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College students, who actively travel in the forms of walking and/or bicycling, have shown a wide range of physical and mental health benefits. Despite the known benefits of bicycling, participation is influenced by various demographics, including gender identity, sexual orientation, and race/ethnicity. Universities have the potential to promote active travel participation to all populations. The study aimed to understand the environmental and social factors influencing female students' decision to commute via bicycle in a university setting. A volunteer sample of female college students (n=153) were surveyed to identify common themes from the participants' responses regarding why female students do not ride a bicycle to/from campus. Participants self-reported their confidence with riding a bicycle and trips to/from campus per week by mode of transportation. The most common themes noted through open-ended responses were amount of traffic (91.1%, n=82), safety concerns (63.3%, n=57), knowledge and ownership of a bicycle (33.3%, n=30), participants' preferences (15.6%, n=14), and riding conditions (13.3%, n=12). Participants (37.9%, n=58) reported feeling "somewhat unconfident" with riding a bicycle in the State College area. Participants (31.4%, n=48) also reported feeling "somewhat unconfident" with riding a bicycle on campus. Participants reported an average of 6.06 (M=6.06; SD=6.25) weekly walking trips to/from campus as compared to 0.40 (M=0.40; SD=1.57) bicycling trips to/from campus. Female college students are less likely to commute via bicycle to/from campus compared to other groups of students. Infrastructure improvements and implementing resources, such as educational programs, bicycle shares and e-bicycles, have the potential to improve female college student active travel participation.

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Objective: We examined associations between older drivers' social and environmental characteristics and odds of using non-driving transportation modes. Methods: Using 2015 National Health and Aging Trends Study data for community-dwelling drivers (n = 5102), we estimated logistic regression models of associations between social characteristics, environmental characteristics, and odds of using non-driving transportation modes three years later. Results: Drivers had 20% increase in odds of getting rides three years later for each additional confidante (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI]: 1.11-1.30). Drivers living in more walkable neighborhoods were more likely to walk to get places (National Walkability Index [NWI] score of 18 vs. 2 aOR = 1.71, 95% CI: 1.02-2.90) and take public transit three years later (NWI 18 vs. 2 aOR = 7.47, 95% CI: 1.69-33.0). Discussion: Identifying modifiable social and environmental characteristics can inform future interventions supporting older adults' health during the transition to non-driving.

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OBJECTIVES: To characterize the effect of the actual and potential ability to get rides from others on older adults' driving reduction at 3-year follow-up in the United States. METHODS: We analyzed National Health and Aging Trends Study data from community-dwelling drivers in 2015 (unweighted n = 5,102). We used weighted logistic regression models to estimate whether getting rides from others in 2015 was associated with older adults increasing the number of driving behaviors they avoided, decreasing the frequency with which they drove, or not driving at 3-year follow-up after adjusting for biopsychosocial variables. We also measured presence of social network members living nearby including household and non-household members and estimated associated odds of driving reduction at 3-year follow-up. RESULTS: Older adults who got rides from others in 2015 had greater odds of reporting no longer driving at 3-year follow-up compared to those who did not get rides (adjusted odds ratio [aOR] = 1.53, 95% confidence interval [CI]: 1.11-2.11). We found no statistically significant association between older adults living with others or having more nearby confidantes outside their household and their odds of reducing driving at 3-year follow-up. DISCUSSION: These findings suggest that getting rides from others plays an important role in the transition to non-driving for older adults. Future research should examine whether other aspects of social networks (e.g., type, quality, and closer proximity) might also be key modifiable coping factors for older adults transitioning to non-driving.

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PURPOSE: This study aimed to investigate the limitations in transport use among stroke survivors in rural India and examine its impact on their social participation. MATERIALS AND METHODS: A cross-sectional survey assessed transport patterns, post-stroke changes, and limitations among patients with stroke (N = 77). Social participation was measured with the Stroke Impact Scale (SIS 3.0). RESULTS: Following stroke, there was a significant decrease (28-41%) in the proportion of participants who could use various modes of transport unassisted, particularly in driving a motorbike or scooter and using a bus or train. Post-stroke changes in transport use showed that many participants ceased or decreased their use of different modes of transport. Independent users consistently had higher social participation scores than dependent users across all transport modes, indicating better social participation. The mean differences in various transport modes ranged from 6 to 11 points (p < 0.01). CONCLUSIONS: Independent use of different modes of transport, particularly public transportation, reduced among rural Indian stroke survivors. These transport limitations are significantly associated with reduced social participation, highlighting the need for interventions to improve accessibility and fostering greater community engagement for stroke survivors in this population.IMPLICATIONS FOR REHABILITATIONLimited transportation access limits social participation for stroke survivors in rural India.Study results show a significant decrease in independent transport use among stroke survivors, affecting their social participation.Rehabilitation interventions should focus on improving transportation accessibility to enhance social engagement for rural stroke survivors.

