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Since its outbreak in December 2019, COVID-19 has spread rapidly across the world. To slow down the spread of the pandemic, various countries have implemented a series of policies and measures. The transportation system is not only an important carrier for COVID-19, but also a vital means for the prevention and control of the spread of the pandemic. Therefore, most anti-pandemic measures are based on travel restrictions, thereby slowing down the spread of the pandemic. As a result, because of the impact of the pandemic and corresponding control measures, the transportation system has undergone tremendous changes. By analyzing the evolution of the transportation system in response to the influence of COVID-19, it is possible to better understand socioeconomic changes and the changes in residents' daily life. Based on rich license plate recognition data, the characteristics of urban motorized travel under the influence of COVID-19 has been analyzed. According to the processes associated with the control of the pandemic and the resumption of work and production, the analysis period is divided into four stages. The changes in indicators of macroscopic traffic status are analyzed for each stage. The three types of typical motor vehicle groups (i.e., non-localized operating vehicles, taxis, and localized operating vehicles) are characterized by the traffic flow they contribute, the number of vehicles in transit, the average travel intensity, the average daily travel time of a vehicle, the average daily travel distance of a vehicle, and the spatiotemporal distributions of origins and destinations of trips. These data clarify the spatiotemporal evolution characteristics of peoples' travel behavior at different stages of the pandemic. The results of data analysis show that COVID-19 has deeply changed the motorized travel behavior of urban residents. In the initial stage of resumption of work and production, the willingness to engage in motorized travel had decreased significantly compared with that in the first stage. This willingness gradually resumed until the third and fourth stages, but still did not fully reach the level before the onset of the pandemic. Specifically, the traffic status during morning and evening peaks has basically recovered, and has even increased beyond the level before the pandemic; however, a certain gap was still found between off-peak hours. There were also significant differences in the extent to which different types of vehicles were affected by the pandemic. Among these, taxis were impacted the most by the pandemic. In the fourth stage (at the end of April), the average daily travel time of a vehicle and the average daily travel distance of a vehicle still decreased by 29.25% and 22.63% compared with the first stage, respectively. The operating time of many taxis was shortened from 22:00 PM to 19:00 PM. The spatiotemporal characteristics of vehicles show that the reduction of flexible travel demand (e.g., shopping, catering, and entertainment) is key to the reduction of the travel demand of the road network. This research provides data support for the implementation of traffic control measures under future grave public health events and enables the formulation of urban traffic policies in the post COVID-19 era. [ABSTRACT FROM AUTHOR]

The coronavirus outbreak was declared a pandemic in 2019, a once‐in‐a‐lifetime event that tested the limits of humanity. The number 2019 is a memorable year that the entire humanity will hardly forget as the world had fitted against this virus. The pandemic has so far changed the habits of people all over the world. The World Health Organization (WHO) has defined a list of barrier measures that have been implemented and are still effective in several countries. Among these measures, social distancing remains the most important. It requires people to avoid physical contact and not to exchange possessions. However, during road checks in Cameroon, police officers usually check passengers by asking them to show their national identity card. After receiving the ID card, a police officer checks the information on the card and returns it to the holder at the end of the check. This process goes beyond the new regulation and contributes to the spread of the Covid'19 virus. This paper considers this issue as an engineering problem and proposes a new approach based on Information and Communication Technology (ICT) to carry out the road traffic control activities. An automatic control system is proposed. It has two main functionalities namely the positioning subsystem and the Data collection subsystem. The positioning subsystem allows the road traffic controller in defining the right position where he/she should stand to collect information from passengers while the data collection subsystem collects data from the ID card presented by each passenger in the car. This approach was tested at police checkpoints on the Douala‐Yaoundé road in Cameroon and the results showed a reduction in COVID‐19 cases related to document handling between police and passengers/drivers. [ABSTRACT FROM AUTHOR]

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development. [ABSTRACT FROM AUTHOR]

