A global analysis of urban design types and road transport injury: an image processing study

Characteristics of road traffic accident types and casualties in Guangzhou, China, from 2007 to 2020: A retrospective cohort study based on the general population

Introduction

This study aimed to explore the trend and main influencing factors of road traffic accidents in Guangzhou, China, from 2007 to 2020 and to provide a reference and guidance for government decision-making.

Methods

A retrospective cohort study was used to describe road traffic accidents in Guangzhou. According to the population types, all people with road traffic accidents were divided into migrant workers and the control population. We divided road users, administrative districts, motorcycle types and injury levels into subgroups to investigate the characteristics of road traffic accidents in Guangzhou. The road traffic accident data were derived from the Guangzhou Public Security Traffic Management Integrated System.

Results

The incidence rate of road traffic accidents per 10,000 vehicles in Guangzhou decreased from 36.55 in 2007 to 10.07 in 2012, remained relatively stable at 9.47 in 2017, and finally rose to 11.12 in 2020. The injury rate showed the same trend as the incidence rate, while the mortality rate gradually decreased from 14.21 in 2007 to 5.19 in 2020. Vulnerable road users such as motorized two-to-three-wheeler drivers and migrant workers were casualties in more than 80% of the cases. The proportion of casualties involving mopeds and electric bicycles increased rapidly after 2018. Motor vehicle drivers frequently caused road traffic accidents and were most often uninjured.

Conclusion

Road safety in Guangzhou has shown a clear trend of improvement, but casualties are uneven across administrative districts. More attention should be given to motorized two-to-three-wheelers, migrant workers, and road traffic violations by uninjured individuals.

Contextual factors influencing the urban mobility infrastructure interventions and policies for older adults in low- and middle-income countries: a realist review

Transportation is among the key aspects that influence active ageing. This realist review intends to understand the mechanisms of urban mobility infrastructure interventions and policies in low- and middle-income countries for older adults and to identify factors, which influenced the success or failure of interventions. We followed the steps suggested by Pawson and colleagues for a realist review. Electronic databases were searched from inception until August 2020. Studies were screened based on titles, abstracts and full text. The quality of included studies was assessed based on rigour and relevance. The evidence was obtained from 36 articles with diverse study designs conducted in 36 low- and middle-income countries. Findings were validated through stakeholder consultations from three low- and middle-income countries. Of the various individual factors identified, behaviour change communication interventions were low-cost, had a long-term impact and were efficient in increasing awareness among users to improve safety, social inclusion and about transport schemes for older adults. Improved transport infrastructure resulted in a shift from private to public transportation. For a sustainable urban transport infrastructure, good governance and involvement of stakeholders for planning and implementing transport interventions were considered necessary. Lack of evaluation, experience of transport planners, and inter-sectoral coordination were key challenges to successful interventions. The review highlighted a lack of older adult-specific transportation policies, and gender-targeted interventions for older women, suggesting a need for interventions and policies based on the contextual factors existing in a region.

The Adoption of Digital Technologies and Artificial Intelligence in Urban Health: A Scoping Review

As more people live in cities, the impact of urban settings on population health has been increasing. One of the main strategies to cope with urbanization is adopting artificial intelligence (AI) and new digital technologies to develop new urban services that improve citizens’ health and well-being. The aim of this study is to review urban interventions and adopting digital technologies and AI-based algorithms to improve population health. A scoping review of the literature was conducted by querying MEDLINE, Web of Science, and Scopus databases. The included studies were categorized into one urban health area, suggested by the WHO, according to the type of intervention investigated. Out of 3733 records screened, 12 papers met all inclusion criteria. Four studies investigated the “outdoor and indoor pollution” area, one “climate change”, one “housing”, two “health and social services” and four “urban transport” areas. Only one article used a comprehensive approach to public health, investigating the use of AI and digital technologies both to characterize exposure conditions to health determinants and to monitor population health effects, while the others were limited to characterizing exposure conditions to health determinants, thus employing a preliminary public health perspective. From this point of view, countries should foster synergy for the development of research on digital technologies to address the determinants of health in the urban context. From a global health perspective, sharing results with the scientific community would also allow other countries to use those technologies that have been shown to be effective, paving the way for more sustainable living conditions worldwide.

An Agent-Based Model of Heterogeneous Driver Behaviour and Its Impact on Energy Consumption and Costs in Urban Space

By 2020, over 100 countries had expanded electric and plug-in hybrid electric vehicle (EV/PHEV) technologies, with global sales surpassing 7 million units. Governments are adopting cleaner vehicle technologies due to the proven environmental and health implications of internal combustion engine vehicles (ICEVs), as evidenced by the recent COP26 meeting. This article proposes an agent-based model of vehicle activity as a tool for quantifying energy consumption by simulating a fleet of EV/PHEVs within an urban street network at various spatio-temporal resolutions. Driver behaviour plays a significant role in energy consumption; thus, simulating various levels of individual behaviour and enhancing heterogeneity should provide more accurate results of potential energy demand in cities. The study found that (1) energy consumption is lowest when speed limit adherence increases (low variance in behaviour) and is highest when acceleration/deceleration patterns vary (high variance in behaviour); (2) vehicles that travel for shorter distances while abiding by speed limit rules are more energy efficient compared to those that speed and travel for longer; and (3) on average, for tested vehicles, EV/PHEVs were £233.13 cheaper to run than ICEVs across all experiment conditions. The difference in the average fuel costs (electricity and petrol) shrinks at the vehicle level as driver behaviour is less varied (more homogeneous). This research should allow policymakers to quantify the demand for energy and subsequent fuel costs in cities.

