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Corrigendum to Travel behavior changes during the COVID-19 pandemic in Japan: Analyzing the effects of risk perception and social influence on going-out self-restriction [Transp. Res. Interdiscip. Perspect. 7 (2020) 100181

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... However, the proximity information of the plausibility of being infected by COVID-19 can potentially influence a modal shift from environmentally more sustainable public transportation to less-sustainable private car use for an urban and long-distance commutes (Gutiérrez et al., 2020). Dong et al. (2021) examined the passengers' perceptions of safety and satisfaction toward using public transportation during COVID, asserting that its psychological effects (Parady et al., 2020) will possibly linger in the post-COVID era. Thus, they recommended that to avoid a modal switch from public to private transportation, there would be a need to eliminate the lingering effects of the pandemic on the public transportation system. ...
... Thus, factoring all the associated factors, as shown in Figure 3, a holistic pre-, during and post-pandemic transportation policy can be developed going forward. Hence, as we advance post-COVID, proactive and sustainable transportation policies will be critical in future pandemic impacts (Dong et al., 2021;Parady et al., 2020). The COVID-19 informed travel behavior framework considering hybridized SPT and TIB could be a good starting point for formulating and implementing the future, holistic, sustainable transportation policy pre-, during, and post-pandemic. ...
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The COVID-19 pandemic unprecedentedly redefined urban mobility as some spread containment protocols, such as lockdown, travel restrictions, and physical distancing, directly impinged mobility: these policies or personal health concerns altered travel behavior during the first and the second waves of the pandemic. Transportation users' reactions to the spread of COVID-19 vis-à-vis the government-imposed containment strategies hinged on the theory of interpersonal behavior and social practice theory, informing that the travel behavior cultured during the waves may become a practice as we advance. This paper investigated the extent of preferential modal shift and travel change during the waves of COVID-19 toward developing a travel behavior framework for a more holistic transportation policy for pre-, during, and post-pandemic periods. This COVID-induced urban mobility assessment sourced primary data from transportation users during Phase 2 of the COVID-19 intervention in southwestern Nigeria. The findings show that COVID-19 has a weak but positive relationship with transportation means change. A private vehicle use mode preference was evident, and daily travel patterns skewed towards the weekends. Most participants felt the state border restrictions every day of the week, and most of the transportation users who commuted were essential workers. At the same time, a medium-range positive association for COVID outings due to travel purpose and employment type informed that the unemployed dominated sports and leisure trip purposes, evidence of exigent travel. Dips in routine travel purposes, geographical extent, and modal choice imply unsustainable economic decisions and must be forestalled post-COVID. The paper recommends an evidence-based COVID-19 travel behavior policy framework for systemic, sustainable transportation policy formulations effective pre-, during, and post-pandemics.
... Although mobility restrictions were not that strict, the response of the population towards these governmental requests led to a significant reduction in the number of trips, with the number of inter-prefectural travel halved across the country compared to pre-pandemic conditions [76]. Changes in human behavior during the pandemic are a cognitive response to the immediate threat of COVID-19, which has an indirect effect on the reduction in disease transmission [77]. Another crucial contribution of the present study is the explicit modeling of the shape of exposure-lag-response associations between mobility patterns and time-varying transmissibility. ...
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We assess the effects of ambient temperature and mobility patterns on the transmissibility of COVID-19 during the epidemiological years of the pandemic in Japan. The prefecture-specific daily time-series of confirmed coronavirus disease 2019 (COVID-19) cases, meteorological variables, levels of retail and recreation mobility (e.g., activities, going to restaurants, cafes, and shopping centers), and the number of vaccinations were collected for six prefectures in Japan from 1 May 2020 to 31 March 2022. We combined standard time-series generalized additive models (GAMs) with a distributed lag non-linear model (DLNM) to determine the exposure–lag–response association between the time-varying effective reproductive number (Rt), ambient temperature, and retail and recreation mobility, while controlling for a wide range of potential confounders. Utilizing a statistical model, the first distribution of the mean ambient temperature (i.e., −4.9 °C) was associated with an 11.6% (95% confidence interval [CI]: 5.9–17.7%) increase in Rt compared to the optimum ambient temperature (i.e., 18.5 °C). A retail and recreation mobility of 10.0% (99th percentile) was associated with a 19.6% (95% CI: 12.6–27.1%) increase in Rt over the optimal level (i.e., −16.0%). Our findings provide a better understanding of how ambient temperature and mobility patterns shape severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. These findings provide valuable epidemiological insights for public health policies in controlling disease transmission.
