Travel Purpose Research Articles

Pilot Study on Annual Horse Movements by Air and the Possible Effect of the Covid-19 Pandemic.

There is a lack of information on the number of horses shipped globally by air annually, the purpose of air travel and the routes of their journeys. This pilot study aimed to collect retrospective data on the international movements of horses by air from 2018 to 2021, describe their routes, and identify the possible effects of the coronavirus SARS-CoV-2 (COVID-19) pandemic. Equine transport data was gathered from 7 of 15 international shipping companies (ISCs) and 5 of 8 airlines contacted by email. The seven ISCs performed a median of 10,401 horse movements annually, ranging from a few hundred to several thousand movements per company, most frequently in Europe (Western and Northern Europe), Middle East/Africa (Middle East, Southern Africa), Asia Pacific (Australia), and the Americas (North and South America). The five airlines performed a median of 10,656 horse movements annually, importing and exporting horses to and from Europe, North America, Australasia, and the Middle East. For all but one airline, the number of horse movements decreased in 2020. The number and journey characteristics of horses transported by air require further scientific studies focused on the epidemiological and welfare risks unique to this type of transport to enable the development and implementation of best practices and regulations based on objective evidence.

COVID-19 Tests and International Travel: How Long Will You Test Positive for SAR-CoV-2?

Abstract: Coronavirus diseases, from SARS to MERS and now COVID-19, have major implications for the aviation industry and international travels. Although many cities and countries are adopting ‘live with COVID’ strategies, various rules and regulations are still in place. Documents demonstrating COVID-19 vaccination or recovery from the disease have now become a basic requirement to enter many travel destinations, while some still require pre-entry and/or post-arrival testing of COVID-19. Recently, the author’s household became COVID-19 positive in late March 2022, as diagnosed by rapid antigen test (RAT), in Singapore whilst enroute to Hong Kong. This had an immediate knock-on impact on hotel quarantine and travel arrangements. Rapid antigen test (RAT) and Polymerase Chain Reaction (PCR) based tests have been used for quarantine, isolation and international travel purposes. The implications and issues of these tests are discussed. Ideally, a COVID-19 test that is fit for purpose should aim at identifying individuals who are infectious with risk of transmission only. Frequent surveillance with an effective RAT may be a more practical solution to normalize international travel without compromising public safety. Meanwhile, physicians have an important role in counselling anxious and often confused travelers before and during international travels. International travelers should be aware of the implications of these COVID-19 testing results, and plan, schedule and have travel insurance accordingly

Infections in travellers returning to the UK: a retrospective analysis (2015-2020).

Every year, many thousands of travellers return to the United Kingdom (UK) from visits to other countries and some will become unwell due to infections acquired abroad. Many imported infections have similar clinical presentations, such as fever and myalgia, so diagnostic testing is an important tool to improve patient management and outcomes. The aim of this study was to examine the demographics, travel history, presenting symptoms and diagnostic outcomes of referrals to the UK's specialist diagnostic Rare & Imported Pathogens Laboratory (RIPL) for the period 2015-2020. Anonymised clinical and laboratory data were extracted from RIPL's Laboratory Information Management System and cleaned prior to descriptive analysis of the data. Travel history data were mapped to one of eight world regions, whereas symptom data were categorised into presenting syndromes. Diagnostic data were categorised as either positive, equivocal or negative. During the period 2015-2020, RIPL received 73 951 samples from 53 432 patients suspected of having infections that are rare in the UK. The most common age group for unwell returning travellers was 30-39years and the most commonly reported travel destination was Southern and SE Asia. Dengue virus was the most diagnosed infection overall, followed by chikungunya, Zika, leptospirosis and spotted fever group Rickettsia. Dengue virus was among the top three most frequent diagnoses for all world regions except Europe and represented 62.5% of all confirmed/probable diagnoses. None of the top five infections diagnosed by RIPL in travellers are vaccine-preventable, therefore understanding traveller demographics, destination-specific risk factors and encouraging preventative behaviours is the best available strategy to reduce the number of returning travellers who become infected. Prompt referral of acute samples with a detailed travel history, including purpose of travel and activities undertaken as well as dates and destinations can be a valuable tool in designing public health interventions and diagnostic algorithms.

