Research and innovation paving the way for climate neutrality in urban transport: Analysis of 362 cities on their journey to zero emissions.

The EU Mission on Climate Neutral and Smart Cities is an ambitious initiative aiming to involve a wide range of stakeholders and deliver 100 climate-neutral and smart cities by 2030. We analysed the information submitted in the expressions of interest by 362 candidate cities. The majority of the cities' strategies for climate neutrality include urban transport as a main sector and combine the introduction of new technologies with the promotion of public transport and active mobility. We combined the information from the EU Mission candidate cities with data from the CORDIS and TRIMIS databases, and applied a clustering algorithm to measure proximity to foci of H2020 funding. Our results suggest that preparedness for the EU Mission is correlated with research and innovation activities on transport and mobility. Horizon 2020 activities specific to transport and mobility significantly increased the likelihood of a city to be a candidate. Among the various transport technology research pathways, smart mobility appears to have a major role in the development of solutions for climate neutrality.

How has COVID-19 changed private car use in European urban areas? An analysis of the effect of socio-economic characteristics and mobility habits.

The private car has been identified as the main winner among transport modes in urban areas during the COVID-19 pandemic. The fear of contagion when using public transport or the decrease in road congestion are likely to have induced changes in citizens' travel habits with respect to cars. This work investigates the impact of the pandemic on individuals' habits and preferences regarding their car ownership levels and car usage in the European urban context, with a special focus on the role played by individual socio-demographics and urban mobility patterns. For this purpose, a Path Analysis approach has been adopted to model car ownership and use before and after COVID-19. The main data source employed in this research is an EU-Wide Urban Mobility Survey that collects detailed information (individual and household socio-economic characteristics, built environment attributes and mobility habits) of 10,152 individuals from a total of 21 European urban areas of different sizes, geographical locations, and urban forms. The survey data has been complemented with city-level variables that account for differences across the cities that may explain changes in car-related behaviour. The results show that the pandemic has induced an increase in car use among socio-economic groups that are generally associated with low car-dependent behaviour, revealing that policy instruments that discourage the use of the private car in urban areas are needed to avoid reversing past trends in the reduction of urban transport emissions. High-income, well-educated teleworkers are observed to be the ones that have reduced their car use to a larger extent. On the contrary, low-income individuals are mostly maintaining similar levels of car mobility. Finally, frequent public transport users are more likely than occasional users to have substituted this mode by the private car.

Challenges for urban transport policy after the Covid-19 pandemic: Main findings from a survey in 20 European cities.

This article explores the changes in transport and mobility patterns that were triggered by the Covid-19 pandemic, as well as citizens' potential new expectations arising from this situation regarding public transport policy and urban planning. We conducted an extensive survey in 20 cities across 11 European countries during the second quarter of 2021, with a total of 10000 respondents. The information that we collected covered the change in the frequency of technology-based alternatives to travel -such as teleworking and online shopping-compared to the pre-pandemic period. It also included the change in trip frequency, purpose, mode and destination. Using the survey dataset as input, we applied a classification model that explains the change in mode choice based on the respondent characteristics and preferences. Our findings suggest that the changes in mobility patterns induced by the pandemic are the result of the combination of the degree of mobility restrictions imposed in each city, the adoption of new lifestyle and work patterns, and individual choices that depend on personal risk aversion. We identify three main challenges for urban transport policy: the increasing use of car that can reinforce long-term car dependency, the avoidance of public transport that may lead to financial and operational instability, and the uncertainty as regards the future of innovation in urban transport, especially as regards emerging technologies and business models.

Survey on urban transport in the aftermath of the COVID-19 outbreak: Data from 20 cities across Europe.

This dataset contains the full results of a survey on mobility patterns after the Covid-19 pandemic. The survey was conducted in the second trimester of 2021 and collected information from 10000 respondents across 20 urban areas. The questions covered demographic and socio-economic characteristics, employment and job related situation, the use of technological alternatives in daily activities, mobility patterns (trip frequency, purpose, destination, mode, level of comfort), and perceptions as regards the usability of each transport option. Particular emphasis was given to the comparison of current activity to that before the pandemic. The survey combined an online (Computer-Assisted Web Interviews, CAWI) approach with telephone (Computer-Assisted Telephone Interviews, CATI) interviews. The sample in each city was representative of the local demographic and socio-economic profile according to age, sex, employment situation, education and urbanization.

Regional mobility during the Covid-19 pandemic: Analysis of trends and repercussions using mobile phones data across the EU.