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Mobility and out-of-home activities restrictions from the COVID-19 pandemic have forced people to maximize their in-home activities. Considering the increase in Information and Communication Technology (ICT) adoption during the outbreak, this paper tries to shed light on the factors that influence changing travel behavior. For these purposes, the study uses data collected through an online questionnaire during the outbreak in Indonesia, which was then analyzed using cluster and discriminant analyses. The study found that online adaptation during the outbreak was affected by income level, whereby high-income individuals are associated with high online adaptation. Residential location also influences ICT adaptation during the outbreak. Cities with higher access to the internet and ICT platforms as well as higher income per capita tend to have higher ICT adoption. People with more experience with online platforms or services also record higher online in-home activity adoption during the outbreak. Furthermore, while the lower-income group tends to reduce their travel, the higher-income group still continues to travel to fulfil their household needs during the outbreak, such as in-store shopping. Since the lower-income group and less accessible areas tend to have difficulty in accessing ICT as a substitute for travel, this study recommends that the government and ICT stakeholders ensure equal access to ICT to support physical distancing and to limit mobility in order to flatten the peak of the pandemic.
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By the end of 2021, the Omicron variant of coronavirus disease 2019 had become the dominant cause of a worldwide pandemic crisis. This demands a deeper analysis to support policy makers in creating interventions that not only protect people from the pandemic but also remedy its negative effects on the economy. Thus, this study investigated people’s mobility changes through the relationship between spatiotemporal population density and urban facilities. Results showed that places related to daily services, restaurants, commercial areas, and offices experienced decreased visits, with the highest decline belonging to commercial facilities. Visits to health care and production facilities were stable on weekdays but increased on holidays. Educational institutions’ visits decreased on weekdays but increased on holidays. People’s visits to residential housing and open spaces increased, with the rise in residential housing visits being more substantial. The results also confirmed that policy interventions (e.g., declaration of emergency and upgrade of restriction level) have a great impact on people’s mobility in the short term. The findings would seem to indicate that visit patterns at service and restaurant places decreased least during the pandemic. The analysis outcomes suggest that policy makers should pay more attention to risk perception enhancement as a long-term measure. Furthermore, the study clarified the population density of each facility type in a time series. Improving model performance would be promising for tracking and predicting the spread of future pandemics.
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Backgrounds The effectiveness of citizens’ behavioral changes to prevent the spread of SARS-CoV-2, such as avoiding large social events, relies on science communication from policymakers and collective action among peer citizens. Extant studies recognize the potential effects of information stimuli on citizens’ behavioral changes, including what epidemiological experts request ( injunctive information ) and what surrounding people behave ( descriptive information ). Yet, they have insufficiently assessed the co-occurrence and possible interaction of multiple information stimuli. Methods 1,819 Japanese citizens aged 18 or over were recruited for an experimental survey during March 1–3, 2021 and asked their views on a hypothetical wedding attendance in Japan while being exposed to randomly assigned normative information stimuli. Their willingness to attend a wedding asked before and after the intervention was measured. Infection risk perception was also asked as a mediating variable. Results Findings suggest the constant supremacy of descriptive information and no synergistic effects in the interaction of multiple information stimuli. We also report that the effects of injunctive and descriptive information vary according to participants’ risk perception, age, and trust in experts. Conclusion Our experimental test enables a systematic assessment of multiple normative information and confirms the primacy of descriptive information as the main driver of behavioral change. Communication by medical experts has limitations but is still effective in specific categories of the population.
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We analyzed time-series changes in people’s purpose-specific mobility characteristics owing to the COVID-19 pandemic in the Tokyo area of Japan, where only legally non-binding requests for self-restraint were enforced. A multiple regression analysis was conducted with the objective variable being the mobile population in the Tokyo area per 500 m square grid estimated from mobile spatial statistical data for 2 years from 10/01/2019 to 9/30/2021. This study period ranges from pre- to mid-pandemic. The explanatory variable was the number of buildings by type per 500 m square grid obtained from building statistical data to determine behavioral changes by mobility purpose. The analysis revealed that self-restraint was sustained until the middle of the COVID-19 pandemic in the Tokyo area regardless of the purpose of mobility and whether a state of emergency was declared.
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The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection.