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.

Study on the Spatial and Temporal Distribution and Traffic Flow Parameters of Non-Motorized Vehicles on Highway Segments Crossing Small Towns

The traffic flow of non-motorized vehicles on the highway segments crossing small towns is disorderly and chaotic. In order to improve the traffic environment and regulate the order of non-motorized operations, this article studies the spatial and temporal distribution and traffic flow parameters of non-motorized traffic on the highway segments crossing small towns. The non-motorized traffic within the section of the National Highway G310 crossing small towns in Henan Province, China, is investigated through various research tools such as questionnaires, interviews, and on-site statistics. The regularity and characteristics of non-motorized traffic in terms of travel purpose, travel distance, travel time, and travel frequency were obtained. Meanwhile, based on the actual collected traffic data, the speed–density relationship, flow rate–density relationship, and speed–distance relationship of non-motorized traffic flow were studied using mathematical and statistical methods. The results show that thresholds exist for both time and distance traveled by non-motorized vehicles on small town road sections. The threshold value of riding time is 30 min, and the threshold value of riding distance is 5 km. Under the free flow state, the speed distribution is near a certain desired speed, and the flow rate–density relationship conforms to the exponential function relationship when the flow rate is greater than the critical flow value. The speed and distance show a cubic function relationship, and the speed gradually increases with the increase in distance between the non-motorized vehicles and towns. Based on the results of the above analysis, it is possible to grasp the travel regularity of non-motorized cyclists on highway segments crossing small towns. This provides a theoretical basis for enhancing the efficiency of non-motorized travel and improving the non-motorized travel environment.

An experimental study on pedestrian movement in railway station

Railway stations are complex and concentrate significant passenger volumes. Urban population rising has a great impact on railway stations, as they are concentrating higher dense of people. Analyzing pedestrian movement assists in understanding their behavior and the quality of service of Public Transport infrastructure. This paper analyses how several factors such as age, gender, carrying backpack, social interaction, and travel purpose influence the average walking speed of pedestrians. An observational study conducted in the central Railway Station in Patras on Sundays during summer months. Day and hour of the observation were selected in order to study the behavior of pedestrians travelling in leisure time. Video footages used to investigate pedestrian movement and the factors that influence pedestrian dynamics. The mean speed was observed 30% lower than the values mentioned in Transit Capacity and Quality of Service Manual, which might be attributed to the travel purpose of pedestrians. In consistent with previous studies, the impact of age, carrying backpack, and walking in a group on pedestrian walking speed rates has been verified. Results also revealed a trivial effect of gender when the travel purpose is leisure activities and people are not in a rush.

СТАН РОЗВИТКУ ОЗДОРОВЧОГО ТУРИЗМУ В УКРАЇНІ

The global trend of recent years is the rethinking of the value of human life and the development of such tourist areas as health and medical tourism, which contribute to the restoration and strengthening of both the physical and psychological health of a person. For the formation of strategies for the development of health and medical tourism, taking into account the characteristics of each region, there is a need to conduct a cluster analysis that will determine the areas with the most potential for the development of the medical and health direction of the tourism sector. Therefore, the article aims to analyze the state and structure of health and medical tourism in Ukraine and to differentiate regional strategies for the development of the tourism sector. The article researched the general tourist potential of Ukraine, analyzed the development of health and medical tourism in Ukraine, investigated tourist flows by the purpose of travel, and analyzed the most attractive regions of the country by the reasons for the journey: treatment, leisure and recreation. Cluster analysis was done for the differentiation of regional tourism development strategies, which take into account the peculiarities of each region of the country and determine the territories where the medical and health direction of tourism prevails. The division into clusters by regions of Ukraine was carried out based on the indicators "Number of tourists in the region" and "Gross regional product" the last is one of the main socio-economic factors affecting tourist flows. The Dnipropetrovsk region, which is the most distant from others due to the high gross regional product, has been allocated to a separate tourist cluster. The second cluster is the Ivano-Frankivsk region, which is the most distant from others due to the number of tourists. In addition, the Vinnytsia region is highlighted as a separate cluster, which has both a high gross regional product and a significant number of tourists compared to others. The fourth cluster unites a group of regions with enough high levels of gross regional product and the number of tourists, respectively. The fifth cluster includes regions with a relatively low level of gross regional product and the number of tourists, respectively.

