Territorial differences in the spread of COVID-19 in European regions and US counties.

This article explores the territorial differences in the onset and spread of COVID-19 and the excess mortality associated with the pandemic, with a focus on European regions and US counties. Both in Europe and in the US, the pandemic arrived earlier and recorded higher Rt values in urban regions than in intermediate and rural ones. A similar gap is also found in the data on excess mortality. In the weeks during the first phase of the pandemic, urban regions in EU countries experienced excess mortality of up to 68 pp more than rural ones. We show that, during the initial days of the pandemic, territorial differences in Rt by the degree of urbanisation can be largely explained by the level of internal, inbound and outbound mobility. The differences in the spread of COVID-19 by rural-urban typology and the role of mobility are less clear during the second wave. This could be linked to the fact that the infection is widespread across territories, to changes in mobility patterns during the summer period as well as to the different containment measures which reverse the link between mobility and Rt.

Demographic and territorial characteristics of COVID-19 cases and excess mortality in the European Union during the first wave.

This article explores for a large number of countries in the European Union (plus the United Kingdom) the main demographic differentials in positive tested COVID-19 cases and excess mortality during the first wave in 2020, accounting for differences at territorial level, where population density and size play a main role in the diffusion and effects of the disease in terms of morbidity and mortality. This knowledge complements and refines the epidemiological information about the spread and impact of the virus. For this analysis, we rely on the descriptive exploration of (1) data from The European Surveillance System (TESSy) database developed at the European Centre for Disease Prevention and Control (ECDC) on the number of cases and fatality rates and (2) of weekly mortality data collected by Eurostat. The analysis at territorial level studies the changes in R0-the basic reproduction number-and median excess mortality, across territories with different levels of urbanization. The unique findings of this study encompassing most European Union Member States confirm and define the demographic and territorial differential impacts in terms of infections and fatalities during the first wave of the pandemic in 2020. The information is important for stakeholders at European Union, national and sub-national levels in charge of designing containment measures for COVID-19 and adaptation policies for the future by anticipating the rebound for certain segments of the population with differential medical and economic needs.

Explaining the travelling behaviour of migrants using Facebook audience estimates.

The paper explores the travelling behaviour of migrant groups using Facebook audience estimates. Reduced geographical mobility is associated with increased risk of social exclusion and reduced socio-economic and psychological well-being. Facebook audience estimates are timely, openly available and cover most of the countries in the world. Facebook classifies its users based on multiple attributes such as the country of their previous residence, and whether they are frequent travellers. Using these data, we modelled the travelling behaviour of Facebook users grouped by countries of previous and current residence, gender and age. We found strong indications that the frequency of travelling is lower for Facebook users migrating from low-income countries and for women migrating from or living in countries with high gender inequality. Such mobility inequalities impede the smooth integration of migrants from low-income countries to new destinations and their well-being. Moreover, the reduced mobility of women who have lived or currently live in countries with conservative gender norms capture another aspect of the integration which is referring to socio-cultural norms and gender inequality. However, to provide more solid evidence on whether our findings are also valid for the general population, collaboration with Facebook is required to better understand how the data is being produced and pre-processed.

Where did the vessels go? An analysis of the EU fishing fleet gravitation between home ports, fishing grounds, landing ports and markets.

The mobile nature of fishing activity entails dynamic spatial relations and dependencies between coastal communities and fishing grounds drawn by the movement of fishing vessels. Analysing these spatial relations is essential to allocate the socio-economic impact of the fishing activity into the relevant coastal communities. In addition, such spatial information gives the possibility, on the one hand, to assess the impacts from fisheries on the marine environment and, on the other, to manage competing uses of the sea space between different activities. In this paper, we use AIS data, which is individual vessels' positioning data, to examine the activity of the EU large-scale fishing fleets, their home ports, high intensity fishing areas (i.e., main fishing grounds), main ports and coastal communities involved.

Estimating and projecting air passenger traffic during the COVID-19 coronavirus outbreak and its socio-economic impact.