The article presents the problem of the cargo transport with the example of a selected mode of transport in Poland. The volume of goods transported by air transport in 2010-2021 was analysed. Cargo transport in air transport is very popular. From year to year, there is an increase in the volume of transported goods. The coronavirus pandemic, and the related economic crisis did not significantly affect cargo transport, as was the case with passenger transport, the number of which decreased significantly during the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has shown to be a global challenge that, in addition to other effects, has influenced travel behavior. This study examines factors affecting academic travelers' mode choice before and during the pandemic and factors contributing to sustainable transportation on campus. By examining their travel patterns and behaviors, we contribute to understanding transportation preferences and identifying opportunities for sustainable transportation on university campuses. Studying academic travelers is crucial as they are significant daily travelers with a substantial impact on transportation systems and the environment. Understanding their mode choices helps transportation planners and policymakers promote sustainable transportation options. The literature has identified influential factors in making trips to university campuses, including age, gender, accommodation, cost, and travel time. However, cross-sectional studies involving comprehensive variables are lacking and the influence of the COVID-19 pandemic on transportation has not been thoroughly evaluated. To address this gap, the current study aims to evaluate novel variables, including intra-transport modes, entry permits, accessibility, parking availability, occupations, level of study, travel purpose, and visit frequency. The University of Isfahan, accessible by all modes of transport, was selected as the study area. After analyzing the questionnaire and variables using SPSS software (IBM SPSS Statistics for Windows, Version 22.0 Released 2013), travel behavior was studied by discrete choice models and the models' coefficients were estimated using NLOGIT. The finding demonstrated that using private modes (taxi, private vehicle, and active modes) increased in response to the pandemic, while using public modes (bus or subway) represented a decline. Before and during the pandemic, most people who had the same trip purpose shifted from taking the bus to using private vehicles and active transportation. Generally, people became more inclined to walk on campus during the pandemic. This study aimed to examine the travel behavior of academic travelers, who possess diverse travel choices compared with typical commuters, thus providing valuable insights into how the broader population might respond to different transportation options. The findings offer a novel perspective for university and city planners, enabling more informed decisions regarding sustainable development in campus areas. [ABSTRACT FROM AUTHOR]

Objective - The objective of the research was to examine the mental health of Croatian high-school students before and during the COVID-19 pandemic with regard to gender, age, school, residence, family structure, and parents' education. Materials and Methods - Total of 211 15-year-old first grade high-school students completed the YP-CORE questionnaire in the 2020, just before the lock-down enforced due to the COVID-19 pandemic. In 2022, now being 17-year-olds, 3rd-grade high-school students filled out the YP-CORE questionnaire once again during the COVID-19 pandemic. Socio-demographic data were collected from the participants' health charts. Results - The median YP-CORE score significantly increased from 7 in 2020 to 11 in 2022. A significant increase in psychological distress was determined, from 11% of adolescents in the pre-pandemic period to 23% of adolescents in the pandemic period. Significantly higher rates were reported by girls in both periods. Students from the School of Applied Arts and Design reported psychological distress significantly more often than students from the Electrical Engineering and Traffic School and the Grammar School before and during the pandemic. Family structure was significantly associated with YP-CORE scores only in the pre-pandemic period. Conclusion - The study showed that the COVID-19 pandemic had negative impact on mental health of Croatian adolescents, with certain sociodemographic risk factors being associated with poorer mental health outcomes. [ABSTRACT FROM AUTHOR]

The latest epidemic of COVID‐19 has significantly impacted both human capital and the global economy, contributing to pandemics and severe global crises. Research into the creation and propagation of the disease is desperately needed. The Internet of Things, cloud computing, and artificial intelligence offer modern technology for real‐time processing for multiple applications such as healthcare applications, transport, traffic control, and so on blockchain is an evolving technology that will dramatically boost transaction protection in finance, supply chain, and other transaction networks. A stable and latency‐sensitive Quality of Service framework for COVID‐19 is the need of an hour. The purpose of this paper is to combine Fog computing and Artificial Intelligence with smart health to establish a reliable platform for early‐stage detection of COVID‐19 infection. A new ensemble‐based classifier is proposed to detect COVID‐19 patients. This research offers a blockchain platform to analyse how the unrelated cases of the COVID‐19 virus can be tracked and identified using peer‐to‐peer, time stamping, and the shared storage advantages of blockchain. In addition to growing patient loyalty, this would effectively enhance the consistency, flexibility, productivity, performance, and effectiveness of healthcare services. The idea of blockchain is used to establish security for the whole framework. Different implementations measure the efficiency of the suggested system. The performance of the proposed framework is evaluated in terms of delay, network usages, RAM usages, and energy consumption. On the other hand, the classifier is evaluated in terms of classifier accuracy, recall, precision, kappa static, and root mean square error. The result shows the performance of the proposed framework and classifier is always better than the traditional frameworks and classifiers. [ABSTRACT FROM AUTHOR]