Analysis of Willingness to Pay for Toll Users in Central Java Province

Transportation infrastructure is a crucial component of national development. Road infrastructure development could lead to increased productivity, global competitiveness, employment opportunities, real sector growth, and reduced poverty. Therefore, this case study aimed to assess the willingness of toll road users in Central Java Province to pay for toll roads and the extent to which the parameters of gender, education, type of vehicle, and occupation affect the willingness to pay. The study also analyzed the variables influencing the toll user’s willingness to pay (WTP). These variables include road conditions, income, age, type of vehicle, frequency of toll users, and travel destinations. Eviews software was used to analyze the economic impact of toll users through logistics regression. Furthermore, Stata software was used to conduct a descriptive analysis of the questionnaire data. The results showed that the frequency of toll users has the greatest impact on willingness to pay, surpassing traffic conditions, type of vehicle, purpose of travel, and travel time. The odds ratio value for the toll user’s frequency was 66.85 [95% CI (13.02-343.07)]. It means that people using toll access more than 15 times are 66.85 times more willing to pay than those using the roads less frequently.

Exploring micromobility mode preferences for last-mile trips from subway stations

The micromobility mode of transportation is convenient for short-distance trips in urban settings. The popularity of dockless sharing systems is rapidly increasing because of their characteristics of convenient rental/return and mobile payment options. Although many previous studies have examined travel behaviors regarding a single means of micromobility transportation, few have analyzed mode choice behavior among multiple, similar, and competing means of micromobility transportation. To our knowledge, no researcher thus far has examined micromobility as a potential means to solve the last-mile problem from the subway station to the destination. Therefore, a stated preference survey was conducted, analyzing factors and preferences influencing the mode choice of subway users for the last-mile trip. This study considered sharing dockless e-scooters and docked bicycles, as well as walking. It analyzed the differences in mode choice behavior of subway users based on their demographic and socio-economic attributes, as well as travel (travel purpose and distance), mode-specific (fare), and environmental (slope) characteristics. Two logit-based models—the multinomial logit (MNL) and mixed logit (ML) models—and two ML models based on residential areas of Seoul and Gyeonggi, Korea, were developed and compared. The results showed that the ML model was superior to the MNL model regarding model fit and individual parameters. In the ML model, the statistically significant variables included fare, marital status, household size, age, income, disability, and slope of roadway. However, the significance differed by alternative modes: for e-scooters (vs. bicycles), the factors influencing last-mile mode choice behaviors showed greater statistical significance. A comparison of the two ML models by region highlighted major differences in the results for the variables of household size and trip purpose between residents of Seoul and Gyeonggi. Urban transport policymakers interested in introducing micromobility services can use the findings of this study to make more well-informed decisions about traffic congestion problems and increase public transportation revenue in an environmentally friendly manner.

Mode shifts from public transport to bike-sharing in the era of COVID-19: Riding back to normality

The pandemic led to the decrease of public transport use, which many passengers believed to have shifted from public transport to bike-sharing. We propose a novel methodology to quantify this shift and shed light on the causal factors of new preferences as well as the likelihood of their continuation. A first short-term intramodal analysis reveals important correlations between trip volumes and durations on the one hand, and COVID-19 policy measures on the other hand. COVID-19 significantly reduced all trips but public transport was hit harder and has not recovered so far. Shared-bike trip durations were extended during pandemic peaks. Then, we perform a second medium-term, disaggregate, and intermodal analysis to identify potential reasons explaining the shift from public transport to cycling. Logit models are specified on empirical ridership data from London and Washington DC. Results indicate that certain pre-covid factors (such as weather and type of day, travel purpose) remain influential under COVID-19. Also, we find facial covering obligation to be a key element in restoring public confidence towards public transport. Simple face covering recommendations seem, instead, to discourage public transport usage and play in favor of cycling.