The analysis of mobile phones data at regional level in the EU reveals varying patterns in mobility trends during the Covid-19 pandemic. These depend on the temporal evolution of the pandemic in each EU Member State, the measures taken at local or national level to limit the growth of the pandemic, as well as the level of urbanization and type of economic activity in each region. During the first phase of the pandemic (March- April 2020) the decrease in mobility was in general uniform among regions in the same Member State, especially in Italy, Spain and France, where national level measures were adopted. A relaxation of the measures and a resulting rebound of mobility was evident during the summer period (July- August 2020). At the same time, a shift from urban to rural areas during the summer vacation period is evident, with especially touristic areas increasing the number of movements in the same Member State. The variance in mobility trends during the second wave of the pandemic (October- November 2020) was higher, a result of the predominantly local and regional level measures applied in each Member State. Those insights suggest a certain correlation between the level of mobility and the evolution of the pandemic at regional level. The association with high levels of Covid-19 prevalence is particularly strong in urban regions with high mobility levels.

The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness.

Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic.

Government support to airlines in the aftermath of the COVID-19 pandemic.

This paper assesses government support measures to the air transport sector following the outbreak of the coronavirus disease (COVID-19) pandemic from two points of view. First, it explores the factors that shape governments' willingness to support airlines. This is followed by a discussion on the various types of support that may be provided and how country-specific parameters influence the choice of measures. Second, it analyses the implications of government support in three dimensions relevant to air transport policy: competition and liberalisation, airline ownership and control, and environmental sustainability. The analysis suggests that most governments give a high priority to maintaining air transport connectivity in order to protect economic activity and jobs, in aviation itself and in related sectors such as tourism. The trade-off between ensuring connectivity and maintaining competition after the COVID-19 pandemic is a challenge with several political and economic dimensions. The re-orientation of public policy in the aftermath of the pandemic may limit the relative importance of the policy priorities that shaped the evolution of the air transport sector before the crisis, especially those related to climate change and the environment. The role of government and public authorities at all levels - especially the type and duration of measures affecting transport operations - will be crucial for the future development of the aviation industry.

A fine resolution dataset of accessibility under different traffic conditions in European cities.

Urban accessibility and congestion indicators allow us to benchmark cities. If these indicators are also available at a fine resolution, we can compare different neighbourhoods within a city. We present a dataset of different accessibility indicators for all urban areas with more than 250 thousand people in the EU27, the UK, Switzerland and Norway. Each city is analysed by means of a population grid of 500 m by 500 m and represented by a wider area covering both the densely populated urban centre and the commuting zone. To capture congestion, we measure accessibility for each grid cell at different times of the day that correspond to different traffic conditions using the detailed network and congestion information provided by TomTom.

Modeling the impact of genetic screening technologies on healthcare: theoretical model for asthma in children.

BACKGROUND AND OBJECTIVE: This study focuses on the potential impact of genetic screening technologies on healthcare. Genetic screening for asthma in children was chosen as a case study to explore the cost effectiveness of applying early genetic screening to infants, and preventive treatment to the population at risk. Early intervention could prevent progression and facilitate clinical management of the disease. From the elite group of genetic markers that have been associated with asthma-related phenotypes, ADAM33 was the first published candidate gene detected by a positional cloning approach, marking the entry of asthma research into the genomic era. The model was, therefore, initially set for an ex ante analysis of the cost effectiveness of applying the preventive program to an infant population at risk, i.e. infants presenting wheezing episodes during the first year of life, and the ADAM33 ST+7 genetic marker, with the idea of expanding to further markers and their combinations lat a later date. METHODS: In accordance with the US National Heart, Lung, and Blood Institute, four categories of asthma were considered. A Markov model was constructed, consisting of six mutually exclusive disease states (including healthy and dead states) with a simulation horizon of 100 years and a cycle length of 1 year. We define a scenario where early genetic screening was applied to infants presenting wheezing episodes during the first year of life and a preventive treatment to those children within this group who tested positive for selected ADAM33 polymorphism (ST+7). The cost-effectiveness analysis was performed from the third-party payer and patient perspective after year 6. We applied our model to a hypothetical cohort of 100 European infants. RESULTS: The number of quality-adjusted life-years (QALYs) gained during the 6 years was 1.483, and the incremental cost-effectiveness ratio per QALY gained was euro 10,100/QALY. A sensitivity analysis was carried out that varied the discount rate and cost of genetic testing, and considered two different transition matrices for the preventive program. Three main conclusions were drawn from the sensitivity analysis. Firstly, if the discount rate for both cost and health outcomes is increased by 2%, the cost effectiveness of the preventive program does not vary significantly. Discounting costs and benefits at 5%, the preventive program appears cost effective (euro 11,100/QALY). Secondly, if the cost of genetic testing is increased to euro 100, the cost effectiveness of the preventive program remains within the limits of cost effectiveness. Thirdly, the cost of genetic screening, together with transition probabilities between health states, will determine the cost effectiveness of applying a preventive program based on genetic information. CONCLUSIONS: Preventive treatment based on an early genetic screening of those children who present wheezing episodes during the first year of life, with treatment applied to those who test positive for the asthma-associated genetic marker ADAM33 ST+7, is theoretically cost effective. The model is a valuable tool for the ex ante assessment of the cost effectiveness of preventive schemes based on genetic screening. The value of modeling prior to clinical trials lies in informing study design and setting priorities for future research.