arXiv subjects

Michele Vespe

Publications and source records attributed to Michele Vespe.

9 recordsLinked to original sources

arXiv2022

Challenges and Opportunities of Computational Social Science for Official Statistics

The vast amount of data produced everyday (so-called 'digital traces') and available nowadays represent a gold mine for the social sciences, especially in a computational context, that allows to fully extract their informational and knowledge value. In the latest years, statistical offices have made efforts to profit from harnessing the potential offered by these new sources of data, with promising results. But how difficult is this integration process? What are the challenges that statistical offices would likely face to profit from new data sources and analytical methods? This chapter will start by setting the scene of the current official statistics system, with a focus on its fundamental principles and dimensions relevant to the use of non-traditional data. It will then present some experiments and proofs of concept in the context of data innovation for official statistics, followed by a discussion on prospective challenges related to sustainable data access, new technical and methodological approaches and effective use of new sources of data.

stat.ME↗

arXiv2021

Mobility Functional Areas and COVID-19 Spread

This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. The MFAs do not coincide necessarily with administrative borders as they are built observing natural human mobility and, therefore, they can be used to inform, in a bottom-up approach, local transportation, spatial planning, health and economic policies. After presenting the methodology behind the MFAs, this study focuses on the link between the COVID-19 pandemic and the MFAs in Austria. It emerges that the MFAs registered an average number of infections statistically larger than the areas in the rest of the country, suggesting the usefulness of the MFAs in the context of targeted re-escalation policy responses to this health crisis. The MFAs dataset is openly available to other scholars for further analyses.

stat.AP↗

arXiv2021

On the Use of Data from Multiple Mobile Network Operators in Europe to fight COVID-19

The rapid spread of COVID-19 infections on a global level has highlighted the need for accurate, transparent and timely information regarding collective mobility patterns to inform de-escalation strategies as well as to provide forecasting capacity for re-escalation policies aiming at addressing further waves of the virus. Such information can be extracted using aggregate anonymised data from innovative sources such as mobile positioning data. This paper presents lessons learnt and results of a unique Business-to-Government (B2G) initiative between several Mobile Network Operators in Europe and the European Commission. Mobile positioning data have supported policy makers and practitioners with evidence and data-driven knowledge to understand and predict the spread of the disease, the effectiveness of the containment measures, their socio-economic impacts while feeding scenarios at EU scale and in a comparable way across countries. The challenges of this data sharing initiative are not limited to data quality, harmonisation, and comparability across countries, however important they are. Equally essential aspects that need to be addressed from the onset are related to data privacy, security, fundamental rights and commercial sensitivity.

stat.AP↗

arXiv2021

Mobility and Economic Impact of COVID-19 Restrictions in Italy using Mobile Network Operator Data

This work presents the analysis of the impact of restrictions on mobility in Italy, with a focus on the period from 6 November 2020 to 31 January 2021, when a three-tier system based on different levels of risk was adopted and applied at regional level to contrast the second wave of COVID-19. The impact is first evaluated on mobility using Mobile Network Operator anonymised and aggregate data shared in the framework of a Business-to-Government initiative with the European Commission. Mobility data, alongside additional information about electricity consuption, are then used to assess the impacts on an economic level of the three-tier system in different areas of the country.

econ.GN↗

arXiv2020

Anomaly Detection of Mobility Data with Applications to COVID-19 Situational Awareness

This work introduces a live anomaly detection system for high frequency and high-dimensional data collected at regional scale such as Origin Destination Matrices of mobile positioning data. To take into account different granularity in time and space of the data coming from different sources, the system is designed to be simple, yet robust to the data diversity, with the aim of detecting abrupt increase of mobility towards specific regions as well as sudden drops of movements. The methodology is designed to help policymakers or practitioners, and makes it possible to visualise anomalies as well as estimate the effect of COVID-19 related containment or lifting measures in terms of their impact on human mobility as well as spot potential new outbreaks related to large gatherings.

stat.AP↗

arXiv2020

Human mobility and COVID-19 initial dynamics

Mobility data at EU scale can help understand the dynamics of the pandemic and possibly limit the impact of future waves. Still, since a reliable and consistent method to measure the evolution of contagion at international level is missing, a systematic analysis of the relationship between human mobility and virus spread has never been conducted. A notable exceptions are France and Italy, for which data on excess deaths, an indirect indicator which is generally considered to be less affected by national and regional assumptions, are available at department and municipality level, respectively. Using this information together with anonymised and aggregated mobile data, this study shows that mobility alone can explain up to 92% of the initial spread in these two EU countries, while it has a slow decay effect after lockdown measures, meaning that mobility restrictions seem to have effectively contribute to save lives. It also emerges that internal mobility is more important than mobility across provinces and that the typical lagged positive effect of reduced human mobility on reducing excess deaths is around 14-20 days. An analogous analysis relative to Spain, for which an IgG SARS-Cov-2 antibody screening study at province level is used instead of excess deaths statistics, confirms the findings. The same approach adopted in this study can be easily extended to other European countries, as soon as reliable data on the spreading of the virus at a suitable level of granularity will be available. Looking at past data, relative to the initial phase of the outbreak in EU Member States, this study shows in which extent the spreading of the virus and human mobility are connected.

stat.AP↗

arXiv2020

Estimating and Projecting Air Passenger Traffic during the COVID-19 Coronavirus Outbreak and its Socio-Economic Impact

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 this 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.

stat.AP↗

arXiv2020

Flight restrictions from China during the COVID-2019 Coronavirus outbreak

This short note provides estimates of the number of passengers that travel from China to all world airports in the period October 2019 - March 2020 on the basis of historical data. From this baseline we subtract the expected reduction in the number of passengers taking into account the temporary ban of some routes which was put in place since 23 January 2020 following the COVID-2019 Coronavirus outbreak. The results indicate a reduction of the number of passengers in the period January - March 2020 of -2.5%. This calculation considers only the complete closure of routes (not just direct flights) and not the reduction in the number of passengers on still active direct and indirect connections. At the moment of writing, with such partial information it is premature to quantify economic losses on the civil air transport and tourism industry. This note is meant to provide a baseline that be extended to all countries of origin and updated as more recent data will become available.

physics.soc-ph↗

arXiv2016

Mapping EU fishing activities using ship tracking data

Information and understanding of fishing activities at sea are fundamental components of marine knowledge and maritime situational awareness. Such information is important to fisheries science, public authorities and policy makers. In this paper we introduce a first map at European scale of EU fishing activities extracted using Automatic Identification System (AIS) ship tracking data. The resulting map is a density of points that identify fishing activities. A measure of the reliability of such information is also presented as a map of coverage reception capabilities.

cs.OH↗