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Human behavioural changes are poorly understood, and this limitation has been a serious obstacle to epidemic forecasting. It is generally understood that people change their respective behaviours to reduce the risk of infection in response to the status of an epidemic or government interventions. We must first identify the factors that lead to such decision-making to predict these changes. However, due to an absence of a method to observe decision-making for future behaviour, understanding the behavioural responses to disease is limited. Here, we show that accommodation reservation data could reveal the decision-making process that underpins behavioural changes, travel avoidance, for reducing the risk of COVID-19 infections. We found that the motivation to avoid travel with respect to only short-term future behaviours dynamically varied and was associated with the outbreak status and/or the interventions of the government. Our developed method can quantitatively measure and predict a large-scale population’s behaviour to determine the future risk of COVID-19 infections. These findings enable us to better understand behavioural changes in response to disease spread, and thus, contribute to the development of reliable long-term forecasting of disease spread.
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Background COVID-19 had a devastating impact on people's work, travel, and well-being worldwide. As one of the first countries to be affected by the virus and develop relatively well-executed pandemic control, China has witnessed a significant shift in people's well-being and habits, related to both commuting and social interaction. In this context, what factors and the extent to which they contribute to well-being are worth exploring. Methods Through a questionnaire survey within mainland China, 688 valid sheets were collected, capturing various aspects of individuals' life, including travel, and social status. Focusing on commuting and other factors, a Gradient Boosting Decision Tree (GBDT) model was developed based on 300 sheets reporting working trips, to analyze the effects on well-being. Two indicators, i.e., the Relative Importance (RI) and Partial Dependency Plot (PDP), were used to quantify and visualize the effects of the explanatory factors and the synergy among them. Results Commuting characteristics are the most critical ingredients, followed by social interactions to explain subjective well-being. Commuting stress poses the most substantial effect. Less stressful commuting trips can solidly improve overall well-being. Better life satisfaction is linked with shorter confinement periods and increased restriction levels. Meanwhile, the switch from in-person to online social interactions had less impact on young people's life satisfaction. Older people were unsatisfied with this change, which had a significant negative impact on their life satisfaction. Conclusions From the synergy of commuting stress and commuting time on well-being, the effect of commuting time on well-being is mediated by commuting stress in the case of China. Even if one is satisfied with online communication, the extent of enhancement on well-being is minimal, for it still cannot replace face-to-face interaction. The findings can be beneficial in improving the overall well-being of society during the pandemic and after the virus has been eradicated.
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Extracting knowledge from open data of traffic accidents has been attracting increasing attention to policymakers responsible for road safety. This article presents a knowledge elicitation approach to exploring the determinants of traffic accidents from open government data of an urban area in Taiwan. The collected open dataset contains 34 decisional attributes and one predictive attribute (i.e., type of injury, including head, breast, leg), and 47,974 cases. Prediction models using a classification-oriented mechanism and generated rules that considered datasets from before (B-dataset; 30,116 cases) and after (A-dataset; 17,868 cases) beginning to combat the Covid-19 pandemic in an urban area of Taiwan were compared. The findings showed that prediction accuracy was acceptable but not high, at 70.73% for B-dataset and 74.77% for A-dataset. Determinants in the human and vehicle categories revealed higher classification ranks than those in the temporal and environment categories. Traffic accidents involving motorcycles were 5.13% higher in A-dataset, whereas those involving cars were 4.11% lower. Injury on leg or foot was 3.46% higher in A-dataset, whereas other types of injury were up to 1.00% lower. The average support for rules in the A-dataset rule base and the simplicity of the A-dataset decision tree were higher than those of B-dataset. The research demonstrates the value of open government data in prediction model development and knowledge elicitation to support policymaking in the traffic safety domain.
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Since the start of COVID-19 pandemic, public transport has been signalled as a potential contagion hot-spot, leading to a generalised decrease in its use. However, public transport use is still being used and little is known about how the perception of loyal users is configured in contexts of influenza-like viruses such as SARS-CoV-2. The configuration of the perception of safety acquires a critical importance in urban contexts where the public transport system is used both by tourists and local users. The presence of strangers or higher crowding levels could impact the perception of safety among residents and their consequent travel behaviour. In the present study, we explored how the presence of tourists influences the configuration of the perception safety related to the transmission of COVID-19 on public transport of daily users. We used data from an ad-hoc survey conducted at the main bus stations and stops of the Tarragona Urban Area (Catalonia, Spain) between August and September 2020. This area includes the Costa Daurada coastal destination. The 2020 summer holiday season was characterised for the relaxation of mobility restrictions and the start of the second wave of COVID-19. Results show how the presence of tourists in buses negatively influenced the perception of safety of local users. However, this influence can be mostly explained to their prior perception of risk of contagion. These findings will be useful for policymakers and public transport managers in both the latter stages of the COVID-19 pandemic and future virus-related epidemics to maintain public transport ridership.
