Modeling and understanding the impact of COVID-19 containment policies on mobile service consumption in French cities

Abstract Amid recent studies that have been exploring the wide impact that COVID-19 containment policies have had across sectors and industries, we investigate how mobility restrictions enacted in French cities during the later stages of the pandemic have affected the usage of smartphones and mobile applications. Leveraging a large-scale dataset of over 14 billion records, we unveil and quantify the substantial incidence of the different measures enforced in urban France to combat the COVID-19 epidemic on mobile service consumption. We present a simple but effective spatial linear model that can relate changes occurring at fine-grained spatial zoning in both global and per-service traffic to a limited set of socioeconomic indicators. Our model unveils some of the mechanisms that drove the significant evolution of mobile data traffic demands during the pandemic. It allows observing how the demand for mobile services has been affected by COVID-19 in very different ways across urban areas characterized by diverse population density, income levels and leisure area presence. It also discloses that usages of individual smartphone applications have been impacted in highly heterogeneous ways by the pandemic, even more so when considering the composite impacts of different transitions between periods characterized by diverse restrictions. Our results can aid governments in understanding how their measures were received across the space and different portions of population, and network operators to comprehend changes in usage due to extraordinary events, which can be used to optimize service provisioning.

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Publication Details

Journal
EPJ Data Science
Published
2024-11-07
DOI
https://doi.org/10.1140/epjds/s13688-024-00507-9
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Modeling and understanding the impact of COVID-19 containment policies on mobile service consumption in French cities

André Felipe Zanella, Zbigniew Smoreda, Marco Fiore, Stefania Rubrichi
EPJ Data Science
COVID-19 epidemiological studies
article

Modeling and understanding the impact of COVID-19 containment policies on mobile service consumption in French cities

André Felipe Zanella, Zbigniew Smoreda, Marco Fiore, Stefania Rubrichi
article en

Abstract

Abstract Amid recent studies that have been exploring the wide impact that COVID-19 containment policies have had across sectors and industries, we investigate how mobility restrictions enacted in French cities during the later stages of the pandemic have affected the usage of smartphones and mobile applications. Leveraging a large-scale dataset of over 14 billion records, we unveil and quantify the substantial incidence of the different measures enforced in urban France to combat the COVID-19 epidemic on mobile service consumption. We present a simple but effective spatial linear model that can relate changes occurring at fine-grained spatial zoning in both global and per-service traffic to a limited set of socioeconomic indicators. Our model unveils some of the mechanisms that drove the significant evolution of mobile data traffic demands during the pandemic. It allows observing how the demand for mobile services has been affected by COVID-19 in very different ways across urban areas characterized by diverse population density, income levels and leisure area presence. It also discloses that usages of individual smartphone applications have been impacted in highly heterogeneous ways by the pandemic, even more so when considering the composite impacts of different transitions between periods characterized by diverse restrictions. Our results can aid governments in understanding how their measures were received across the space and different portions of population, and network operators to comprehend changes in usage due to extraordinary events, which can be used to optimize service provisioning.

EPJ Data ScienceVol. 13(1)
Orange (France) (FR), IMDEA Networks (ES), Universidad Carlos III de Madrid (ES)
Comunidad de Madrid, European Commission, Agence Nationale de la Recherche, Horizon 2020, Agencia Estatal de Investigación
Openalex Percentile: Top 79%
COVID-19 epidemiological studies
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