The rapid global spread of the coronavirus disease 2019 (COVID-19) is now a reality. China has taken urban traffic control measures to prevent and control the epidemic, but this has prevented the flow of people between cities. This study investigates the mechanism of the impact of urban traffic control measures on the intercity population flow in China using the one-way causal measurement method. The results show that the impact of urban traffic control measures on the intercity flow of the population changes with time. Based on this, this study makes scientific suggestions for the government on how to reasonably undertake traffic control measures. [ABSTRACT FROM AUTHOR]

With the spread of the COVID-19 pandemic and the implementation of closure measures in 2020, population mobility and human activities have decreased, which has seriously impacted atmospheric quality. Huaibei City is an important coal and chemical production base in East China, which faces increasing environmental problems. The impact of anthropogenic activities on air quality in this area was investigated by comparing the COVID-19 lockdown in 2020 with the normal situation in 2021. Tropospheric NO2, HCHO and SO2 column densities were observed by ground-based multiple axis differential optical absorption spectroscopy (MAX-DOAS). In situ measurements for PM2.5, NO2, SO2 and O3 were also taken. The observation period was divided into four phases, the pre-lockdown period, phase 1 lockdown, phase 2 lockdown and the post-lockdown period. Ground-based MAX-DOAS results showed that tropospheric NO2, HCHO and SO2 column densities increased by 41, 14 and 14%, respectively, during phase 1 in 2021 vs. 2020. In situ results showed that NO2 and SO2 increased by 59 and 11%, respectively, during phase 1 in 2021 vs. 2020, but PM2.5 and O3 decreased by 15 and 17%, respectively. In the phase 2 period, due to the partial lifting of control measures, the concentration of pollutants did not significantly change. The weekly MAX-DOAS results showed that there was no obvious weekend effect of pollutants in the Huaibei area, and NO2, HCHO and SO2 had obvious diurnal variation characteristics. In addition, the relationship between the column densities and wind speed and direction in 2020 and 2021 was studied. The results showed that, in the absence of traffic control in 2021, elevated sources in the Eastern part of the city emitted large amounts of NO2. The observed ratios of HCHO to NO2 suggested that tropospheric ozone production involved NOX-limited scenarios. The correlation analysis between HCHO and different gases showed that HCHO mainly originated from primary emission sources related to SO2. [ABSTRACT FROM AUTHOR]

In intelligent transportation, various types of sensors are used both in traffic control systems as well as in the control, safety, and entertainment systems of the vehicles themselves. In the process of educating future designers and developers of such systems, it is necessary to familiarize them with the operation and parameters of sensors. The recent years of the COVID-19 pandemic have disturbed this process due to the need to conduct classes remotely. This article presents the general concept of a laboratory stand for testing sensors of electrical and non-electrical quantities, which can be used both in stationary and remote learning. Additionally, the practical implementation of two laboratory stands for testing current and linear displacement sensors was also presented. Both stands have been tested in the remote access mode. The tests showed some shortcomings in the management software but also confirmed the correctness of the adopted concept of their implementation. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic large numbers of single-use, surgical style face masks were lost or discarded in public spaces, primarily in on public streets and car parking settings. Many of these masks were blown onto the road surfaces where they were subjected to degradation through the tire impact of passing vehicle traffic. As series of field observations as well as experimental simulations show that the three-ply polypropylene mask fabric is subjected to shear forces when compressed between the tire and the road surface. The mechanical action breaks the bonds between the fibers (both spunbonded and meltblown) leading to a continual shedding of microfibers. Wind disperses these into the environment along road sides, while surface water action moves them into stormwater drains and from there into the waterways. As the decay is rapid, municipal agencies only have a short window of time to remove stray face masks from the urban environment if micro-fiber pollution is to be reduced. [ABSTRACT FROM AUTHOR]

