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Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness
Due to an unprecedented agreement with the European Mobile Network Operators, the Joint Research Centre of the European Commission was in charge of collecting and analyze mobile positioning data to provide scientific evidence to policy makers to face the COVID-19 pandemic. This work introduces a liv...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934126/ https://www.ncbi.nlm.nih.gov/pubmed/35425884 http://dx.doi.org/10.1007/s42081-021-00109-z |
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author | Iacus, Stefano Maria Sermi, Francesco Spyratos, Spyridon Tarchi, Dario Vespe, Michele |
author_facet | Iacus, Stefano Maria Sermi, Francesco Spyratos, Spyridon Tarchi, Dario Vespe, Michele |
author_sort | Iacus, Stefano Maria |
collection | PubMed |
description | Due to an unprecedented agreement with the European Mobile Network Operators, the Joint Research Centre of the European Commission was in charge of collecting and analyze mobile positioning data to provide scientific evidence to policy makers to face the COVID-19 pandemic. This work introduces a live anomaly detection system for these high-frequency and high-dimensional data collected at European scale. To take into account the different granularity in time and space of the data, the system has been 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. A web application designed for policy makers, makes possible to visualize the anomalies and perceive the effect of containment and lifting measures in terms of their impact on human mobility as well as spot potential new outbreaks related to large gatherings. |
format | Online Article Text |
id | pubmed-7934126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-79341262021-03-05 Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness Iacus, Stefano Maria Sermi, Francesco Spyratos, Spyridon Tarchi, Dario Vespe, Michele Jpn J Stat Data Sci Original Paper Due to an unprecedented agreement with the European Mobile Network Operators, the Joint Research Centre of the European Commission was in charge of collecting and analyze mobile positioning data to provide scientific evidence to policy makers to face the COVID-19 pandemic. This work introduces a live anomaly detection system for these high-frequency and high-dimensional data collected at European scale. To take into account the different granularity in time and space of the data, the system has been 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. A web application designed for policy makers, makes possible to visualize the anomalies and perceive the effect of containment and lifting measures in terms of their impact on human mobility as well as spot potential new outbreaks related to large gatherings. Springer Singapore 2021-03-05 2021 /pmc/articles/PMC7934126/ /pubmed/35425884 http://dx.doi.org/10.1007/s42081-021-00109-z Text en © Japanese Federation of Statistical Science Associations 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Iacus, Stefano Maria Sermi, Francesco Spyratos, Spyridon Tarchi, Dario Vespe, Michele Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title | Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title_full | Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title_fullStr | Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title_full_unstemmed | Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title_short | Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness |
title_sort | anomaly detection of mobile positioning data with applications to covid-19 situational awareness |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934126/ https://www.ncbi.nlm.nih.gov/pubmed/35425884 http://dx.doi.org/10.1007/s42081-021-00109-z |
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