Evidence map›Paper›PMID 34956834›Full record

ArticleCase studies on transport policy2022

Regional mobility during the Covid-19 pandemic: Analysis of trends and repercussions using mobile phones data across the EU.

Panayotis Christidis, Biagio Ciuffo, Michele Vespe

Abstract read
In one paragraph

Article in Case studies on transport policy, 2022. 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

3 authors.

Panayotis ChristidisEuropean Commission, Joint Research Centre, Seville, Spain.
Biagio CiuffoEuropean Commission, Joint Research Centre, Ispra, Italy.
Michele VespeEuropean Commission, Joint Research Centre, Ispra, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The analysis of mobile phones data at regional level in the EU reveals varying patterns in mobility trends during the Covid-19 pandemic. These depend on the temporal evolution of the pandemic in each EU Member State, the measures taken at local or national level to limit the growth of the pandemic, as well as the level of urbanization and type of economic activity in each region. During the first phase of the pandemic (March- April 2020) the decrease in mobility was in general uniform among regions in the same Member State, especially in Italy, Spain and France, where national level measures were adopted. A relaxation of the measures and a resulting rebound of mobility was evident during the summer period (July- August 2020). At the same time, a shift from urban to rural areas during the summer vacation period is evident, with especially touristic areas increasing the number of movements in the same Member State. The variance in mobility trends during the second wave of the pandemic (October- November 2020) was higher, a result of the predominantly local and regional level measures applied in each Member State. Those insights suggest a certain correlation between the level of mobility and the evolution of the pandemic at regional level. The association with high levels of Covid-19 prevalence is particularly strong in urban regions with high mobility levels.

Indexed as

Covid-19European UnionMobile phonesMobilityNon-pharmaceutical interventionsPandemicRegionsTeleworkTransport

Identifiers

PMID34956834
PMCPMC8685257

What OpenQuestion holds

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Registered trials

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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.