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The COVID-19 outbreak has significantly impacted people’s mobility in terms of travel, which is directly related to regional economic vitality and individuals’ well-being. This study conducted research on the COVID-19 epidemic’s impact on travel mobility in China’s Greater Bay Area, utilizing mobile phone big data. The overall influence of COVID-19 was measured by investigating the impact between different income and migration groups in three core cities: Shenzhen, Guangzhou, and Foshan. Individuals’ weekly activity space area and travel frequency were calculated, and the average values between the different cities and various social groups were compared. The results showed that travel mobility declined during the epidemic’s peak, followed by a recovery based on the overall trend. The start and end of strict law enforcement had a significant impact on the initial decline and subsequent recovery of travel mobility in the core cities. COVID-19 had a larger impact on core cities than peripheral areas, and on non-commute travel frequency, compared to commute travel frequency. Compared to advantaged groups, socially disadvantaged groups experienced a steeper decline in travel mobility during the epidemic’s peak, but a more significant recovery afterwards. These findings indicate that discretionary activities have not yet recovered and remain below the pre-epidemic level, and that disadvantaged social groups had limited access to superior precautionary measures for avoiding infection. Based on the findings, we provide several policy suggestions regarding the recovery of travel mobility.
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COVID-19 is one of the worst global health crises in a century. Japan confirmed its first case of COVID-19 in mid-January and declared a state of emergency in April and May 2020, urging people to stay at home and reduce travel. Using Mobile Spatial Statistics (i.e., population statistics created from operational data of mobile terminal networks), we estimated daily intra- and inter-prefectural population mobility in the Tokyo Megalopolis Region, Japan in 2020. Then, we developed a compartmental model with population mobility to explore the role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19. This model describes the COVID-19 pandemic through a susceptible-exposed-presymptomatic infectious-undocumented and documented infectious-removed (SEPIR) process and incorporates intra- and inter-prefectural population mobility into the transmission process. We found that people significantly reduced travel during the state of emergency, although stay-at-home requests and travel restrictions were recommended rather than mandatory. The reduction in population mobility, combined with other control measures, resulted in a substantial reduction in effective reproduction numbers to below 1, thus controlling the first wave of the pandemic. Moreover, the relationship between population mobility and COVID-19 transmission changed over time. The dampening of the second wave of the pandemic indicated that smaller reductions in population mobility could result in pandemic control, probably because of other social distancing behaviors. Our proposed model can be used to analyze the impact of different public health interventions, and our findings shed light on the effectiveness of soft containments in curbing the spread of COVID-19.
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This study aims to determine how the COVID-19 pandemic affects career anxiety of tourism students, who are the potential future employees of tourism and hospitality industry. Data was collected using an online survey with 1097 undergraduate students in the field of tourism in Turkey. The results of the study revealed that perceived risk of infection and fear of COVID-19 significantly impact students' career anxiety, and fear of COVID-19 mediate the relationship between perceived infection risk and career anxiety. In addition, the results indicated that psychological resilience, which is an individual resource against difficulties, represents a factor that reduces career anxieties of students in the face of pandemic-related negative impacts. The findings contribute to the understanding of how pandemic diseases affect career anxiety in students, who are the future workforce of the tourism sector, and to determine the role of individual resources such as psychological resilience in this process. Key Words: COVID-19 fear, Perceived risk of infection, psychological resilience, career anxiety, Tourism and hospitality education
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Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people's travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals' travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people's responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals' transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.
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The arrival of the coronavirus in 2020 brought major changes to education, with the rapid transition to online classes being the most significant. In the case of university students, the pandemic meant returning to their homes, which can be interpreted as a temporary destudentification. This manuscript analyses and interprets the motivations of university students from Temuco (Chile) to change their social relations and place of residence as a consequence of the COVID-19 pandemic. Through a quantitative methodology that used more than 800 online surveys and a principal component analysis, it was concluded that the psychological well-being and the security provided by the family were the main causes for changing accommodation; but a total of four main components related to material conditions, economic aspects, family and psychological and physical well-being were identified. Similarly, although with the pandemic the family was the most reinforced dimension in terms of social relations, there were groups of students who were more connected to friends and colleagues or neighbours. The results point to a partial and temporary destudentification, explainable by the nature of the lease contract and the dependent role of the students with respect to the landlords.
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