Due to the coronavirus global crisis, most countries have put in place restrictive measures in order to confine the pandemia and contain the number of casualties. Among the restrictive measures, air traffic suspension is certainly quite effective in reducing the mobility on the global scale in the short term but it also has high socio-economic impact on the long and short term. The main focus of this study is to collect and prepare data on air passengers traffic worldwide with the scope of analyze the impact of travel ban on the aviation sector. Based on historical data from January 2010 till October 2019, a forecasting model is implemented in order to set a reference baseline. Making use of airplane movements extracted from online flight tracking platforms and on-line booking systems, this study presents also a first assessment of recent changes in flight activity around the world as a result of the COVID-19 pandemic. To study the effects of air travel ban on aviation and in turn its socio-economic, several scenarios are constructed based on past pandemic crisis and the observed flight volumes. It turns out that, according to these hypothetical scenarios, in the first Quarter of 2020 the impact of aviation losses could have negatively reduced World GDP by 0.02% to 0.12% according to the observed data and, in the worst case scenarios, at the end of 2020 the loss could be as high as 1.41-1.67% and job losses may reach the value of 25-30 millions. Focusing on EU27, the GDP loss may amount to 1.66-1.98% by the end of 2020 and the number of job losses from 4.2 to 5 millions in the worst case scenarios. Some countries will be more affected than others in the short run and most European airlines companies will suffer from the travel ban. We hope that these preliminary results may be of help for informed policy making design of exit strategies from this global crisis.

Quantifying international human mobility patterns using Facebook Network data.

Quantifying global international mobility patterns can improve migration governance. Despite decades of calls by the international community to improve international migration statistics, the availability of timely and disaggregated data about long-term and short-term migration at the global level is still very limited. In this study, we investigate the feasibility of using non-traditional data sources to fill existing gaps in migration statistics. To this end, we use anonymised and publicly available data provided by Facebook's advertising platform. Facebook's advertising platform classifies its users as "lived in country X" if they previously lived in country X, and now live in a different country. Drawing on statistics about Facebook Network users (Facebook, Instagram, Messenger, and the Audience Network) who have lived abroad and applying a sample bias correction method, we estimate the number of Facebook Network (FN) "migrants" in 119 countries of residence and in two time periods by age, gender, and country of previous residence. The correction method estimates the probability of a person being a FN user based on age, sex, and country of current and previous residence. We further estimate the correlation between FN-derived migration estimates and reference official migration statistics. By comparing FN-derived migration estimates in two different time periods, January-February and August-September 2018, we successfully capture the increase in Venezuelan migrants in Colombia and Spain in 2018. FN-derived migration estimates cannot replace official migration statistics, as they are not representative, and the exact methods the FN uses for classifying its users are not known, and might change over time. However, after carefully assessing the validity of the FN-derived estimates by comparing them with data from reliable sources, we conclude that these estimates can be used for trend analysis and early-warning purposes.

Global seafood consumption footprint.

To ensure food security and nutritional quality for a growing world population in the face of climate change, stagnant capture fisheries production, increasing aquaculture production and competition for natural resources, countries must be accountable for what they consume rather than what they produce. To investigate the sustainability of seafood consumption, we propose a methodology to examine the impact of seafood supply chains across national boundaries: the seafood consumption footprint. The seafood consumption footprint is expressed as the biomass of domestic and imported seafood production required to satisfy national seafood consumption, and is estimated using a multi-regional input output model. Thus, we reconstruct for the first time the global fish biomass flows in national supply chains to estimate consumption footprints at the global, country and sector levels (capture fisheries, aquaculture, distribution and processing, and reduction into fishmeal and fish oil) taking into account the biomass supply from beyond national borders.

Mapping Fishing Effort through AIS Data.

Several research initiatives have been undertaken to map fishing effort at high spatial resolution using the Vessel Monitoring System (VMS). An alternative to the VMS is represented by the Automatic Identification System (AIS), which in the EU became compulsory in May 2014 for all fishing vessels of length above 15 meters. The aim of this paper is to assess the uptake of the AIS in the EU fishing fleet and the feasibility of producing a map of fishing effort with high spatial and temporal resolution at European scale. After analysing a large AIS dataset for the period January-August 2014 and covering most of the EU waters, we show that AIS was adopted by around 75% of EU fishing vessels above 15 meters of length. Using the Swedish fleet as a case study, we developed a method to identify fishing activity based on the analysis of individual vessels' speed profiles and produce a high resolution map of fishing effort based on AIS data. The method was validated using detailed logbook data and proved to be sufficiently accurate and computationally efficient to identify fishing grounds and effort in the case of trawlers, which represent the largest portion of the EU fishing fleet above 15 meters of length. Issues still to be addressed before extending the exercise to the entire EU fleet are the assessment of coverage levels of the AIS data for all EU waters and the identification of fishing activity in the case of vessels other than trawlers.

