Will modal shift occur from subway to other modes of transportation in the post-corona world in developing countries?

Analysis of SARS-CoV-2 transmission in a university classroom based on real human close contact behaviors

Due to high-population density, frequent close contact, possible poor ventilation, university classrooms are vulnerable for transmission of respiratory infectious diseases. Close contact and long-range airborne are possibly main routes for SARS-CoV-2 transmission. In this study, taking a university classroom in Beijing for example, close contact behaviors of students were collected through a depth-detection device, which could detect depth to each pixel of the image, based on semi-supervised learning. Finally, >23 h of video data were obtained. Using Computational Fluid Dynamics, the relationship between viral exposure and close contact behaviors (e.g. interpersonal distance, relative facial orientations, and relative positions) was established. A multi-route transmission model (short-range airborne, mucous deposition, and long-range airborne) of infectious diseases considering real close contact behaviors was developed. In the case of Omicron, the risk of infection in university classrooms and the efficacy of different interventions were assessed based on dose-response model. The average interpersonal distance in university classrooms is 0.9 m (95 % CI, 0.5 m-1.4 m), with the highest proportion of face-to-back contact at 87.0 %. The risk of infection of susceptible students per 45-min lesson was 1 %. The relative contributions of short-range airborne and long-range airborne transmission were 40.5 % and 59.5 %, respectively, and the mucous deposition was basically negligible. When all students are wearing N95 respirators, the infection risk could be reduced by 96 %, the relative contribution of long-range airborne transmission increases to 95.6 %. When the fresh air per capita in the classroom is 24 m3/h/person, the virus exposure could be decreased by 81.1 % compared to the real situation with 1.02 m3/h/person. In a classroom with an occupancy rate of 50 %, after optimized arrangement of student distribution, the infection risk could be decreased by 62 %.

The Impact of Urban Rail Transit Epidemic Prevention Measures on Passengers' Safety Perception

In 2020, COVID-19 triggered concern about the safety of public transport. To meet passengers' expectations regarding safety, the public transport department has stepped up its pandemic prevention services. Some prevention services require passengers to follow mandatory requirements. However, whether and to what extent these requirements affect passenger satisfaction with public transportation services remains unclear. This study aims to construct an integrated framework to explore the direct and indirect relationships between four constructs (regular services quality, pandemic prevention service, psychological distance, and safety perception) and passengers' satisfaction in the context of urban rail transit services. Based on survey data collected from 500 passengers on the Shanghai Metro, this paper examines the relationships between routine service, pandemic prevention measures, safety perceptions, and satisfaction with the service. The results from the structural equation model indicate that routine service (0.608), pandemic prevention measures (0.56), and safety perception (0.05) have positive effects on passenger satisfaction. Psychological distance negatively impacts safety perception (-0.949) and has indirect effects on passenger satisfaction. Further, in order to identify the service improvements that public transportation departments should focus on, we use the three-factor theory to identify the services that should be improved: Basic factors, such as "punctual arrival of metros", "treatment of harmful garbage", "increasing frequency of platform disinfection", and "measurement of station temperature" should be treated as the first priority. As the second improvement priority, "the planning of metro stations can accommodate my travel scope" can be considered. Last, public transportation departments can enhance the exciting factor by installing "metro entrance signs" when resources are available.

Investigating factors affecting university students' use of subway before and after COVID-19 outbreak: A case study in Tehran

Identifying and examining factors affecting the use of the subway is critical for developing countries as they struggle with high levels of auto use and resulting congestion, noise and air pollution. In this research, we surveyed students of a top-ranked university in the capital of Iran before and after the COVID-19 outbreak to identify the factors affecting their use of the subway. Chi-square tests show that gender, level of education, and being the only child of the family have the highest impact on using a private car. These variables had no significant influence on students' mode choice to university before the COVID-19 pandemic, when students' mode choice was only a function of their residence location. However, the pandemic has affected priorities for mode choice. For instance, hygiene and social distancing, which were previously insignificant to students, are now among their top criteria, and travel time and cost are less important for students than in the past. As a result, subway use has significantly decreased. Based on the results of the research, when making relevant policies, more attention should be paid to the groups of women, undergraduate students and single children that are more likely to use private cars.

Data analytics during pandemics: a transportation and location planning perspective

The recent COVID-19 pandemic once again showed the value of harnessing reliable and timely data in fighting the disease. Obtained from multiple sources via different collection streams, an immense amount of data is processed to understand and predict the future state of the disease. Apart from predicting the spatio-temporal dynamics, it is used to foresee the changes in human mobility patterns and travel behaviors and understand the mobility and spread speed relationship. During this period, data-driven analytic approaches and Operations Research tools are widely used by scholars to prescribe emerging transportation and location planning problems to guide policy-makers in making effective decisions. In this study, we provide a review of studies which tackle transportation and location problems during the COVID-19 pandemic with a focus on data analytics. We discuss the major data collecting streams utilized during the pandemic era, highlight the importance of rapid and reliable data sharing, and give an overview of the challenges and limitations on the use of data.

The Future and Sustainability of Carpooling Practices. An Identification of Research Challenges

This article proposes several new research directions regarding the future and sustainability of carpooling practices. The reflection is based on a systematic review of the literature (2010–2021) and a consideration of some of the main recent changes in carpooling, such as carpooling platforms and apps, and changes in lifestyles that may affect carpooling practices, such as telework. Carpooling is defined here as the sharing of short- or long-distance car rides between people who are not members of the same household, for a trip (or part of a trip) already scheduled by the driver, free of charge or expense sharing. After a description of the corpus selection method used, followed by a brief review of existing literature, we propose three new avenues for research. The first avenue is a call for greater consideration of forms of transport, other than carpooling, to work (or to the place of study), which remain poorly studied. The second avenue proposes the investigation of the role that the current digitalisation of carpooling, namely online carpooling platforms and their integration into mobility platforms, and also the use of social media by carpoolers, could play in the coming years. The third avenue argues that the consequences of the rise of collaborative consumption and the current pandemic, namely teleworking practices and the perception of shared mobility, could have an effect on carpooling, which merits specific investigation.