Pedestrian risk perception of marked and unmarked crosswalks in Kumasi, Ghana

Pedestrians constitute the majority of all urban road crashes in Ghana, yet there is inadequate supply of pedestrian facilities, and road-user behaviours have been cited as a major contributing factor to the high crash rates. This study seeks to investigate how pedestrians perceive risk at different crosswalks. The study adopted a mixed-method approach, where secondary crash data for 30 selected crosswalks was correlated with corresponding primary data that consisted of pedestrian surveys. The crash data from 2011 through 2014 was obtained from the database of the Building and Road Research Institute of the Council for Scientific and Industrial Research (CSIR-BRRI) in Kumasi, and supplemented with a survey of 900 pedestrians. The results revealed that pedestrians perceived marked crosswalks to be safer than unmarked crosswalks, but this is contrary to the crash records. Also, most of the crashes were registered for crosswalks located across multilane highways. In light of these results, it is recommended that the safety features of crosswalks be re-examined, while restricting indiscriminate crossing by channelling pedestrians to designated protected crossing points, installing traffic control devices and other speed-calming devices at identified high-risk crosswalks, and signalising crosswalks that are located on multilane roads. It is also recommended to intensify road safety campaigns and public education on safe road-crossing practices, while enforcing traffic safety laws to influence road-user behaviours

Exploratory Analysis of Recent Trends in School Travel Mode Choices in the U.S.

The study explores the recent trends in school travel using the 2017 National Household Travel Survey data. The study also investigates the exogenous factors affecting the school travel mode choice using random parameters multinomial logit (RPMNL) model. The results indicate that urban school trips range between 3 and 5 miles, whereas, average rural trips are longer than 6 miles. School commute times are higher among lower-income households. Further, the share of school bus and auto has declined while that of walking and biking has increased in 2017. This change is significant among high school students. Like other studies, the findings of the RPMNL model confirm that students within shorter distances from school are more likely to walk or bike to school. However, the likelihood of riding a school bus for distances \u3e15 miles is higher than that of auto, indicating a policy implication to support school transportation budgets, especially in rural school districts. Lower-income households have a higher likelihood of riding the school bus. Females are more likely to use a car and less likely to bike to school. Interestingly, households with more than three vehicles are more likely to use the school bus compared to no-vehicle households. Children living in rented houses are less likely to ride the school bus or car. Also, an increase in gas price is indirectly but positively linked with walking, biking, and auto use. The findings from this study will assist policymakers in formulating policies and planning decisions towards improvements in the current school travel trends

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Gendered Analysis of Fatal Crashes among Young Drivers in Alabama, USA

As part of broader research efforts to understand the factors contributing to crashes involving younger drivers, it is important to characterize the crash contributing factors of the at-fault younger drivers. This study applied latent class analysis (LCA) to identify subgroups with statistically distinct patterns in the contributing factors of fatal crashes involving young male and female drivers in Alabama. Model estimation results reveal that crashes on rural roads are a serious issue in Alabama. It was also observed that a high proportion of the young driver fatal crashes occurred on weekends and closer to the driver’s place of residence. Interestingly, the proportion of crashes involving speeding increased with age for males and decreased with age for females. In general, younger female drivers (15–18 years) were more likely to be involved in speed and aggressive driving related fatal crashes than their male counterparts. Also, fatal crashes involving driving under influence (DUI) increase with age for both male and female drivers, with a significant increase for drivers between 19 and 21 years of age. These study findings suggest that specific attention should be focused towards younger drivers in rural communities and communities with lower socioeconomic opportunities. Targeted education and outreach campaigns, combined with appropriate enforcement efforts could meaningfully change the attitudes and behaviors related to road safety

Exploratory Applications of Epidemiological Methods in Transport Safety and Mobility