Through a review of previous studies, this paper analysed the epidemiological characteristics and attempts to determine the various trends of road traffic injuries (RTIs) in China before and after the coronavirus disease 2019 (COVID-19). This paper proposed effective measures and suggestions for responding to RTIs in China. Moreover, this paper aimed to provide some references for studies on RTIs in the future. According to a reference review, 50 articles related to RTIs were published and viewed in the China National Knowledge Infrastructure (CNKI), Wanfang database, Weipu (VIP) database and PubMed/MEDLINE database. Articles were selected according to the exclusion and inclusion criteria and then classified and summarized. Regarding cases, RTIs in China were highest in summer, autumn, and in rural areas and lowest in February. Men, elderly individuals and people living in rural areas were more susceptible to RTIs. In addition, thanks to effective and proactive policies and measures, the number of RTIs and casualties in China has substantially decreased, while there has been a growing number of traffic accidents along with the increase in nonmotor vehicles. However, it is worth noting that the number of RTIs obviously fell during the COVID-19 pandemic due to traffic lockdown orders and home quarantine policies. Nevertheless, accidents related to electric bicycles increased unsteadily because of the reduction in public transportation use at the same time. The factors that cause RTIs in China can be divided into four aspects: human behaviours, road conditions, vehicles and the environment. As a result, measures responding to RTIs should be accordingly proposed. Moreover, the road traffic safety situation in developing countries was more severe than that in developed countries. RTIs in China showed a downward trend attributed to road safety laws and various policies, and the downward trend was more significant during the COVID-19 pandemic owing to traffic lockdowns and home quarantine measures. It is urgent and necessary to promote road traffic safety, reduce injuries, and minimize the burden of injuries in developing countries. [ABSTRACT FROM AUTHOR]

Since the beginning of the coronavirus pandemic in 2020, the transport sector has faced new challenges connected with decreasing use of public transport and passengers' concerns about possible contagion. Using focus groups and data collection by telephone interviews during the different phases of the pandemic, we investigated passengers' current concerns connected with public transport and what measures would help alleviate their fear of using it again. Our findings show that the pandemic has amplified passengers' sensitivity to phenomena they perceived negatively already before the pandemic, such as overcrowded vehicles, odours, or inadequate cleaning of vehicles. An appeal to people's own responsibility, appropriate communication by key institutions, increasing sanitation standards and promotion of contactless services are crucial for a safe travel feeling during and after the pandemic. The technological solutions, such as cashless payments, real-timeinformation for adequate guidance of users, more sophisticated ventilation systems etc. gained even more significance during the COVID-19 pandemic. In spite of various measures taken in the PT system, users reduced their PT trips substantially. The fear of COVID-19 contagion has been one of the reasons, although the fear of PT use has not been greater than the fear of contagion in other situations, such as shopping. One of the reasons for passengers´ decline was also the PT service reduction in frequency or number of connections. On the other hand, PT operators have been exposed to an enormous pressure to ensure sanitary requirements and had to overcome economic shortages due to a decreased demand and increased costs, so they had to find a viable balance between a necessary supply and safe operation during the COVID-19 waves. The study brings an overview of measures and changes in PT demand and gives a complex view on the development of attitudes and experience with PT use in the Czech Republic during the different phases of the COVID-19 pandemic. Results bring recommendations to PT providers, transport authorities and other institutions dealing with mobility and public health. Implementation of such measures can minimize the risk of contagion by COVID-19 or other respiratory infections and will help further development of public transport as a sustainable transport mode in the post-pandemic era. [ABSTRACT FROM AUTHOR]

Monitoring road traffic is extremely important given the possibilities it opens up in terms of studying the behavior of road users, road design and planning problems, as well as because it can be used to predict future traffic. Especially on highways that connect beaches and larger urban areas, traffic is characterized by having peaks that are highly dependent on weather conditions and rest periods. This paper describes a dataset of mobility patterns of a coastal area in Aveiro region, Portugal, fully covered with traffic classification radars, over a two-year period. The sensing infrastructure was deployed in the scope of the PASMO project, an open living lab for co-operative intelligent transportation systems. The data gathered includes the speed of the detected objects, their position, and their type (heavy vehicle, light vehicle, two-wheeler, and pedestrian). The dataset includes 74,305 records, corresponding to the aggregation of road information at 10 min intervals. A brief analysis of the dataset shows the highly dynamic nature of traffic during the two-year period. In addition, the existence of meteorological records from nearby stations, and the recording of daily data on COVID-19 infections, make it possible to cross-reference information and study the influence of weather conditions and infections on traffic behavior. [ABSTRACT FROM AUTHOR]

