

RESULTS

Participants' confirmed that RTCs are a significant problem in Colombia with neurotrauma as an important outcome. Human and organisational factors were identified as key causes of the high rates of RTCs. Participants described the current local preventative strategies, but were quick to discuss limitations and challenges to their success. Key barriers reported were poor attitudes and knowledge, particularly in the community. Suggestions were provided on ways to improve prevention through better education and awareness, stricter enforcement and new policies on prevention, proper budgeting and resource allocation, as well as through collaboration and changes in attitudes and leadership. Participants identified four key research areas they felt would influence prevention of RTCs and associated neurotrauma: causes of RTCs; consequences and impact of RTCs; public involvement in research; improving prevention.

CONCLUSION

RTCs are a major problem in Colombia despite the current preventative strategies and interventions. Findings from this study have a potential to influence policy, practice and research by illustrating different solutions to the challenges surrounding prevention and by highlighting areas for further research.

Understanding motorcyclist-related accidents in Colombia

In 2016, Colombia's position regarding motorcyclist fatalities per 100,000 inhabitants was tenth worldwide and second in South America. In the seven years from 2012-2018, the proportion of deceased and injured motorcyclists among all road users was 50%. To analyse the significant aspects of the accident rate of motorcyclists in Colombia from 2016 to 2018 and estimate cost social value of motorcycle-related deaths. The global numbers of fatalities and injuries were compared to the Colombian context. Descriptive and inferential statistics were conducted to explore the association of fatal trauma and motorcycle accidents. P values and odds ratios were calculated. Bogotá, Cali, and Medellín were the cities with the most accidents. The month, day, time, age of the victims, and climatic conditions had a statistically significant association with the fatal trauma. Most victims were between the ages of 20-29 years. Motorcycles were involved in more than 60% of accidents. The social cost of a life lost in a motorcycle accident was estimated at $2,418 million Colombian pesos (725,400 USD) per year. The establishment of countermeasures for the road safety of vulnerable users should focus on associated causal factors in order to develop strategies to effectively reduce the number of accidents.

Road Safety in Low-Income Countries: State of Knowledge and Future Directions

Road safety in low-income countries (LICs) remains a major concern. Given the expected increase in traffic exposure due to the relatively rapid motorisation of transport in LICs, it is imperative to better understand the underlying mechanisms of road safety. This in turn will allow for planning cost-effective road safety improvement programs in a timely manner. With the general aim of improving road safety in LICs, this paper discusses the state of knowledge and proposes a number of future research directions developed from literature reviews and expert elicitation. Our study takes a holistic approach based on the Safe Systems framework and the framework for the UN Decade of Action for Road Safety. We focused mostly on examining the problem from traffic engineering and safety policy standpoints, but also touched upon other sectors, including public health and social sciences. We identified ten focus areas relating to (i) under-reporting; (ii) global best practices; (iii) vulnerable groups; (iv) disabilities; (v) road crash costing; (vi) vehicle safety; (vii) proactive approaches; (viii) data challenges; (ix) social/behavioural aspects; and (x) capacity building. Based on our findings, future research ought to focus on improvement of data systems, understanding the impact of and addressing non-fatal injuries, improving estimates on the economic burden, implementation research to scale up programs and transfer learnings, as well as capacity development. Our recommendations, which relate to both empirical and methodological frontiers, would lead to noteworthy improvements in the way road safety data collection and research is conducted in the context of LICs.