Evident similarities and links between the outcomes of traffic crashes and stranded (or constrained) mobility have been identified and are reported in this research. Generally, a high level of travel activities is an indicator of high crash exposure. However, studies have shown that the highest rates of traffic fatalities occur in low- and middle-income regions, where many citizens experience relatively low levels of motorized travel. This ironic observation reveals serious challenges facing transport mobility systems in the less privileged regions of the world. Studies on traffic crashes and mobility constraints also reveal that they both have individual and regional variations in their occurrence, effects, and severities. Consequently, the outcomes of traffic crashes and constrained mobility are serious public health concerns worldwide. As public health problems, their study is analogous to the study of diseases and other injuries and thus, suitable for the application of epidemiological techniques. This dissertation therefore explores the use of epidemiological techniques to analyze traffic crashes and mobility/accessibility constraints from a human-centered perspective. The dissertation therefore consists of two major focus areas. The first part of the study applies widely used epidemiology/public health – based statistical tools to analyze traffic crashes with the aim of gaining better understanding of the human-centered causes and factors that influence these causes, and how these ultimately affect the severity of crashes. This part is further divided into two sub-sections. The first sub-section used latent class analysis to identify homogeneous clusters of human-centered crash causal factors and then applied latent class logit and random parameters logit modeling techniques to investigate the effects of these factors on crash outcomes. The second sub-section of the first part of the dissertation applies multilevel regression analysis to understand the effects of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across sub-regions. Both studies are necessary to develop potential human-centered mitigations and interventions and for the effective and targeted implementation of those countermeasures. The second part of the study provides an epidemiological framework for addressing mobility/accessibility constraints with a view to diagnosing symptoms, recommending treatment, and even discussing the idea of transmission of constrained mobility among city dwellers. The medical condition, hypomobility, has been used to connote constrained mobility and accessibility for people in urban areas. In transportation and urban studies, hypomobility can result in a diminished ability to engage in economic opportunities and social activities, hence deepening poverty and social exclusion and increasing transport costs, among other negative outcomes. The condition is especially pronounced in poor urban areas in developing countries. The framework proposed in this study is expected to help identify and address barriers to mobility and accessibility in the rapidly growing cities throughout the developing world, with particular applicability to the rapidly developing cities in Sub-Saharan Africa. Ultimately, this dissertation explores the application of epidemiological techniques to two major transportation problems: traffic safety and constrained mobility. The techniques presented in this dissertation provide policy makers, agencies, and transport professionals with tools for evidence-based policies and effective implementation of appropriate countermeasures

Effects of Human-Centered Factors on Crash Injury Severities

Factors related to drivers and their driving habits dominate the causation of traffic crashes. An in-depth understanding of the human factors that influence risky driving could be of particular importance to facilitate the application of effective countermeasures. This paper sought to investigate effects of human-centered crash contributing factors on crash outcomes. To select the methodology that best accounts for unobserved heterogeneity between crash outcomes, latent class (LC) logit model and random parameters logit (RPL) model were developed. Model estimation results generally show that serious injury crashes were more likely to involve unemployed drivers, no seatbelt use, old drivers, fatigued driving, and drivers with no valid license. Comparison of model fit statistics shows that the LC logit model outperformed the RPL model, as an alternative to the traditional multinomial logit (MNL) model

Severity analysis of crashes involving in-state and out-of-state large truck drivers in Alabama: A random parameter multinomial logit model with heterogeneity in means and variances

The trucking sector contributes significantly to the economic vitality of the United States. Large trucks are primarily used for transporting goods within and across states. Despite its economic importance, large truck crashes constitute public safety concerns. To minimize the consequences, there is a need to understand the factors that contribute to the severity outcomes of truck-involved crashes. Since many large truck drivers transport goods across several states, the driver-centered crash factors are expected to differ between in-state and out-of-state drivers. For this reason, this study developed two random parameters multinomial logit models with heterogeneity in means and variances to examine the factors contributing to the severity of crashes involving in-state and out-of-state large truck drivers in Alabama. The study was based on the 2016–2020 large truck crashes in Alabama. After data cleaning and preparation, it was observed that approximately 20% of in-state and 23% of out-of-state large truck crashes were fatigue-related. There were more speeding related crashes (12.4%) among in-state large truck drivers, but the contribution of speeding to crash severity outcomes was only significant in the out-of-state model. More crashes related to red light running violation (14.2%) were observed among out-of-state drivers, pointing to the fundamental issues of fatigue and unfamiliarity with the operations of signalized intersections in Alabama. The study contributes to the literature on large truck crashes by uncovering the nuances in crashes involving in-state and out-of-state large truck drivers. Despite the seeming similarity in factors that influence crash outcomes, this study provides the basis for truck drivers’ training and communication campaigns on the differences that may exist in roadway characteristics from state to state. Also, policy formulations and strategies that prioritizes the well-being of the large truck drivers and creates a better working condition for them should be explored

Crash severity analysis of single-vehicle rollover crashes in Namibia: A mixed logit approach

Road traffic crashes are a leading cause of serious injuries and fatalities globally and place unnecessary developmental and economic burdens on low- and middle-income countries (LMIC) as they account for the vast majority of the world's road related deaths. This is typically due to both the increased frequency of dangerous crash types and the increased severity of said crash types. Rollover crashes while quite rare are a particularly dangerous crash type among other various crash types. In the case of Namibia, rollover crashes reportedly accounted for 34% of both road related injuries and fatalities in Namibia for 2020. When compared to high-income countries the issue of rollover crash severity in Namibia and like sub-Saharan African (SSA) countries becomes apparent. Therefore, it crucial to understand the contributing factors and their associated effects on rollover crash severities in these countries. This study aims to investigate and identify the significant factors influencing crash severities and their associated impact magnitudes on single-vehicle rollover crashes in Namibia by adopting a mixed logit with heterogeneity in means and variances approach to account for unobserved heterogeneity in the data. Although it is not without its limitations the dataset used in this study includes single-vehicles rollover crash instances from 2014 to 2016 within Namibia and is able to provide unique details for the crash observations including various driver, environmental, roadway, and vehicle characteristics. Results from this study indicate several factors including weekends, open roadways, and minibuses to be significantly increasing the crash severity of single-vehicle rollover crashes. Additionally, results provide a basis for which researchers and policy makers can understand rollover crashes in Namibia and adopt an appropriate approach to address this issue, such as, Safe Systems. Such an approach would include but not be limited to the implementation of roadside features, educational campaigns, speed enforcement, and vehicle standards policy