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• Overall PM 2.5 pollution in Guangzhou improved markedly during the COVID-19 lockdown. • O 3 was the only air pollutant that demonstrated increased levels during COVID-19. • The trend of PM 2.5 pollution wasn't consistent with traffic and industrial emissions. • Transportation and secondary pollution offset the reduction of primary PM 2.5 emission. • Industrial PM 2.5 from western and southeastern Guangzhou was the key source of PEs. The COVID-19 pandemic has raised awareness about various environmental issues, including PM 2.5 pollution. Here, PM 2.5 pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM 2.5 in Guangzhou, with an emphasis on heavy pollution. The lockdown led to large reductions in industrial and traffic emissions, which significantly reduced PM 2.5 concentrations in Guangzhou. Interestingly, the trend of PM 2.5 concentrations was not consistent with traffic and industrial emissions, as minimum concentrations were observed in the fourth period (3/01-3/31, 22.45 μg/m3) of the lockdown. However, the concentrations of other gaseous pollutants, e.g., SO 2 , NO 2 and CO, were correlated with industrial and traffic emissions, and the lowest values were noticed in the second period (1/24-2/03) of the lockdown. Meteorological correlation analysis revealed that the decreased PM 2.5 concentrations during COVID-19 can be mainly attributed to decreased industrial and traffic emissions rather than meteorological conditions. When meteorological factors were included in the PM 2.5 composition and backward trajectory analyses, we found that long-distance transportation and secondary pollution offset the reduction of primary emissions in the second and third stages of the pandemic. Notably, industrial PM 2.5 emissions from western, southern and southeastern Guangzhou play an important role in the formation of heavy pollution events. Our results not only verify the importance of controlling traffic and industrial emissions, but also provide targets for further improvements in PM 2.5 pollution. [Display omitted] [ABSTRACT FROM AUTHOR]

India is a fast Developing Country in the World. During Construction or development of Road Projects occurs a Accidents for Labours, Traffic Vehicles in sometime Environmental problems are created due to Unscientific or Unsafe Highway Construction Management Technique's. In the Highway Construction involves Physical, Chemical, Electrical, and Machineries Hazardous to the labours or Workers in Road Construction Site. And also includes Risky Operations and Occupational Unhealthy Operation, Unskilled labours Causes Deaths, Minor or Major Health issues, Accidents, delay of work, Cost affect to Contractors, losses of Construction Company Reputation. For the most important the Ergonomic injuries due to the High or Low illumination of light, High levels of Sound (db) Toxic Substances are causes the Accidents are occurred from the Ergonomic factors, Such as Exertion, Physical Contact with Pressure, Exposure to vibrating Machineries, Expose the body to Extreme Heat or Cold Environment have create major problems on Work and Safety of the Road Construction. Mainly the workers or Labors Suffering from the Muscular Skeletal Disorders, Strain & Stress Due to the hard work, Collision with Equipment, Vehicle related Accidents. Mainly the Labours and workers behavior Plays a very important role in the Road or Highway Construction Site. The Occupational Safety and Health Act (1970) defines Protect the Employers, have a legal obligation provide with a Safe Environment with Safety Precautionary Measurements in Highway Construction. The main agenda of this Paper is to Educate and Awareness for the labors, how and why to use of Personal Protective Equipment (PPE) at Highway Construction Site, Safety Regulations, Traffic Control Systems, Safety Culture adopted in Highway Construction, Identifying the Hazard Materials, First Aid Treatment, Causes of Accidents and Hazards, Environmental Awareness and Health Awareness Programs, Covid-19 Pandemic's etc. And Mainly the Paper Concluded that Create a Awareness among Highway Construction Workers and Educate to Adopt the Various Safety Related Equipments, Measurements, and Protection in Highway Construction Site. [ABSTRACT FROM AUTHOR]

