Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model

The relation between barrier-free environment perception and campus commuting satisfaction

Introduction

The COVID-19 pandemic, which began in the last quarter of 2019, has had a significant impact on urban transportation. With increasing demand for urban transport, the internal roads and public spaces of university campuses play an important role in facilitating commuting and communication between various functional zones. While considerable research has been conducted on route planning, pedestrian-vehicle segregation, and safety management in the internal transportation environment of university campuses, empirical investigations exploring barrier-free inclusive campus environment design and the subjective evaluation of road and public space users in the aftermath of the COVID-19 pandemic are lacking. Recent developments in travel behavior models and positive psychology have led to an increased focus on the correlation among subjective perceptions, attitudes, emotions, and commuting satisfaction in urban transportation and planning design.

Methods

To elucidate this relationship, a study was conducted on the new campus of Central South University in Changsha, Hunan Province, China. Using 312 valid samples, a structural equation model was constructed to analyse the relationship between commuting satisfaction and the barrier-free environment perception of university students regarding the internal transportation environment of the campus.

Results

The results revealed that individuals' instantaneous barrier-free environment perceptions and long-term established positive emotions had a significant positive effect on commuting satisfaction. Furthermore, positive emotions were found to mediate the relationship between commuting attitudes induced by COVID-19, barrier-free environment perceptions, and commuting satisfaction.

Discussion

The results of this study provide a theoretical basis for the necessity of accessibility design in the post-COVID era. In addition, this study considers the perspective of users to provide ideas for the planning and construction of barrier-free campus environments that are based on convenient and inclusive design.

Interaction between travel restriction policies and the spread of COVID-19

To investigate the interaction between travel restriction policies and the spread of COVID-19, we collected data on human mobility trends, population density, Gross Domestic Product (GDP) per capita, daily new confirmed cases (or deaths), and the total confirmed cases (or deaths), as well as governmental travel restriction policies from 33 countries. The data collection period was from April 2020 to February 2022, resulting in 24,090 data points. We then developed a structural causal model to describe the causal relationship between these variables. Using the Dowhy method to solve the developed model, we found several significant results that passed the refutation test. Specifically, travel restriction policies played an important role in slowing the spread of COVID-19 until May 2021. International travel controls and school closures had an impact on reducing the spread of the pandemic beyond the impact of travel restrictions. Additionally, May 2021 marked a turning point in the spread of COVID-19 as it became more infectious, but the mortality rate gradually decreased. The impact of travel restriction policies on human mobility and the pandemic diminished over time. Overall, the cancellation of public events and restrictions on public gatherings were more effective than other travel restriction policies. Our findings provide insights into the effects of travel restriction policies and travel behavioral changes on the spread of COVID-19, while controlling for informational and other confounding variables. This experience can be applied in the future to respond to emergent infectious diseases.

The relationship between subjective well-being and individual characteristics, personality traits, and choice of transport mode during the first lock-down in Milan, Italy

Introduction

Concerning the adverse effect of COVID-19 virus pandemic on subjective well-being and daily travel, this research sought to analyse which personal characteristics, personality traits, and transport modes are related to positive and negative affect, and satisfaction with life during the first lock-down in Milan, Italy.

Method

In the spring of 2020, an online survey was conducted in Milan, and 1025 responses were collected. Then, three Multinomial Ordinal Regression models (MNOR) are carried out to examine the relationship between the data.

Results

Results show that women were more likely to feel fewer positive emotions than men. More physical activity, and income were positively associated with the models. Significant relevance of personality traits with subjective well-being is reported Regarding daily mobility during the pandemic, transport mode after lock-down, satisfaction with public transport, and worry about using public transport were found relevant to subjective wellbeing.

Conclusions

Whereas the feeling of worry about using public transport increased the negative affect. Transport mode during lock-down was not related to subjective well-being, though the preferred mode of transport after lock-down was related to satisfaction with life. Respondents who chose to use private cars more than other modes of transport were more likely to have higher satisfaction with life. Findings are discussed to improve transport and mobility planning during pandemics.

