Evidence map›Paper›PMID 37500782›Full record

ArticleNature human behaviour2023

COVID-19 is linked to changes in the time-space dimension of human mobility.

Clodomir Santana, Federico Botta, Hugo Barbosa, Filippo Privitera, Ronaldo Menezes, Riccardo Di Clemente

Abstract read
In one paragraph

Article in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  6. The impact of the Social Exposome in Cardiovascular Health and Disease.Journal of precision medicine (Amsterdam, Netherlands) · 2025
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  16. Quantifying the differences inRoyal Society open science · 2021
    Article
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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

6 authors.

Clodomir SantanaComputer Science Department, University of Exeter, Exeter, UK.ORCID 0000-0001-7869-7184
Federico BottaComputer Science Department, University of Exeter, Exeter, UK.ORCID 0000-0002-5681-4535
Hugo BarbosaComputer Science Department, University of Exeter, Exeter, UK.ORCID 0000-0002-3927-969X
Filippo PriviteraSpectus, New York, NY, USA.
Ronaldo MenezesComputer Science Department, University of Exeter, Exeter, UK.ORCID 0000-0002-6479-6429
Riccardo Di ClementeComputer Science Department, University of Exeter, Exeter, UK. riccardo.diclemente@nulondon.ac.uk.ORCID 0000-0001-8005-6351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Socio-economic constructs and urban topology are crucial drivers of human mobility patterns. During the coronavirus disease 2019 pandemic, these patterns were reshaped in their components: the spatial dimension represented by the daily travelled distance, and the temporal dimension expressed as the synchronization time of commuting routines. Here, leveraging location-based data from de-identified mobile phone users, we observed that, during lockdowns restrictions, the decrease of spatial mobility is interwoven with the emergence of asynchronous mobility dynamics. The lifting of restriction in urban mobility allowed a faster recovery of the spatial dimension compared with the temporal one. Moreover, the recovery in mobility was different depending on urbanization levels and economic stratification. In rural and low-income areas, the spatial mobility dimension suffered a more considerable disruption when compared with urbanized and high-income areas. In contrast, the temporal dimension was more affected in urbanized and high-income areas than in rural and low-income areas.

Indexed as

COVID-19Communicable Disease ControlHumansIncomePopulation DynamicsUrbanization

Identifiers

PMID37500782
PMCPMC10593607

What OpenQuestion holds

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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.