• The study explores how explore how crash patterns have changed after the pandemic outbreak. • Factors to changes in the percentages of crashes by type and numbers of crashes by type were analyzed. • Total crashes, peak-hour crashes decreased by 14% and 22% after the outbreak, respectively. • Fatal crashes slightly increased but not with statistical significance. In the twentieth year of the twenty-first century, humanity is facing an unprecedented global crisis owing to the COVID-19 pandemic. It has brought about drastic changes in the way we live and work, as well as the way we move from one place to another, namely transportation. Previous studies have preliminarily found that mobility, travel behavior, and road traffic safety status experienced great changes after the outbreak of the COVID-19. The objective of this study is to explore how crash patterns have changed, as well as the contributing factors of such changes and the heterogeneity between counties in Florida. Thus, data of COVID-19 cases, crash, socioeconomic factors, and traffic volume of 2019 and 2020 are collected. Preliminary analyses show a considerable reduction from March to June. Substantial changes are shown in the proportions of crashes by time of occurrence and injury severity. Two types of statistical models are developed to identify factors of (1) changes in the percentages of crashes by type and (2) the numbers of crashes by type. The developed models reveal various demographic, socioeconomic, and travel factors. After controlling other factors, the total numbers of crashes are 14% lower after the outbreak. The most significant reductions are observed in peak-hour (22%), while no significant change is found in fatal crashes. The results show that the number of crashes has significantly decreased even after controlling the traffic volume, but some crash types (e.g., fatal) did not show a significant reduction. The findings are expected to provide some insights into better transportation planning and management to ensure traffic safety in a possible future epidemic. [ABSTRACT FROM AUTHOR]

With the spatial structure of urban agglomerations, well-developed transportation networks and close economic ties can increase the risk of intercity transmission of infectious diseases. To reveal the epidemic transmission mechanism in urban agglomerations and to explore the effectiveness of traffic control measures, this study proposes an Urban-Agglomeration-based Epidemic and Mobility Model (UAEMM) based on the reality of urban transportation networks and population mobility factors. Since the model considers the urban population inflow, along with the active intracity population, it can be used to estimate the composition of urban cases. The model was applied to the Chang-Zhu-Tan urban agglomeration, and the results show that the model can better simulate the transmission process of the urban agglomeration for a certain scale of epidemic. The number of cases within the urban agglomeration is higher than the number of cases imported into the urban agglomeration from external cities. The composition of cases in the core cities of the urban agglomeration changes with the adjustment of prevention and control measures. In contrast, the number of cases imported into the secondary cities is consistently greater than the number of cases transmitted within the cities. A traffic control measures discount factor is introduced to simulate the development of the epidemic in the urban agglomeration under the traffic control measures of the first-level response to major public health emergency, traffic blockades in infected areas, and public transportation shutdowns. If none of those traffic control measures had been taken after the outbreak of COVID-19, the number of cases in the urban agglomeration would theoretically have increased to 3879, which is 11.61 times the actual number of cases that occurred. If only one traffic control measure had been used alone, each of the three measures would have reduced the number of cases in the urban agglomeration to 30.19 %–57.44 % of the theoretical values of infection cases, with the best blocking effect coming from the first-level response to major public health emergency. Traffic control measures have a significant effect in interrupting the spread of COVID-19 in urban agglomerations. The methodology and main findings presented in this paper are of general interest and can also be used in studies in other countries for similar purposes to help understand the spread of COVID-19 in urban agglomerations. • This study proposes an Urban-Agglomeration-based Epidemic and Mobility Model (UAEMM) based on the reality of urban transportation networks and population mobility factors. • We analyze case composition in cities and urban agglomerations, and to evaluate the effectiveness of traffic control measures taken. • The composition of cases in the core cities of the urban agglomeration changes with the adjustment of prevention and control measures. • The best blocking effect coming from the first-level response to major public health emergency. [ABSTRACT FROM AUTHOR]

This paper investigates the imppact of COVID-19 travel restrictions on population flow in the People's Republic of China. We discover an "unreasonable" surge in population flow after the Wuhan travel ban. We further find out that such a sure of population flow is attributed to the "spill-over" effect of the Wuhan travel ban. We utilize a logistic regression model to quantify that the spill-over effect linearly decays with the travel distance to the Pandemic center city. Because of the "spill-over" effect of the travel ban policy, government authorities should design redundancy polity to simultaneously implement a travel ban for the pandemic center city and its neighboring cities to restrain human movement and pandemic transmission. • We discovered the "spill-over" effect of the Wuhan travel ban. • A travel ban policy may stimulate human movement if it's not properly designed • The transportation distance to the COVID-19 pandemic center city negatively linearly determines the "spill-over" effect. • The "spill-over" effects can help city administrators to predicate population flow and make traffic control plans when pandemic outbreaks. [ABSTRACT FROM AUTHOR]