Role of Passengers in Single-Vehicle Drunk-Driving Crashes: An Injury-Severity Analysis

Background: Drunk-driving is a major crash risk factor, and crashes resulting from this risky behavior tend to be serious and have significant economic and societal impacts. The presence of passengers and their demographics and activities can influence risky driving behaviors such as drunk-driving. However, passengers could either be an “enabling” factor to take more risks or could be an “inhibiting” factor by ensuring safe driving by a drunk-driver. Objective: This study examines whether the presence of passengers affects the contributing factors of single-vehicle (SV) drunk-driving crashes, by presenting a severity analysis of single- and multi-occupant SV drunk-driving crashes, to identify risk factors that contribute to crash severity outcomes, for the effective implementation of relevant countermeasures. Method: A total of 7407 observations for 2012–2016 from the crash database of the State of Alabama was used for this study. The variables were divided into six classes: temporal, locational, driver, vehicle, roadway, and crash characteristics and injury severities into three: severe, minor, and no injury. Two latent class multinomial logit models—one each for single- and multi-occupant crashes—were developed, to analyze the effects of significant factors on injury severity outcomes using marginal effects. Results: The estimated results show that collision with a ditch, run-off road, intersection, winter season, wet roadway, and interstate decreased the probability of severe injuries in both single- and multi-occupant crashes, whereas rural area, road with downward grade, dark and unlit roadway, unemployed driver, and driver with invalid license increased the likelihood of severe injuries for both single- and multi-occupant crashes. Female drivers were more likely to be severely injured in single-occupant crashes, but less likely in multi-occupant crashes. A significant association was found between severe injuries and weekends, residential areas, and crash location close (<25 mi ≈40.23 km) to the residence of the at-fault driver in multi-occupant crashes. Sport utility vehicles were found to be safer when driving with passengers. Conclusions: The model findings show that, although many correlates are consistent between the single- and multi-occupant SV crashes that are associated with locational, roadway, vehicle, temporal, and driver characteristics, their effect can vary across the single- and multi-occupant driving population. The findings from this study can help in targeting interventions, developing countermeasures, and educating passengers to reduce drunk-driving crashes and consequent injuries. Such integrated efforts combined with engineering and emergency response may contribute in developing a true safe systems approach

Understanding the Factors Associated with the Temporal Variability in Crash Severity before, during, and after the COVID-19 Shelter-in-Place Order

The COVID-19 travel restriction orders have significantly reduced travel and generally lowered the risk of road traffic collisions, but many accounts suggest an increase in risky driving behaviors and consequent fatal crashes during the shelter-in-place period. Risky driving behaviors including failure to wear a seatbelt, speeding, and drunk driving were observed to be the leading contributing factors of the fatalities. Whereas the fatal crashes that characterized the shelter-in-place period has become a topical issue, the high number of crashes that occurred as a result of the panic shopping and increased travel activities in the weeks before the shelter-in-place order have not received much attention. In this study, we investigated the differences and similarities in the effects of the factors that were associated with crash injury severity before, during, and after the shelter-in-place order. The study used crash data from the state of Alabama for the 2020 calendar year. Preliminary data analysis revealed interesting variations in crash trends across the three periods. It was found that the highest weekly crash frequency occurred in the immediate week before the shelter-in-place order, and a higher proportion of crashes that occurred between 6 p.m. and 6 a.m. and those that occurred in residential areas happened during the shelter-in-place period while shopping area crashes, manufacturing/industrial area crashes, rear-end collisions, and crashes involving female drivers occurred mostly before the shelter-in-place period. Three injury severity models were developed using random parameters logit with heterogeneity in means and variances approach. The results showed that major injury crashes occurred mainly in rural areas and occurred due to speeding, fatigue driving, and failure to use a seatbelt. The effects of these factors on crash outcome did not vary across the year, indicating that the shelter-in-place order did not impact the driving behaviors of the driver population that got into major injury crashes. The results further revealed that the effects of some crash factors, such as road type and manner of collision, varied across the periods. The findings of the study provide a deeper, data-driven understanding of how driving behaviors and associated crash outcomes may be affected by extreme events such as the COVID-19 shelter-in-place