Exploring the Public Health of Travel Behaviors in High-Speed Railway Environment during the COVID-19 Pandemic from the Perspective of Trip Chain: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China

The outbreak and spreading of COVID-19 since early 2020 have dramatically impacted public health and the travel environment. However, most of the studies are devoted to travel behavior from the macro perspective. Meanwhile, few researchers pay attention to intercity travel behavior. Thus, this study explores the changes in the travel behavior of intercity high-speed railway travelers during the COVID-19 pandemic from the perspective of the individual. Using the smartphone data, this study first extracts the trip chains by proposing a novel method including three steps. The trip chain can describe the whole process of traveling, including individual characteristics, travel time, travel distance, travel mode, etc. Then, a Multinomial Logit model is applied to analyze the trip chains which verified the validity by using studentized residual error. The study finds that intercity travel behavior has changed in gender, age, travel mode choice, and travel purpose by comparing the trip chains between May 2019 and May 2021 in the Beijing-Tianjin-Hebei urban agglomeration. The method proposed in this study can be used to assess the impact of any long-term emergency on individual travel behavior. The findings proposed in this study are expected to guide public health management and travel environment improvement under the situation of normalized COVID-19 prevention and safety control.

Did the COVID-19 vaccine rollout impact transportation demand? A case study in New York City

INTRODUCTION

This study investigates the influence of vaccination along with other pandemic-related factors on driving, transit, and walking in New York City (NYC). The results of this study help inform policymakers of the weight of their decisions in a pandemic setting as well as factors to consider when modeling transportation during a pandemic.

METHODS

In this study, ARIMAX time series analysis was performed on driving, transit, and walking data from Apple Mobility Trends Reports. The data was segmented into two categories "pre-vaccine" and post-vaccine" for both Manhattan and Brooklyn. The independent variables were primarily COVID-19 statistics (vaccination, case counts, deaths, etc.) along with additional predictors aggregated from Google Community Mobility Reports, Google Trends, Citi Bike, National Oceanic and Atmospheric Administration (NOAA), and the Oxford Covid-19 Government Response Tracker (OxCGRT).

RESULTS

Vaccination led to increases in driving, transit, and walking in Brooklyn but was not as statistically significant in Manhattan (the only effect being on walking trips). Despite this, vaccination was not the strongest influencer on transportation. The COVID-19 policy score variable had the highest standardized β in nearly every model, indicating that stricter lockdown policies were the main factor discouraging travel. Furthermore, the lifting of these policies contributed to increases in travel numbers more than vaccination.

CONCLUSIONS

In the event of future pandemics or health crises, NYC policymakers should be aware that they play a significant role in mitigating infectious diseases. The public is seemingly more responsive to policy than anything else. Similar studies should be conducted in other cities as the public response may vary based on other factors.

Impact of perceptions and attitudes on air travel choices in the post-COVID-19 era: A cross-national analysis of stated preference data

The COVID-19 pandemic and the consequent travel restrictions have had an unprecedented impact on the air travel market. However, a rigorous analysis of the potential role of safety perceptions and attitudes towards COVID-19 interventions on future air passenger choices has been lacking to date. To investigate this matter, 1469 individuals were interviewed between April and September 2020 in four multi-airport cities (London, New York City, Sao Paulo, Shanghai). The core analysis draws upon data from a set of stated preference (SP) experiments in which respondents were asked to reflect on a hypothetical air travel journey taking place when travel restrictions are lifted but there is still a risk of infection. The hybrid choice model results show that alongside traditional attributes, such as fare, duration and transfer, attitudinal and safety perception factors matter to air passengers when making future air travel choices. The cross-national analysis points towards differences in responses across the cities to stem from culturally-driven attitudes towards interpersonal distance and personal space. We also report the willingness to pay for travel attributes under the expected future conditions and discuss post-pandemic implications for the air travel sector, including video-conferencing as a substitute for air travel.

Travel satisfaction and travel well-being: Which is more related to travel choice behaviour in the post COVID-19 pandemic? Evidence from public transport travellers in Xi'an, China