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BACKGROUND: Walking is the primary and preferred mode of exercise for older adults. Walking to and from public transit stops may support older adults in achieving exercise goals. This study examined whether density of neighborhood public transit stops was associated with walking for exercise among older adults. METHODS: 2018 National Health and Aging Trends Study (NHATS) data were linked with the 2018 National Neighborhood Data Archive, which reported density of public transit stops (stops/mile2) within participants' neighborhood, defined using census tract boundaries. Walking for exercise in the last month was self-reported. The extent to which self-reported public transit use mediated the relationship between density of neighborhood public transit stops and walking for exercise was examined. Covariates included sociodemographic characteristics, economic status, disability status, and neighborhood attributes. National estimates were calculated using NHATS analytic survey weights. RESULTS: Among 4,836 respondents with complete data, 39.7% lived in a census tract with at least one neighborhood public transit stop and 8.5% were public transit users. The odds of walking for exercise were 32% higher (OR = 1.32; 95% confidence interval: 1.08, 1.61) among respondents living in a neighborhood with > 10 transit stops per mile compared to living in a neighborhood without any public transit stops documented. Self-reported public transit use mediated 24% of the association between density of neighborhood public transit stops and walking for exercise. CONCLUSIONS: Density of neighborhood public transit stops was associated with walking for exercise, with a substantial portion of the association mediated by self-reported public transit use. Increasing public transit stop availability within neighborhoods may contribute to active aging among older adults.

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PURPOSE OF REVIEW: Explore the varied pathways between the built environment and children's health. The review begins by describing how the built environment and transport infrastructure relate to conditions that lead to health outcomes. The review examines emissions, noise, and traffic dangers in relation to children's physical, mental, and social health. RECENT FINDINGS: Evidence is increasing for walkable neighborhoods and health-related behavior such as physical activity. However, diverse land uses (often supporting walkability) were also found to increase traffic injuries. Cognitive impacts of motorways on children at schools were found. Finally, the relationships between social activities and built environment are beginning. The built environment's influence on various physical health outcomes is increasingly clear and is often through a transport pathway. However, the links with mental and social health are less developed, though recent findings show significant results. Having accessible child-relevant destinations is an important consideration for children's health.

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Carpooling is a sustainable, economical, and environmentally friendly solution to reduce air pollution and ease traffic congestion in urban areas. However, existing regret theories lack consideration of the heterogeneity of attribute perception in different ways and the psychological factors that affect regret, so they cannot accurately portray urban residents' carpool travel decisions and cannot provide a correct explanation of the actual carpool choice behavior. In this paper, based on the analysis of classical random regret minimization models and random regret minimization models considering heterogeneity, the concept of psychological distance is introduced to address shortcomings of the existing models and construct an improved random regret minimization model considering heterogeneity and psychological distance. The results show that the fit and explanatory effect of the improved model proposed in this paper is better than that of the other two models. The psychological distance of travel residents during the Corona Virus Disease 2019 (COVID-19) affects the anticipated regret value and the willingness to carpool. The model can better describe the carpool travel choice mechanism of travelers and effectively explain the carpool travel choice behavior of travelers.