Systems for prevention and control of epidemic emergencies.

The development of early warning systems is fundamental for preventing the spread of infectious diseases. Data collection, however, is a costly activity and it is not possible to implement early warning systems everywhere and for all possible events. Hence, tools helping to improve the focus of surveillance efforts are of paramount importance. Risk assessment methods and other provisional modelling techniques may permit to estimate the probability of introduction and spread of infectious diseases in different geographical areas. Similarly, efficient information systems must be in place to assist the veterinary services in case of epidemic emergencies in order to support the prompt application of control measures for the containment of the infection and the reduction of the magnitude of negative consequences. This review describes two recent approaches to the estimation of the probability of introduction and spread of infectious diseases based on the use of risk maps/ spatial modelling and Social Network Analysis (SNA) techniques. The review also describes a web application developed in Italy to help official veterinary services to trace animals in case of outbreaks of infectious diseases.

Transport temperatures observed during the commercial transportation of animals.

Current temperature standards and those proposed by the European Food Safety Authority (EFSA) were compared with the actual practices of commercial transport in the European Union. Temperature and humidity records recorded for a year on 21 vehicles over 905 journeys were analysed. Differences in temperature and humidity recorded by sensors at four different positions in the vehicles exceeded 10°C between the highest and lowest temperatures in nearly 7% of cases. The number and position of temperature sensors are important to ensure the correct representation of temperature conditions in the different parts of a vehicle. For all journeys and all animal categories, a relatively high percentage of beyond threshold temperatures can be observed in relation to the temperature limits of 30°C and 5°C. Most recorded temperature values lie within the accepted tolerance of ±5°C stipulated in European Community Regulation (EC) 1/2005. The temperature thresholds proposed by EFSA would result in a higher percentage of non-compliant conditions which are more pronounced at the lower threshold, compared to the thresholds laid down in Regulation (EC) 1/2005. With respect to the different animal categories, the non-compliant temperature occurrences were more frequent in pigs and sheep, in particular with regard to the thresholds proposed by EFSA.

Dynamical patterns of cattle trade movements.

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions.

Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks.

A new method for the calculation of a centrality measure (Disease Flow Centrality, DFC), which takes into account temporal dynamics of livestock movement networks, is proposed. The method is based on a network traversal algorithm which represents an epidemic process more realistically compared with traditional graph traversal algorithms used in the calculation of centrality measures on static networks. The new approach was tested on networks generated from all the registered movements of cattle in Italy in the years 2007, 2008 and 2009 and the results were compared to those obtained by classical centrality measures. The results show that DFC values often differ substantially from those of other centrality measures and that these DFC values tend to be more unstable in time. The DFC offers several advantages for assessing risk and vulnerability of specific holdings and of an entire network, using recent movement data from national livestock databases. Some examples also indicate how the basic approach in the DFC calculation could be expanded into a more complex epidemic model by incorporating weights and how it could be combined with a geo-spatial perspective.

Network analysis of Italian cattle trade patterns and evaluation of risks for potential disease spread.

Livestock movement data represent a valuable source of information to understand the pattern of contacts between premises which may determine the spread of diseases. Social network analysis techniques have been used to analyse the movement patterns of cattle in Italy in 2007. A description of the structure of the Italian cattle industry is presented and the main trade flows and the relations between premises in relation to the potential spread of cattle diseases are investigated. Epidemic simulations have been carried out on the network build out of movement data using a network-based meta-population model. The simulations show the influence of the network structure on the dynamics and size of a hypothetic epidemic and give useful indications on the effects of targeted removal of nodes based on the centrality of premises within the network of animal movements.

Animal welfare monitoring and livestock traceability during transport.

The authors present an experimental project that aims to establish an effective navigation system in accordance with European Council Regulation 1/2005 concerning animal welfare during transport. The prototype created during the project consists of both hardware and software components. An onboard unit is installed at truck level. It collects and transmits real-time information of the animal transport to a remote receiver database. A Web/geographic information system (GIS) application is used to analyse and monitor the information received. The architecture of the hardware and software of the project is presented, focusing on the features of the Web-GIS application.