The spread of Coronavirus Disease 2019 (COVID-19) has decreased the willingness to choose public transport where travellers are more likely to be infected due to intensive passenger flow, in which case it is hard to attract passenger volume if the subjective well-being of travellers is not improved. However, the traditional measurement of travel evaluation may be not applicable to the context of the pandemic and it is necessary to analyse the changes in the internal mechanisms of travel well-being to avoid the loss of passengers. Based on structural equation modelling, this paper explored the internal relationship between the constructs of travel well-being and emphasised the significance of taking psychological factors into consideration in the post COVID-19 pandemic. The results show that travel satisfaction with the anti-pandemic related service quality of public transport is related to overall travel well-being, which can be used as a key part of well-being measurement scale design in the future. The results also indicate that, due to negative mood on the affective level induced by COVID-19, travel satisfaction on the cognitive level is not directly but indirectly related to travel choice behaviour through overall travel well-being. Compared to travel satisfaction, travel well-being is more extensive and covers travel satisfaction to some extent. Therefore, instead of studying travel satisfaction simply, taking travel well-being as the dependent variable to identify shortages existing in public transport will provide a more accurate perspective for policymakers in the post COVID-19 pandemic.

ANN-Based traffic volume prediction models in response to COVID-19 imposed measures

Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with their impact on economy, education, social and recreational activities, and domestic and international travels. Intuitively, the different imposed policies and measures have indirect impacts on urban traffic mobility. As a result of those imposed measures and policies, urban traffic flows have changed. However, those impacts are neither measured nor quantified. Therefore, estimating the impact of these combined yet different policies and measures on urban traffic flows is a challenging task. This paper demonstrates the development of an artificial neural networks (ANN) model which correlates the impact of the imposed response measure and other factors on urban traffic flows. The results show that the adopted ANN model is capable of mapping the complex relationship between traffic flows and the response measures with a high level of accuracy and good performance. The predicted values are closed to the observed ones. They are clustered around the regression line, with a coefficient of determination ( R 2 ) of 0.9761. Furthermore, the developed model can be generalized to determine the anticipated demand levels resulted from imposing any of the response measures in the post-pandemic era. This model can be used to manage traffic during mega-events. It can be also utilized for disaster or emergency situations, where traffic flow estimates are highly required for operational and planning purposes.

On male urination and related environmental disease transmission in restrooms: From the perspectives of fluid dynamics

Indoor transmission of COVID-19 is highly probable. Multiple sources have verified that the SARS-CoV-2 can be detected within toilets, and people can be infected in restrooms. There is a huge gap in the coronavirus transmission mechanism in restrooms. Understanding it can help to flatten the curve of the infected cases as well as prevent other viruses transmitted through the sewage or human body fluid. Previous studies have shown how simple actions in daily life (coughing, sneezing, or toilet flushing) contribute to virus transmission. This paper visually and quantitatively demonstrates that male urination, which is also a daily action, can agitate virus particles within the toilet and raise them, which may be the main promoter of cross-infection of COVID-19 in restrooms. Adopting numerical and experimental methods, we demonstrate that male urination can cause strong turbulent flow with an averaged urine impinging velocity of 2.3 m/s, which can act as an agitator to raise the virus particles. The climbing velocity of the airflow can be 0.75-1.05 m/s. The observed upwards flow will disturb and spread any lurking virus particles (not limited to SARS-CoV-2). Experiments demonstrated that the concentration of the airborne particle could be tripled during male urination. Corresponding precautions are offered as well to prepare the public to act properly when and after using facilities in restrooms for preventing emerging and re-emerging pandemics not limited to the current COVID-19, contributing to the sustainability of human society.

Assessing the impact of mobility on the incidence of COVID-19 in Dublin City

COVID-19 has had a major impact on the transport systems around the world. Several transport-related policies were implemented in short period of time to contain the spread of the pandemic. These policies had a major influence on travel behavior and people's perception towards the safety of different modes of transport, especially public transport, thus affecting several sustainable mobility initiatives. To build a resilient and sustainable transport system and to rebuild trust in public transport, it is important to understand the role of mobility in the spread of COVID-19 pandemic. The present study investigates the relationship between mobility and reported COVID-19 infections using data from Dublin city. Different modes of transport including traffic volume, bus passengers, pedestrians and cyclists were considered in the study during a forty week period. Multiple scenarios involving two-week lag and three-week lag of mobility data and COVID-19 infections were considered in building statistical models. Results showed that, 36.2% of the reported COVID-19 infections after a two-week lag and 33% of the infections after a three-week lag. Our research examines the links between movements and COVID-19 numbers, but clearly this was not the only reason for increased case numbers as many other events impacted on increased numbers. The study further discusses the policy implications and strategies for ensuring a resilient and sustainable transport system.