arXiv subjects

Francesco Sermi

Publications and source records attributed to Francesco Sermi.

10 recordsLinked to original sources

arXiv2022

Migration patterns, friendship networks, and the diaspora: the potential of Facebook Social Connectedness Index to anticipate displacement patterns induced by Russia invasion of Ukraine in the European Union

The conflict in Ukraine is causing large-scale displacement in Europe and in the World. Based on the United Nations High Commissioner for Refugees (UNHCR) estimates, more than 7 million people fled the country as of 5 September 2022. In this context, it is extremely important to anticipate where these people are moving so that national to local authorities can better manage challenges related to their reception and integration. This work shows how innovative data from social media can provide useful insights on conflict-induced migration flows. In particular, we explore the potential of Facebook's Social Connectedness Index (SCI) for predicting migration flows in the context of the war in Ukraine, building on previous research findings that the presence of a diaspora network is one of the major migration drivers. To do so, we first evaluate the relationship between the Ukrainian diaspora and the number of refugees from Ukraine registered for Temporary Protection or similar national schemes as a proxy of migratory flows into the EU. We find a very strong correlation between the two (Pearson's r=0.94, p<0.0001), which indicates that the diaspora is attracting the people fleeing the war, who tend to reach their compatriots, in particular in the countries where the Ukrainian immigration was more a recent phenomenon. Second, we compare Facebook's SCI with available official data on diaspora at regional level in Europe. Our results suggest that the index, along with other readily available covariates, is a strong predictor of the Ukrainian diaspora at regional scale. Finally, we discuss the potential of Facebook's SCI to provide timely and spatially detailed information on human diaspora for those countries where this information might be missing or outdated, and to complement official statistics for fast policy response during conflicts.

physics.soc-ph↗

arXiv2022

Data Innovation in Demography, Migration and Human Mobility

With the consolidation of the culture of evidence-based policymaking, the availability of data has become central to policymakers. Nowadays, innovative data sources offer an opportunity to describe demographic, mobility, and migratory phenomena more accurately by making available large volumes of real-time and spatially detailed data. At the same time, however, data innovation has led to new challenges (ethics, privacy, data governance models, data quality) for citizens, statistical offices, policymakers and the private sector. Focusing on the fields of demography, mobility, and migration studies, the aim of this report is to assess the current state of data innovation in the scientific literature as well as to identify areas in which data innovation has the most concrete potential for policymaking. Consequently, this study has reviewed more than 300 articles and scientific reports, as well as numerous tools, that employed non-traditional data sources to measure vital population events (mortality, fertility), migration and human mobility, and the population change and population distribution. The specific findings of our report form the basis of a discussion on a) how innovative data is used compared to traditional data sources; b) domains in which innovative data have the greatest potential to contribute to policymaking; c) the prospects of innovative data transition towards systematically contributing to official statistics and policymaking.

cs.CY↗

arXiv2022

The potential of Facebook advertising data for understanding flows of people from Ukraine to the European Union

This work contributes to the discussion on how innovative data can support a fast crisis response. We use operational data from Facebook to gain useful insights on where people fleeing Ukraine following the Russian invasion are likely to be displaced, focusing on the European Union. In this context, it is extremely important to anticipate where these people are moving so that local and national authorities can better manage challenges related to their reception and integration. By means of the Ukrainian-speaking Monthly Active Users estimates provided by Facebook advertising platform, we analyse the flows of people fleeing the country towards the European Union. At the fifth week since the beginning of the war, our results indicate an increase in the number of Ukrainian-speaking Facebook users in all the EU countries, with Poland registering the highest percentage share ($33\%$) of the overall increase, followed by Germany ($17\%$), and Czechia ($15\%$). We assess the reliability of prewar Facebook estimates by comparison with official statistics on the Ukrainian diaspora, finding a strong correlation between the two data sources (Pearson's $r=0.93$, $p<0.0001$). We then compare our results with data on arrivals in Poland and Hungary reported by the UNHCR, and we observe a similarity in their trend. In conclusion, we show how Facebook advertising data could offer timely insights on international mobility during crisis, supporting initiatives aimed at providing humanitarian assistance to the displaced people, as well as local and national authorities to better manage their reception and integration.

stat.AP↗

arXiv2021

Monitoring COVID-19-induced gender differences in teleworking rates using Mobile Network Data

The COVID-19 pandemic has created a sudden need for a wider uptake of home-based telework as means of sustaining the production. Generally, teleworking arrangements impacts directly worker's efficiency and motivation. The direction of this impact, however, depends on the balance between positive effects of teleworking (e.g. increased flexibility and autonomy) and its downsides (e.g. blurring boundaries between private and work life). Moreover, these effects of teleworking can be amplified in case of vulnerable groups of workers, such as women. The first step in understanding the implications of teleworking on women is to have timely information on the extent of teleworking by age and gender. In the absence of timely official statistics, in this paper we propose a method for nowcasting the teleworking trends by age and gender for 20 Italian regions using mobile network operators (MNO) data. The method is developed and validated using MNO data together with the Italian quarterly Labour Force Survey. Our results confirm that the MNO data have the potential to be used as a tool for monitoring gender and age differences in teleworking patterns. This tool becomes even more important today as it could support the adequate gender mainstreaming in the ``Next Generation EU'' recovery plan and help to manage related social impacts of COVID-19 through policymaking.

cs.SI↗

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↗

arXiv2021

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, across the European NUTS3 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 68pp 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 causality between mobility and Rt.

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↗