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The COVID-19 pandemic has a significant impact on daily life, leading to quarantines and essential travel restrictions worldwide in an effort to curb the virus's spread. Despite the potential importance of essential travel, research on changes in travel patterns during the pandemic has been limited, and the concept of essential travel has not been fully explored. This paper aims to address this gap by using GPS data from taxis in Xi'an City between January and April 2020 to investigate differences in travel patterns across three periods pre, during, and post the pandemic. Spatial statistical models are used to examine the major supply and demand-oriented factors that affect spatial travel patterns in different periods, and essential and nonessential socioeconomic resources are defined based on types of services. Results indicate that the spatial distribution of travel demand was highly correlated with the location of socioeconomic resources and opportunities, regardless of the period. During the "Emergency Response" period, essential travel was found to be highly associated with facilities and businesses providing essential resources and opportunities, such as essential food provider, general hospital and daily grocery supplies. The findings suggest that local authorities may better identify essential travel destinations by referencing the empirical results, strengthening public transit connections to these locations, and ultimately promoting traffic fairness in the post-pandemic era.

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The unprecedented COVID-19 outbreak has significantly influenced our daily life, and COVID-19's spread is inevitably associated with human mobility. Given the pandemic's severity and extent of spread, a timely and comprehensive synthesis of the current state of research is needed to understand the pandemic's impact on human mobility and corresponding government measures. This study examined the relevant literature published to the present (March 2023), identified research trends, and conducted a systematic review of evidence regarding transport's response to COVID-19. We identified key research agendas and synthesized the results, examining: (1) mobility changes by transport modes analyzed regardless of government policy implementation, using empirical data and survey data; (2) the effect of diverse government interventions to reduce mobility and limit COVID-19 spread, and controversial issues on travel restriction policy effects; and (3) future research issues. The findings showed a strong relationship between the pandemic and mobility, with significant impacts on decreased overall mobility, a remarkable drop in transit ridership, changes in travel behavior, and improved traffic safety. Government implemented various non-pharmaceutical countermeasures, such as city lockdowns, travel restrictions, and social distancing. Many studies showed such interventions were effective. However, some researchers reported inconsistent outcomes. This review provides urban and transport planners with valuable insights to facilitate better preparation for future health emergencies that affect transportation. Supplementary Information: The online version contains supplementary material available at 10.1007/s11116-023-10392-2.

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The COVID-19 pandemic has significantly affected travel behavior, including the frequency and mode of travel, with the magnitude and nature of these effects varying over time. This study investigates the nature of these relationships by examining changes in various measures of travel behavior, including weekly driving hours, as well as the frequency of telecommuting, use of ride-sharing services, travel for medical purposes, and use of food delivery services. Self-reported travel data from a representative statewide survey of Michigan residents were used to assess changes in these metrics during the early stages of the pandemic, as well as one year thereafter. Random effects linear regression and ordered logit regression models were estimated and the findings show that various changes in behavior had long-lasting effects, while other behaviors generally reverted back toward pre-pandemic levels. In addition, these changes were found to vary across individuals. For example, significant differences were observed based on socio-demographic characteristics, between urban and rural areas, and amongst individuals with differing views on COVID-19 and related government interventions. In general, the pandemic tended to have less pronounced and sustained effects among younger adults as compared to older age groups. Further, those individuals who were opposed to mandatory COVID-19 vaccines were less likely to change their travel behavior, during both the early and latter stages of the pandemic. Changes were observed consistently across most of the travel metrics of interest. Among these, overall driving hours, travel for medical purposes, and ride-sharing were still lower during the latter stages of the pandemic, while telecommuting and the use of food delivery services reverted nearer to pre-pandemic levels.

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Since the COVID-19 outbreak, consumer behavior has been affected by the perceived threat of the pandemic and economic uncertainty. This paper aims to explore the dynamic effects of COVID-19, consumer sentiment, economic policy uncertainty, and fuel prices on travel behavior in the United States. Using updated daily trip data, the results show that consumer sentiment has a positive long-run impact on travel demand for air and auto, suggesting that a positive change in consumer sentiment can boost demand for these modes of transportation in the long term. Additionally, consumer sentiment has a favorable effect (1.34) on demand for long-distance trips, but it has a negative impact (-0.42) on the number of people staying at home. Economic and political shocks have a detrimental impact on demand for air and auto travel, suggesting that consumers reduce the frequency and cost of these transport services if they have pessimistic expectations about the future state of the economy and policy. However, in the short term, US travelers appear to be insensitive to shocks in consumer sentiment and economic policy uncertainty. Regarding the perceived threat of the pandemic, the results indicate that rising COVID-19 cases have a negative long-term effect on demand for air travel (-0.09) and public transit (-0.19), while they are positively associated with demand for auto travel (0.06). Similarly, the increasing number of deaths due to COVID-19 has led to a shift from shared-use mass transportation (air travel and public transit) to private autos and non-motorized travel, such as walking in the short term.