Characteristics of Polish travellers: six-month experience from the University Centre of Maritime and Tropical Medicine in Gdynia, Poland.

The number of international travels has grown substantially over the last decade, both globally and in Poland. Thousands of Poles travel to tropical or subtropical countries in Asia, Africa or South America each year. The aim of this paper was to discuss the characteristics of Polish travellers seeking pre-travel consultation at the largest diagnostic and treatment travel medicine clinic in Poland. This retrospective study was based on the analysis of medical records of 1291 patients seeking pre-travel advice at the University Centre of Maritime and Tropical Medicine in Gdynia, Poland, between 1 July and 31 December 2022. The study comprised the analysis of the following patient variables: age, sex, travel details (purpose and length of travel, continents and countries to be visited, activities planned). The study also aimed to evaluate the range of prevention measures which were recommended/ administered (preventive vaccinations, chemoprophylaxis). In addition, it assessed the health status of the patients presenting at the travel medicine clinic. Patients who sought pre-travel advice were mostly people aged 18-35 years old (50.1%), travelling for tourism (72.2%), for a maximum period of 4 weeks (85.0%), travelling in December (24.3%) or in November (22.2%). Most of the Polish travellers consulted at the clinic travelled to Asia (56.2%), mainly to Thailand (27.3%), Vietnam (10.8%) or India (8.7%). Most travellers were planning a beach holiday (56.4%). As regards extreme activities, scuba diving was the most popular among the patients involved in the study (22.5%). The most frequently administered immunoprophylaxis were vaccines against typhoid fever (76.3%) and hepatitis A (56.2%). Other commonly recommended/prescribed prevention measures included: probiotics (75.9%), repellents (73.6%), antimalarial drugs (60.9%), and antidiarrheal antibiotics (51.9%). The analysis of patient interviews demonstrated that 42.4% of Polish travellers consulted at the clinic complained of no medical problems while 36.0% were taking chronic medications, mainly for allergies (17.1%) or thyroid disorders (12.2%). A growing number of people from Poland travel to destinations where the risk of infectious disease exposure or transmission is high. Providing a patient with appropriate advice during a pre-travel consultation will help protect the traveller against travel-associated risks at their intended destinations.

«ПЛИВУЧИ РЕЙНОМ, Я МАВ У РУКАХ ПРИДБАНІ У КЕЛЬНІ RHEIN- SAGEN І ЧИТАВ ЇХ, ЗВІРЯЮЧИ МІСЦЕВОСТІ, ЯКІ У НИХ ЗГАДУВАЛИСЯ НА САМІЙ ПРИРОДІ»: ПОГЛЯД НА НІМЕЦЬКІ ЗЕМЛІ МАНДРІВНИКІВ З НАДДНІПРЯНСЬКОЇ УКРАЇНИ У ХІХ НА ПОЧАТКУ ХХ СТ.

The article considers a range of issues related to travel to Germany in the 19 th – the beginning of the 20th century. Attention is drawn to the purpose of travel, routes, choice of objects for review, interethnic cultural contacts. It was established that the purpose of the trips to Germany were rest, treatment and education. Travelers got to Germany in different ways: by steamboat from Saint Petersburg through Sweden or overland through Radzivyliv, Lemberg and the Czech or Polish lands. Guidebooks printed in Germany became useful for travelers. They helped to develop of the travel route, choose the residence, objects for review and decide on means of transportation. The cities that attracted travelers the most were Berlin, Heidelberg, Leipzig, Munich, as well as the resorts of Baden-Baden and Kissingen. During of the 19th century, under the influence of changes in movement in European art – from romanticism to modernism, accents shifted, and interest arosed to various monuments and artistic masterpieces. While in the first half of the 19th century travelers were admired by Gothic architecture, works of the Renaissance, classical opera, ethnographic customs of the local population, in the second half of the 19 th century, attention was paid to modern art, achievements of science and technology, lifestyle, shops, cafes, etc. People, who traveled to Germany, expanded of social circle. There travelers were able to get to know representatives of European elites, leading scientists and practitioners, compatriots. Established contacts were usually long-lasting and multi-year. Sometimes under the influence of new acquaintances and European culture, imperial ideological stereotypes were destroyed and self-identification of travelers from Dnieper Ukraine took place. Keywords: travels, Germany, architectural monuments, memories, M. Rigelman, M. Kostomarov, Dresden Gallery, Cologne Cathedral.