Urban landscape and street-design factors associated with road-traffic mortality in Latin America between 2010 and 2016 (SALURBAL): an ecological study

BACKGROUND

Road-traffic injuries are a key cause of death and disability in low-income and middle-income countries, but the effect of city characteristics on road-traffic mortality is unknown in these countries. The aim of this study was to determine associations between city-level built environment factors and road-traffic mortality in large Latin American cities.

METHODS

We selected cities from Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Panama, and Peru; cities included in the analysis had a population of at least 100 000 people. We extracted data for road-traffic deaths that occurred between 2010 and 2016 from country vital registries. Deaths were grouped by 5-year age groups and sex. Road-traffic deaths were identified using ICD-10 codes, with adjustments for ill-defined codes and incomplete registration. City-level measures included population, urban development, street design, public transportation, and social environment. Associations were estimated using multilevel negative binomial models with robust variances.

FINDINGS

366 cities were included in the analysis. There were 328 408 road-traffic deaths in nearly 3·5 billion person-years across all countries, with an average crude rate of 17·1 deaths per 100 000 person-years. Nearly half of the people who died were younger than 35 years. In multivariable models, road-traffic mortality was higher in cities where urban development was more isolated (rate ratio [RR] 1·05 per 1 SD increase, 95% CI 1·02-1·09), but lower in cities with higher population density (0·94, 0·90-0·98), higher gross domestic product per capita (0·96, 0·94-0·98), and higher intersection density (0·92, 0·89-0·95). Cities with mass transit had lower road mortality rates than did those without (0·92, 0·86-0·99).

INTERPRETATION

Urban development policies that reduce isolated and disconnected urban development and that promote walkable street networks and public transport could be important strategies to reduce road-traffic deaths in Latin America and elsewhere.

FUNDING

Wellcome Trust.

New urban models for more sustainable, liveable and healthier cities post covid19; reducing air pollution, noise and heat island effects and increasing green space and physical activity

Cities are centres of innovation and wealth creation, but also hotspots of air pollution and noise, heat island effects and lack of green space, which are all detrimental to human health. They are also hotspots of COVID19. COVID19 has led to a rethink of urban public space. Therefore, is it time to re-think our urban models and reduce the health burden? We provide a narrative meta-review around a number of cutting edge and visionary urban models that that may affect health and that have been reported over the past few years. New urban concepts such as the Superblocks, the low traffic neighbourhood, 15 Minute city, Car free city or a mixture of these that may go some way in reducing the health burden related to current urban and transport practices. They will reduce air pollution and noise, heat island effects and increase green space and physical activity levels. What is still lacking though is a thorough evaluation of the effectiveness and acceptability of the schemes and the impacts on not only health, but also liveability and sustainability, although they are expected to be positive. Finally, the COVID19 pandemic may accelerate these developments and stimulus funding like the EU Next Generation funding should be used to make these changes.

Built environment profiles for Latin American urban settings: The SALURBAL study

The built environment of cities is complex and influences social and environmental determinants of health. In this study we, 1) identified city profiles based on the built landscape and street design characteristics of cities in Latin America and 2) evaluated the associations of city profiles with social determinants of health and air pollution. Landscape and street design profiles of 370 cities were identified using finite mixture modeling. For landscape, we measured fragmentation, isolation, and shape. For street design, we measured street connectivity, street length, and directness. We fitted a two-level linear mixed model to assess the association of social and environmental determinants of health with the profiles. We identified four profiles for landscape and four for the street design domain. The most common landscape profile was the "proximate stones" characterized by moderate fragmentation, isolation and patch size, and irregular shape. The most common street design profile was the "semi-hyperbolic grid" characterized by moderate connectivity, street length, and directness. The "semi-hyperbolic grid", "spiderweb" and "hyperbolic grid" profiles were positively associated with higher access to piped water and less overcrowding. The "semi-hyperbolic grid" and "spiderweb" profiles were associated with higher air pollution. The "proximate stones" and "proximate inkblots" profiles were associated with higher congestion. In conclusion, there is substantial heterogeneity in the urban landscape and street design profiles of Latin American cities. While we did not find a specific built environment profile that was consistently associated with lower air pollution and better social conditions, the different configurations of the built environments of cities should be considered when planning healthy and sustainable cities in Latin America.