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To prevent the pandemic spread of human-to-human transmitted diseases such as COVID-19, governments commonly resort to countrywide or regional lockdown strategies. Such lockdowns, whenever and wherever implemented, curtail the movement of persons and vehicles, and drastically alter traffic conditions. This study focuses on the effect of drastic and sudden changes in the traffic conditions, during the COVID-19 lockdown in the State of Maharashtra in India, in March-June 2020, on the numbers of motor vehicle accidents (MVAs), and the resultant fatalities and injuries. Content analysis of police-reported first information reports (FIRs) of MVAs is performed, and these lockdown trends are compared with archival data from corresponding previous (normal) periods. The statistical analysis shows that, during the lockdown, while the total number of MVAs fall drastically, they are more severe and have a much higher fatality rate per MVA. Also, the pattern of vehicles involved in MVAs, and resultant pattern of fatalities, also changes during lockdowns. The paper explores the reasons for these changed patterns and provides suggestions to reduce these negative externalities of pandemic related lockdowns.

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The paper reports evidence related to peoples' perceptions and attitude during the early stages of COVID-19 related lockdown in India in four major aspects: strategies and preventive measures, long-distance travel, essential services, and post-lockdown travel. A five-stage survey instrument was designed and circulated through various online modes to make it convenient to the respondents and also to achieve a greater geographical coverage within a short period of time. The survey responses were analyzed using statistical tools and the results are translated into potential policy recommendations which may be useful to implement effective interventions during future pandemics of similar nature. The findings highlight a high rate of awareness among the people about the COVID-19, lack of supply of protective equipment such as masks, gloves, and personal protective equipment kits during the early stage of lockdown in India. However, several heterogeneities were also observed across a few socio-economic groups which emphasize the need for targeted campaigns in a diverse country such as India. The findings also suggest the need for arranging safe and hygienic long-distance trips for a section of the society when such lockdown measures are extended for long periods. The observations related to mode choice preferences during the post-lockdown recovery period indicate a potential shift of public transport patronage to the personal modes.

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This research examines the impacts of COVID-19 on the mobility of resource-poor women and its linkage with livelihoods in urban South Asia, and how gender-responsive transport measures could be adopted. The study, conducted in Delhi between October 2020 and May 2021, used a mixed methods, multi-stakeholder, and reflexive approach. A literature review was conducted on the gender and mobility context in Delhi, India. Quantitative data were collected through surveys with resource-poor women, while qualitative research methods consisted of in-depth interviews with them. Different stakeholders were engaged through round tables and key informant interviews before and after data collection to share the findings and recommendations. The sample survey (n = 800) revealed that only 1.8% of working resource-poor women have access to a personal vehicle, making them dependent on public transport. While 81% of their trips are by bus, 57% of their peak hour trips are by paratransit, despite free travel on buses. Only 10% of the sample have access to a smart phone, which restricts their access to digital initiatives based on smart phone applications. The women expressed concerns such as poor bus frequencies and buses not stopping for them under the free ride scheme. These were consistent with issues faced before the COVID-19 pandemic. These findings highlight the need for targeted strategies for resource-poor women to achieve equity in gender-responsive transport. These include a multimodal subsidy, short messaging service to obtain real-time information, increased awareness on filing complaints, and an effective grievance redressal system.

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COVID-19 has caused huge disruptions to urban travel and mobility. As a critical transportation mode in cities, public transit was hit hardest. In this study, we analyze public transit usage of urban visitors with a nearly two-year smart card dataset collected in Jeju, South Korea - a major tourism city in the Asia Pacific. The dataset captures transit usage behavior of millions of domestic visitors who traveled to Jeju between January 1, 2019 and September 30, 2020. By identifying a few key pandemic stages based on COVID-19 timeline, we employ ridge regression models to investigate the impact of pandemic severity on transit ridership. We then derive a set of mobility indicators - from perspectives of trip frequency, spatial diversity, and travel range - to quantify how individual visitors used the transit system during their stay in Jeju. By further employing time series decomposition, we extract the trend component for each mobility indicator to study long-term dynamics of visitors' mobility behavior. According to the regression analysis, the pandemic had a dampening effect on public transit ridership. The overall ridership was jointly affected by national and local pandemic situations. The time series decomposition result reveals a long-term decay of individual transit usage, hinting that visitors in Jeju tended to use the transit system more conservatively as the pandemic endured. The study provides critical insights into urban visitors' transit usage behavior during the pandemic and sheds light on how to restore tourism, public transit usage, and overall urban vibrancy with some policy suggestions.