Enhancing Tourists’ Satisfaction Through Blockchain Technology

Background: Blockchain technology, a decentralized ledger system, offers a secure and transparent means to record transactions, holding promise for enhancing tourists' contentment within the travel industry. Objective: The aim of the study was to assess how blockchain technology impacts tourists' trust, willingness to pay, and environmental considerations. Methodology: Employing a qualitative research approach combined with thematic analysis, the study was conducted. The research was conducted in the Kolkata region of West Bengal. Sample size was 18 participants who were tourists utilizing travel agency services for travel purposes. Data was collected by semi-structured interview. Thematic was utilized to analyze the interview data. Results: The research unveiled that respondent possessed a solid comprehension of blockchain technology and recognized its potential effects on the travel sector. Their preference leaned towards travel-related products and services utilizing blockchain, driven by the belief in heightened security, efficiency, and cost-effectiveness. Furthermore, respondents expressed a willingness to invest more in travel offerings incorporating blockchain technology, assuming it would deliver superior security, transparency, efficiency, sustainability, and innovation. Conclusion: The study's outcomes affirm that blockchain technology holds the potential to significantly enhance tourists' satisfaction within the travel industry. Nonetheless, further investigation is required to explore the precise mechanisms by which blockchain can elevate tourists' experiences.

What features of digital travel-related information is generation Z looking for?

Purpose - The study aims to identify segments of Generation Z based on common digital information features used for travel purposes. Generation Z is specific generation in terms of digital information use as they have grown up as digital natives unlike older generations. Methodology/Design/Approach – Students representing Generation Z are studied by collecting data from a structured online questionnaire consisting of Likert-type scales on digital information features. The questionnaire also includes travel-related benefits and some demographic characteristics of the respondents. Principal component analysis is performed to identify the factors underlying the information features sought, followed by K-Means clustering applied to the identified factors. The characteristics of the clusters are analysed. Findings - Based on the importance of digital travel-related information features, two distinct segments are identified to be targeted through digital marketing. The larger segment “Practical information seekers” looks for accessible and secure information and the smaller segment “Genuine information seekers” focuses on authenticity of information. Originality of the research - The study confirms the heterogeneity of the Generation Z travel market by identifying two distinct segments that pursue different digital information features.

Evolution of teleworking and urban mobility changes driven by the COVID-19 pandemic across European Cities

Work-related travel is one of the primary travel purposes for citizens (Eurostat, 2021). The COVID-19 pandemic triggered significant changes in lifestyles and mobility that may persist in the long term. Teleworking and online shopping are much more widely adopted than before the pandemic crisis, while active mobility modes have gained a considerable share of urban transport activity. Restrictions in response to the COVID-19 pandemic have shown that several activities developed within the city can be done by ICT tools, such as working from home or shopping online, among others. Those tools can be used to avoid -potentially- unnecessary trips and consequently reduce Green House Gas (GHG) emissions. This work aims to determine how the COVID-19 pandemic affected the adoption of teleworking and how mobility behaviour has changed during the pandemic. It also explores the factors that may affect mobility changes, their long-term effects and potential repercussion on GHG emissions.To do so, we use an extensive survey carried out in 20 European cities across 11 Member States, applying statistical inference analysis among different categories of variables focusing on active workers. Results show that teleworking has grown significantly during the pandemic, both in the number of users and in the frequency of use. The change in mobility patterns has been significant and might serve as a lever for change towards a more sustainable mobility, but also for the worse if the right decisions are not made consequently.

