Housing and accessibility after the COVID-19 pandemic: Rebuilding for resilience, equity and sustainable mobility

Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong

The COVID-19 pandemic has exerted unprecedented impacts on travel behaviors because of people's increased health precautions and the presence of various COVID-19 containment measures. However, little research has explored whether and how people changed their travel with respect to their perceived local infection risks across space and time. In this article, we relate elasticity and resilience thinking to the changes in metro travel and perceived infection risks at the station or community level over time. Using empirical data from Hong Kong, we measure a metro station's elasticity as the ratio of changes in its average trip length to the COVID-19 cases' footprints around that station. We regard those footprints as a proxy for people's perceived infection risks when making trips to that station. To explore influencing factors on travel in the ups and downs of perceived infection risks, we classify stations based on their elasticity values and examine the association between stations' elasticities and characteristics of stations and their served communities. The findings show that stations varied in elasticity values across space and different surges of the local pandemic. The elasticity of stations can be predicted by socio-demographics and physical attributes of station areas. Stations serving a larger percentage of population with higher education degrees and certain occupations observed more pronounced trip length decrease for the same level of perceived infection risks. The number of parking spaces and retail facilities significantly explained variations in stations' elasticity. The results provide references on crisis management and resilience improvement amid and post COVID-19.

Urban resilience under the COVID-19 pandemic: A quantitative assessment framework based on system dynamics

The COVID-19 pandemic, which lasted for three years, has had a great impact on the public health system, society and economy of cities, revealing the insufficiency of urban resilience under large-scale public health events (PHEs). Given that a city is a networked and multidimensional system with complex interactions, it is helpful to improve urban resilience under PHEs based on system thinking. Therefore, this paper proposes a dynamic and systematic urban resilience framework that incorporates four subsystems (governance, infrastructures, socioeconomy and energy-material flows). The composite index, system dynamics and epidemic simulation model are integrated into the framework to show the nonlinear relationships in the urban system and reflect the changing trend of urban resilience under PHEs. Then, urban resilience under different epidemic scenarios and response policy scenarios is calculated and discussed to provide some suggestions for decision-makers when faced with the trade-off between the control of PHEs and the maintenance of city operation. The paper concludes that control policies could be adjusted according to the characteristics of PHEs; strict control policies under a severe epidemic could lead to a significant decrease in urban resilience, while a more flexible control strategy can be adopted under a mild epidemic scenario to ensure the normal operation of urban functions. Moreover, the critical functions and impact factors of each subsystem are identified.

Investigating impacts of COVID-19 on urban mobility and emissions

The COVID-19 pandemic has severely impacted human activities in a way never documented in modern history. The prevention policies and measures have abruptly changed well-established urban mobility patterns. In this context, we exploit different sources of urban mobility data to gain insights into the effects of restrictive policies on the daily mobility and exhaust emissions in pandemic and post-pandemic periods. Manhattan, the most densely populated borough in New York City, is chosen as the study area. We collect data generated by taxis, sharing bikes, and road detectors between 2019 and 2021, and estimate exhaust emissions using the COPERT (Computer Programme to calculate Emissions from Road Transport) model. A comparative analysis is conducted to identify important changes in urban mobility and emission patterns, with a particular focus on the lockdown period in 2020 and its counterparts in 2019 and 2021. The results of the paper fuel the discussion on urban resilience and policy-making in a post pandemic world.

Comparing COVID-19 in the antipodes: Insights from pandemic containment strategies on both sides of the Pacific

That the COVID-19 pandemic is unprecedented in terms of its scale, spread and shocks can be evinced by the myriad of ever-changing responses cities all around the world have rolled out throughout the different waves of outbreaks. Although the threat is similar across the world, it took some time before its reach became global and the waves of outbreak are experienced by cities at different times. While this staggered spread imply that some cities might manage the virus better as they learn from the experiences of cities which had been amongst the earliest to face the virus, the reality is more complicated. In the early stages of the pandemic, the global consensus on the best way to contain the virus swiftly converged in the interlinked strategies of restricting the movement of people and minimizing their social contact. However, the effectiveness of these strategies differ greatly between cities. To that end, this study focuses on COVID-19 responses in two regions (Latin America and Southeast Asia) and examines the evolution of the first wave of COVID-19 outbreaks during 2020 in Singapore, Jakarta (Indonesia), Bogotá (Colombia) and Santiago (Chile). The study is based on a comparative approach and uses a variety of data sources, namely morphology, density, housing concentration, mobility, and governance in the four analyzed cities. The goal is to shed light on the response of city governments in these two different regions in terms of mobility restrictions in order to reduce the cases of new infections. The results show the relevance of urban policies and their territorial approaches, particularly in terms of mobility and public transport networks in the four cities.