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As an important component of bike-sharing (BS) users, the travel behavior of college students and office workers is important to the promotion of BS within Chinese cities. To explore the influencing factors for the behavioral intentions of BS, this paper makes a different analysis between the two groups. Based on the theory of planned behavior, and using environmental awareness as an extended variable, a BS travel intention model was developed. A total of 676 valid questionnaires were collected and analyzed from college students and office workers in Zhengzhou. The results indicate that attitude, subjective norms, perceived behavior control, and environmental awareness have a positive impact on the behavioral intentions of BS. However, the influence degree of each variable is different between the two groups. Perceived behavior control, including travel time, travel cost, and cycling difficulty, has the greatest impact on BS behavioral intention for college students. Meanwhile, subjective norms, including policy and media publicity, has the most significant impact on BS behavioral intention for office workers. The impact of environmental awareness on college students' use of BS is higher than that of office workers. We also found that undergraduates use BS more frequently than postgraduates. The findings provide the clear influence factors on behavioral intentions of BS between college students and office workers, that can help policy optimization in terms of bike-sharing systems, giving some suggestion for an approach devoted to deepen the individual-context interactions.

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The COVID-19 pandemic has resulted in substantial negative impacts on social equity. To investigate transport inequities in communities with varying medical resources and COVID controlling measures during the COVID pandemic and to develop transport-related policies for the post-COVID-19 world, it is necessary to evaluate how the pandemic has affected travel behavior patterns in different socio-economic segments (SES). We first analyze the travel behavior change percentage due to COVID, e.g., increased working from home (WFH), decreased in-person shopping trips, decreased public transit trips, and canceled overnight trips of individuals with varying age, gender, education levels, and household income, based on the most recent US Household Pulse Survey census data during Aug 2020 âˆ¼ Dec 2021. We then quantify the impact of COVID-19 on travel behavior of different socio-economic segments, using integrated mobile device location data in the USA over the period 1 Jan 2020-20 Apr 2021. Fixed-effect panel regression models are proposed to statistically estimate the impact of COVID monitoring measures and medical resources on travel behavior such as nonwork/work trips, travel miles, out-of-state trips, and the incidence of WFH for low SES and high SES. We find that as exposure to COVID increases, the number of trips, traveling miles, and overnight trips started to bounce back to pre-COVID levels, while the incidence of WFH remained relatively stable and did not tend to return to pre-COVID level. We find that the increase in new COVID cases has a significant impact on the number of work trips in the low SES but has little impact on the number of work trips in the high SES. We find that the fewer medical resources there are, the fewer mobility behavior changes that individuals in the low SES will undertake. The findings have implications for understanding the heterogeneous mobility response of individuals in different SES to various COVID waves and thus provide insights into the equitable transport governance and resiliency of the transport system in the "post-COVID" era.

