The effects of economic stress and urbanization on driving behaviours of Boda-boda drivers and accidents in Gulu, Northern Uganda: a qualitative view of drivers

A systematic review of risk factors associated with road traffic crashes and injuries among commercial motorcycle drivers

To effectively reduce road traffic crashes (RTCs) and injuries interventions should be based on firm evidence regarding risk factors of RTCs and injuries in that specific population. Therefore, we undertook a systematic review to determine risk factors of RTCs and injuries among commercial motorcycle drivers. Searches were performed from inception to May 2022 in Medline, Embase, Cochrane Library, Web of Science Core Collection, PsycINFO and Cinahl, along with registers and reference lists. Inclusion criteria were commercial motorcycle drivers, quantitative observational studies, and RTCs and injuries. The search resulted in 1546 articles, of which 20 met the relevance and quality criteria. Of the 20 articles, 17 were cross-sectional, 2 were case-control studies, and one was a cohort study. Close to half of all articles (9) came from sub-Saharan Africa. Risk factors with consistent association with RTCs and injuries were young age, low education level, alcohol consumption, speeding, mobile phone use, non-helmet use, risky driving behaviours and long working hours. There was inconclusive evidence for driver's training, work schedules, motorcycle ownership, experience, dependents number, and marital status. More robust designs such as case-control or longitudinal studies are required to gain a comprehensive understanding of the antecedents of RTCs among commercial motorcycle drivers.

Risk chain identification of single-vehicle accidents considering multi-risk factors coupling effect

The real-time monitoring on the risk status of the vehicle and its driver can provide the assistance for the early detection and blocking control of single-vehicle accidents. However, complex risk coupling relationship is one of the main features of single-vehicle accidents with high mortality rate. On the basis of investigating the coupling effect among multi-risk factors and establishing a safety management database throughout the life cycle of vehicles, single-vehicle driving risk network (SVDRN) with a three-level threshold was developed, and its topology features were analyzed to assessment the importance of nodes. To avoid the one-sidedness of single indicator, the multi-attribute comprehensive evaluation model was applied to measure the comprehensive effect of characteristic indicators for nodes importance. A algorithm for real-time monitoring of vehicle driving risk status was proposed to identify key risk chains. The result revealed that improper operation, speeding, loss of vehicle control and inefficient driver management were the sequence of top four risk factors in the comprehensive evaluation result of nodes importance (mean value = 0.185, SD = 0.119). There were minor differences of 0.017 in the node importance among environmental factors, among which non-standard road alignment had the larger value. The improper operation and non-standard road alignment were the highest combination correlation of factors affecting road safety, with the support of 51.81% and the confidence of 69.35%. This identification algorithm of key risk chains that combines node importance and its risk state threshold can effectively determine the high-frequency risk transmission paths and risk factors through multi-vehicle test, providing a basis for centralization management of transport enterprises.

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Background

The adherence to speed limits can reduce deaths associated with road traffic injuries (RTIs) by more than a quarter. This study aimed to evaluate the effective factors on the speeding behavior of Iranian taxi drivers around fixed speed cameras.

Method

Telematics devices used in this study collected the location and speed of the vehicles. The units of analysis in this study were trips per camera, including 2.5 km before and after each camera. Linear regression analysis was used to identify kangaroo driving (KD), defined as trips with a significant V-shape in speed distribution around the camera. In the clustered camera zones, cameras were placed at regular intervals of approximately 3.5 km.

Findings

A total of 93,160 trips were recorded from 13,857,443 data points. There was an inverse association between drivers' age and KD with an odds ratio (OR) of 0.98 (95% confidence interval: 0.98-0.98). The intercity trips had a substantially higher probability of KD than urban trips (OR: 4.94 [4.73-5.16]). The tendency of drivers toward KD during the daylight hours vs. nighttime was significant for both urban (OR: 1.15 [1.06-1.25]) and intercity (OR: 1.18 [1.14-1.22]) trips. The 4 -8 a.m. period had the highest chance of KD in both urban (10.71% [7.41-14.53]) and intercity (44.13% [41.18-47.09]) trips. There was a significant decrease in the odds of KD inside the clustered camera zones (OR: 0.22 [0.20-0.25]).

Conclusion

The heterogeneous occurrence of KD in different locations and times indicates the necessity of evidence-based decision-making in urban planning to improve safe driving behaviors. The lower occurrence of KD in clustered camera zones could be a practical key to the effective control of speeding behaviors by helping in the efficient placement of cameras through sustainable development of cities and roads.

A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations

With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011-2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.

Humanitarian Surgical Missions in Times of COVID-19: Recommendations to Safely Return to a Sub-Saharan Africa Low-Resource Setting

Background

Since the declaration of the pandemic, humanitarian medicine has been discontinued. Until now, there have been no general recommendations on how humanitarian surgical missions should be organized.

Methods

Based on our experience in the field of humanitarian surgical missions to Sub-Saharan Africa, a panel of recommendations in times of COVID-19 was developed. The fields under study were as follows: (1) Planning of a multidisciplinary project; (2) Organization of the infrastructure; (3) Screening, management and treatment of SARS-COV-2; (4) Diagnostic tests for SARS-COV-2; (5) Surgical priorization and (6) Context of patients during health-care assistance. We applied a risk bias measurement to obtain a consensus among humanitarian health-care providers with experience in this field.

Results

A total of 94.36% of agreement were reached for the approval of the recommendations. Emergency surgery must be a priority, and elective surgery adapted. For emergency surgery, we established a priority level 1a (< 24 h) and 1b (< 72 h). For an elective procedure, according our American College of Surgeon adaptation score, process with more than 60 points should be reconsidered. Due to the low life expectancy in many African countries, we consider 45–50 years as age of risk. In case of SARS-COV-2 active infection or high clinical suspicion, the screening, management and treatment should be following the international guidelines adapted to duration of the stay, available infrastructure, size of the cooperation team and medical resources.

Conclusions

Humanitarian surgical mission in times of COVID-19 is a challenge that must extrapolate the established recommendations to the local cooperation environment.

Supplementary Information

The online version contains supplementary material available at (10.1007/s00268-021-06001-x).