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.

The expectations for post-COVID recovery of transport activity point towards a gradual return to normality, once the pandemic is under control and mobility restrictions end. The shock to society and economy has, however, caused a number of behavioural changes that can influence the evolution of the transport sector. We analyse the main factors that can influence future supply and demand and explore how they may affect trip generation, distribution and modal split in passenger transport. We combine several conventional and innovative data sources with a detailed strategic transport model at the EU level, in order to present quantitative estimates under various scenarios. New remote work patterns or personal risk avoidance attitudes can lead to increased levels of car ownership and use. Public policy priorities in the aftermath of the pandemic would need to address the emerging challenges and adopt measures that can sustain the shift to active travel, support public transport, railways and aviation and stimulate innovation in transport technologies and services.

In this paper, we assess the impacts of climate change on seaports for different global warming level scenarios. The results refer to the potential risks associated with two scenarios, represented by...

Border regions are in the forefront of geographical cohesion of the European Union but often lag behind more central areas on development and connectivity. As transport infrastructure—or rather the lack of it—plays a primary role in this, specific policy measures to improve the quality of road connections and address the overall issues of geographic isolation are often necessary. The methodology presented here provides a set of indicators and tools that allow policy makers to measure accessibility and connectivity of border regions, identify areas where transport infrastructure may be lacking, and prioritize potential investments based on specific policy-relevant criteria. The approach uses very detailed spatially disaggregate data covering EU28 plus Norway and Switzerland at grid level (1 km by 1 km), as well as the complete road network. This level of resolution allows many of the specificities of the areas covered to be taken into account.

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.