Evidence map›Paper›PMID 35425884›Full record

ArticleJapanese journal of statistics and data science2021

Anomaly detection of mobile positioning data with applications to COVID-19 situational awareness.

Stefano Maria Iacus, Francesco Sermi, Spyridon Spyratos, Dario Tarchi, Michele Vespe

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Japanese journal of statistics and data science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stefano Maria IacusEuropean Commission, Joint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.ORCID 0000-0002-4884-0047
Francesco SermiEuropean Commission, Joint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Spyridon SpyratosEuropean Commission, Joint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Dario TarchiEuropean Commission, Joint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Michele VespeEuropean Commission, Joint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Anomaly detectionData scienceHigh-dimensional time series analysisMobile network operator data

Identifiers

PMID35425884
PMCPMC7934126

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.