Tempo-Spatial Modelling of the Spread of COVID-19 in Urban Spaces

The relationship between the social structure of urban spaces and the evolution of the COVID-19 pandemic is becoming increasingly evident. Analyzing the socio-spatial structure in relation to cases may be one of the keys to explaining the ways in which this contagious disease and its variants spread. The aim of this study is to propose a set of variables selected from the social context and the spatial structure and to evaluate the temporal spread of infections and their different degrees of intensity according to social areas. We define a model to represent the relationship between the socio-spatial structure of the urban space and the spatial distribution of pandemic cases. We draw on the theory of social area analysis and apply multivariate analysis techniques to check the results in the urban space of the city of Malaga (Spain). The proposed model should be considered capable of explaining the functioning of the relationships between societal structure, socio-spatial segregation, and the spread of the pandemic. In this paper, the study of the origins and consequences of COVID-19 from different scientific perspectives is considered a necessary approach to understanding this phenomenon. The personal and social consequences of the pandemic have been exceptional and have changed many aspects of social life in urban spaces, where it has also had a greater impact. We propose a geostatistical analysis model that can explain the functioning of the relationships between societal structure, socio-spatial segregation, and the temporal evolution of the pandemic. Rather than an aprioristic theory, this paper is a study by the authors to interpret the disparity in the spread of the pandemic as shown by the infection data.

System dynamics model for intra-city multimodal transportation considering behavioral indicators and demand under uncertainty conditions

Purpose

By designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.

Design/methodology/approach

The paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.

Findings

Four scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.

Originality/value

The value of this paper is considering uncertainty in traffic optimization; taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status; investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.

To Use or Not Use Car Sharing Mobility in the Ongoing COVID-19 Pandemic? Identifying Sharing Mobility Behaviour in Times of Crisis

Car sharing services have expanded in order to meet the new necessities of mobility worldwide in an innovative way. Before the COVID-19 pandemic, car sharing was a very popular mode of transportation among young adults in big cities. However, during this ongoing pandemic and with public transportation considered a super-spreading transmitter, the usage of car sharing is unclear. Therefore, the aim of this study, which is explorative in nature, is to investigate the usage, advantages, drivers, and barriers to car sharing during this ongoing pandemic era. To this end, 66 interviews were conducted among users of car sharing during the COVID-19 pandemic. The findings provide key information for the planning of car sharing operations and public transportation in the context of avoiding COVID-19 infection and respecting the recommendations of local governments. In addition, new emerging profiles of car sharing users in the ongoing pandemic are identified. This research provides relevant insights for both business practice and policy makers.

The impacts of COVID-19 on older adults' active transportation mode usage in Isfahan, Iran

AIMS

Since active mobility is essential for older adults' health and well-being, especially in crises, this study aims to investigate and compare factors affecting active mode choice of older adults (AMCOA) in the pre- and post-COVID-19 outbreak and evaluate changes in their active mobility behavior and no research has been conducted this subject.

METHODOLOGY

The sample study of this cross-sectional study includes individuals over 60 years old residing in Isfahan, Iran. For interviews based on a structured questionnaire, which was drafted based on reviewing the literature, 453 participants were randomly selected in 15 municipality districts of Isfahan. A binary logistic regression model was used to analyze the data.

RESULT AND DISCUSSION

The results indicate that in the post-outbreak the average walking duration per week decreased from 59 to 29 min; while, the share of this mode has increased from 40% to 65%. Also, the share of bicycles and the average cycling duration per week increased from 9% to 18% and from 9 to 15 min, respectively. Moreover, trip frequency, bicycle ownership, quality of walking and cycling routes, intersections safety, neighborhood security and greenery, traffic calming, CBD accommodation, and public transportation accessibility have positive effects on AMCOA; while, trip distance and vehicle ownership affect negatively. The results reveal that older adults have turned to the bicycle for most of their long trips during the pandemic because it is not subjected to traffic restrictions. Besides, the findings show that increasing bicycle ownership and improving bike-sharing infrastructure make the bicycle a resilient alternative when public transportation and private vehicles are not efficient.

CONCLUSION

Policymakers and urban planners should consider that an elderly-friendly neighborhood with mixed, dense, and accessible land uses and services, as well as safe and secure routes can increase older adults' active mobility in the crises.

AIMS

Since active mobility is essential for older adults' health and well-being, especially in crises, this study aims to investigate and compare factors affecting active mode choice of older adults (AMCOA) before and during the first wave of COVID-19 outbreak and evaluate changes in their active mobility behavior and no research has been conducted this subject.