Data Analytics and Predictive Modeling for Toll Violation Prevention

This study aims to utilize data analytics and predictive modeling techniques to prevent toll violations. By analyzing various sources of data such as travel datasets, unstructured data, and financial data, the study will develop algorithms that can accurately predict toll violations and identify potential fraud patterns. The research, which utilized unstructured data, points to the utility of data mining which would greatly benefit traffic research, particularly African-based studies, that suffer from data inadequacy. The study will also explore the use of machine learning algorithms to decipher the large textual data contained in transportation research papers. Additionally, the study will investigate the accuracy and performance of different predictive algorithms, such as linear regression, analysis of variance, and artificial neural networks, in predicting toll violations based on various factors such as category, purpose, total distance, and speed of travel. Furthermore, the study will examine the forensic aspects of big data in order to enhance the capabilities of forensic investigators in case of a network attack. In today’s rapidly changing world, the significance of accurate toll violation prevention using data analytics and predictive modeling techniques cannot be overstated. In today’s rapidly changing world, the significance of accurate toll violation prevention using data analytics and predictive modeling techniques cannot be overstated. By leveraging data analytics and predictive modeling, this study aims to develop an effective toll violation prevention system

Understanding the Effect of Built Environment on Travel Behavior at Multiple Geographic Scales

Understanding the effect of built environment on travel behavior has been an important research issue in transportation, geography, and urban planning. Geographic scales for travel behavior research have started attracting attentions in recent years. In this research, we proposed a method to extract suitable geographic scales of built environment influence on travel behavior with different travel purposes. We designed a modeling framework to examine different types of corresponding scales that affect the relationships between travel behavior and the built environment. The scale-correspondence covers the aspects of geography, model, and indicators. In a real travel data supported case study, the results show a stronger and more explainable influence from built environment on travel distance and travel mode choices at scale-corresponding models than that with the non-scale-corresponding models. We discovered that all three types of scale correspondence can reduce the geographic-contextual uncertainty in both travel and built environment contexts. The results of this study offer methodological insights that may facilitate further research investigating travel behaviors.

Emotional wellbeing in intercity travel: Factors affecting passengers' long-distance travel moods.

The travel mood perception can significantly affect passengers' mental health and their overall emotional wellbeing when taking transport services, especially in long-distance intercity travels. To explore the key factors influencing intercity travel moods, a field survey was conducted in Xi'an to collect passengers' individual habits, travel characteristics, moods, and weather conditions. Travel mood was defined using the 5-Likert scale, based on degrees of happiness, panic, anxiety, and tiredness. A support vector machine (SVM) and ordered logit model were used in tandem for determinant identification and exploring their respective influences on travel moods. The results showed that gender, age, occupation, personal monthly income, car ownership, external temperature, precipitation, relative humidity, air quality index, visibility, travel purposes, intercity travel mode, and intercity travel time were all salient influential variables. Specifically, intercity travel mode ranked the first in affecting panic and anxiety (38 and 39% importance, respectively); whereas occupation was the most important factor affecting happiness (23% importance). Moreover, temperature appeared as the most important influencing factor of tiredness (22% importance). These findings help better understand the emotional health of passengers in long-distance travel in China.

STABILITY ANALYSIS FOR URBAN TRAFFIC EVOLUTION PROCESS USING TEMPORAL TRAFFIC STATE PATTERNS

Recognizing the stability of the traffic evolution process of urban traffic networks has been an important consideration in traffic evolution research. However, little work has been conducted on identifying and associating temporal Traffic State Pattern (TSP) with the traffic evolution process. By clustering multi-dimensional traffic time series, we attempted to map the traffic evolution process into massive transitions of consecutive TSPs. Through the statistics of the time distribution of the transitions, we then defined the stability coefficient to conduct a quantitative analysis of the traffic evolution process. An empirical study using 30 days of traffic flow rate data of multiple road sections from the network of Nanshan District (Shenzhen, China) was carried out. Numerical results indicated that the traffic evolution process experienced obvious nonlinear changes at different periods of the day, but presented a regular cycle characteristic from morning till night. Further, with consideration of different travel purposes and traffic features on weekday and weekend, more traffic dynamics was extracted, which would be conducive to understand the complex behaviour of traffic evolution process.

COVID-19 stimulated travel behavior policy framework with evidence from travel change in southwestern Nigeria

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.