Evaluation of Urban Design Qualities across Five Urban Typologies in Hanoi

Urban design has been shown to play a vital role in promoting the health and wellbeing of urban citizens. However, studies of microscale urban design are underrepresented in comparison with macroscale urban design, especially from low- and middle-income countries in Asia, where urban forms are traditionally compact, complex and with multiple layers and varied urban typologies. The study evaluated microscale urban design qualities of streets (n = 40) across five urban typologies in Hanoi—a typical city in a low- and middle-income country in Asia. The study found that urban typologies and their characteristics have particular impacts on urban design qualities. Old and high-density urban typologies tend to report higher urban design qualities than modern and low-density typologies. Urban design qualities are also significantly associated with the number of pedestrians on the streets. Compared to Western cities, the urban design qualities in Hanoi are substantially different, especially in terms of imageability and complexity, reflecting the differences in urban design and cultural context between cities from various regions. Overall, the study contributes to our understanding of urban design circumstances in Hanoi, providing policymakers, planners, urban designers and architects with important insights for sustainable urban design policies, strategies and interventions.

Could smart research ensure healthy people in disrupted cities?

BACKGROUND

Since the late 19th century, city planners have struggled to cope with new types of urban transport and mobility that threatened the existing system, or even rendered it obsolete.

PURPOSE

As city planners confront the range of disruptive urban mobilities currently on the horizon, this paper explores how we can draw on a vast body of evidence to anticipate and avoid unintended consequences to people's health and wellbeing.

METHODS

This commentary involved a rapid review of the literature on transport disruption.

RESULTS

We found that to avoid the unintended consequences of disruption, research, policy and practice must think beyond single issues (such as the risk of chronic disease, injury, or traffic management) and consider the broader consequences of interventions. For example, although autonomous vehicles will probably reduce road trauma, what will be the negative consequences for physical inactivity, sedentary behavior, chronic disease, land use, traffic congestion and commuting patterns? Research is needed that considers and informs how to mitigate the range of potential harms caused by disruptive mobilities.

CONCLUSION

In the face of new disruptive mobilities, we must: (a) draw on existing evidence to shape new regulations that address the 'who, when and where' rules of introducing new mobilities (such as electric assisted bicycles (e-bikes) and scooters (e-scooters)) of which the health repercussions can be easily anticipated; (b) monitor and evaluate the implementation of any interventions through natural experiment studies; and (c) use innovative research methods (such as agent-based simulation and health-impact-assessment modelling) to assess the likely effects of emerging disruptive mobilities (e.g., autonomous vehicles) on health and wellbeing and on the environment.

Out of the silos: embedding injury prevention into the Sustainable Development Goals

Globally, unintentional injuries contribute significantly to disability and death. Prevention efforts have traditionally focused on individual injury mechanisms and their specific risk factors, which has resulted in slow progress in reducing the burden. The Sustainable Development Goals (SDGs) represent a global agenda for promoting human prosperity while respecting planetary boundaries. While injury prevention is currently only recognised in the SDG agenda via two road safety targets, the relevance of the SDGs for injury prevention is much broader. In this State of the Art Review, we illustrate how unintentional injury prevention efforts can be advanced substantially within a broad range of SDG goals and advocate for the integration of safety considerations across all sectors and stakeholders. This review uncovers injury prevention opportunities within broader global priorities such as urbanisation, population shifts, water safeguarding and corporate social responsibility. We demonstrate the relevance of injury prevention efforts to the SDG agenda beyond the health goal (SDG 3) and the two specific road safety targets (SDG 3.6 and SDG 11.2), highlighting 13 additional SDGs of relevance. We argue that all involved in injury prevention are at a critical juncture where we can continue with the status quo and expect to see more of the same, or mobilise the global community in an 'Injury Prevention in All Policies' approach.

The “Paris-End” of Town? Deriving Urban Typologies Using Three Imagery Types

Urban typologies allow areas to be categorised according to form and the social, demographic, and political uses of the areas. The use of these typologies and finding similarities and dissimilarities between cities enables better targeted interventions for improved health, transport, and environmental outcomes in urban areas. A better understanding of local contexts can also assist in applying lessons learned from other cities. Constructing urban typologies at a global scale through traditional methods, such as functional or network analysis, requires the collection of data across multiple political districts, which can be inconsistent and then require a level of subjective classification. To overcome these limitations, we use neural networks to analyse millions of images of urban form (consisting of street view, satellite imagery, and street maps) to find shared characteristics between the largest 1692 cities in the world. The comparison city of Paris is used as an exemplar and we perform a case study using two Australian cities, Melbourne and Sydney, to determine if a “Paris-end” of town exists or can be found in these cities using these three big data imagery sets. The results show specific advantages and disadvantages of each type of imagery in constructing urban typologies. Neural networks trained with map imagery will be highly influenced by the structural mix of roads, public transport, and green and blue space. Satellite imagery captures a combination of both urban form and decorative and natural details. The use of street view imagery emphasises the features of a human-scaled visual geography of streetscapes. However, for both satellite and street view imagery to be highly effective, a reduction in scale and more aggressive pre-processing might be required in order to reduce detail and create greater abstraction in the imagery.