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The COVID-19 pandemic has had unprecedented impacts on the way we get around, which has increased the need for physical and social distancing while traveling. Shared mobility, as an emerging travel mode that allows travelers to share vehicles or rides has been confronted with social distancing measures during the pandemic. On the contrary, the interest in active travel (e.g., walking and cycling) has been renewed in the context of pandemic-driven social distancing. Although extensive efforts have been made to show the changes in travel behavior during the pandemic, people's post-pandemic attitudes toward shared mobility and active travel are under-explored. This study examined Alabamians' post-pandemic travel preferences regarding shared mobility and active travel. An online survey was conducted among residents in the State of Alabama to collect Alabamians' perspectives on post-pandemic travel behavior changes, e.g., whether they will avoid ride-hailing services and walk or cycle more after the pandemic. Machine learning algorithms were used to model the survey data (N = 481) to identify the contributing factors of post-pandemic travel preferences. To reduce the bias of any single model, this study explored multiple machine learning methods, including Random Forest, Adaptive Boosting, Support Vector Machine, K-Nearest Neighbors, and Artificial Neural Network. Marginal effects of variables from multiple models were combined to show the quantified relationships between contributing factors and future travel intentions due to the pandemic. Modeling results showed that the interest in shared mobility would decrease among people whose one-way commuting time by driving is 30-45 min. The interest in shared mobility would increase for households with an annual income of $100,000 or more and people who reduced their commuting trips by over 50% during the pandemic. In terms of active travel, people who want to work from home more seemed to be interested in increasing active travel. This study provides an understanding of future travel preferences among Alabamians due to COVID-19. The information can be incorporated into local transportation plans that consider the impacts of the pandemic on future travel intentions.

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Background: Many people changed their travel behavior during the coronavirus pandemic with more telecommuting, fewer trip frequencies, and less use of transit and ride-hailing to avoid infection. The lack of outdoor activities may result in social isolation and then trigger anxiety or depressive symptoms. Research objective: This study examines the relationship between anxiety and depression, and correlates various sociodemographic, income, job status, health-related factors, and travel behavior changes in six large U.S. cities. Data: U.S. Census Household Pulse Survey Phases 3.0 and 3.1 are employed. Method: GAD-2 and PHQ-2 are used to screen the scores of anxiety and depression. The synthetic minority oversampling technique is applied to correct sample distribution. The multivariate mixed model is employed to examine relationships. Results: (1) Anxiety and depression are positively correlated, and the percentage of high anxiety is greater than the percentage of high depression. (2) The levels of anxiety and depression significantly vary across the six cities. (3) Women, young, singles, and white people have higher levels of anxiety and depression during the pandemic. (4) People who are willing to receive vaccination tend to have higher levels of anxiety and depression. (5) The prevalence of depressive disorders is significantly lower in the high-income group. (6) People who applied for unemployment insurance and experienced expense difficulties are more likely to suffer high levels of anxiety and depression. (7) Travel behavior changes, measured by increased telecommuting, reduced trip frequency, and reduced use of transit and ride-hailing, all suggest positive correlations with anxiety and depression. Conclusions: More assistance and attention should be given to women, singles, and low-income households to reduce the prevalence of mental stress in vulnerable groups. Telecommuting can be but need to work with other travel demand management strategies. Travel and outdoor activities should be promoted under the new normal.

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Introduction: As a planetary health challenge, COVID-19 forced governments around the world to take action to prevent the most severe consequences resulting from the spread of the virus. These measures ranged from stay-at-home orders to limitations on indoor and outdoor activities, travel restrictions and the cancelation of sports events, all of which affected people's leisure activities and daily lives. Therefore, the aim of this study is to examine changes in sports-related leisure behavior in terms of attending major sports events, following major sports events via media, travel intentions and the use of new sports offerings. Furthermore, we aimed to identify variables associated with changed sports-related leisure behavior during the pandemic. Methods: A cross-sectional online survey (n = 1,809) was conducted from December 2020 to January 2021 in the Alpine regions of Austria, Germany and Italy. Sports-related leisure behavior was investigated for changes during the pandemic compared to the time before the coronavirus outbreak and for differences between the three countries. Results: Results showed that the self-reported importance of attending major sports events decreased significantly in the Alpine regions of all three countries during COVID-19. Prevailing restrictions affected vacation planning for over 80% of participants. A majority of approximately three quarters of respondents stated they had spent their holidays at home during the travel restrictions. Sports facilities and opportunities played an important role in the choice of vacation destination for more than half of participants. A binary logistic regression showed significant correlations between vacation planning during COVID-19 and the variables gender, income, quality of life and mental health. 31.9% of all respondents tried new sports offerings during extended restrictions, with a large proportion (72.4%) using apps, online tools or courses. Furthermore, approximately 30% of respondents increased their e-sports consumption. Discussion: The results showed that sports-related leisure behavior in Alpine regions changed in the course of the COVID-19 pandemic. In the future, policymakers as well as sports and leisure providers should react to these behavioral changes and adapt their portfolio and services to meet consumers92 demands.

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