Evidence map›Paper›PMID 36330119›Full record

ArticleFrontiers in public health2022

Human mobility variations in response to restriction policies during the COVID-19 pandemic: An analysis from the Virus Watch community cohort in England, UK.

Tao Cheng, Tongxin Chen, Yunzhe Liu, Robert W Aldridge, Vincent Nguyen, Andrew C Hayward, Susan Michie

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Use of cell phone data to correct Île-de-France population estimates and SARS-CoV-2 incidence, July to September, 2021: a proof-of-concept exercise.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
  3. EFAS/EAN survey on the influence of the COVID-19 pandemic on European clinical autonomic education and research.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2023
    Article
  4. Article
  5. 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

7 authors.

Tao ChengSpaceTimeLab for Big Data Analytics, Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom.
Tongxin ChenSpaceTimeLab for Big Data Analytics, Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom.
Yunzhe LiuSpaceTimeLab for Big Data Analytics, Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom.
Robert W AldridgeInstitute of Health Informatics, University College London, London, United Kingdom.
Vincent NguyenInstitute of Health Informatics, University College London, London, United Kingdom.
Andrew C HaywardInstitute of Epidemiology and Health Care, University College London, London, United Kingdom.
Susan MichieCentre for Behaviour Change, University College London, London, United Kingdom.

Funding

Medical Research Council MC PC 19,070Medical Research Council MC_PC_19070Medical Research Council MR/V028375/1
6 · The paper itself

Abstract

Objective: Since the outbreak of COVID-19, public health and social measures to contain its transmission (e.g., social distancing and lockdowns) have dramatically changed people's lives in rural and urban areas globally. To facilitate future management of the pandemic, it is important to understand how different socio-demographic groups adhere to such demands. This study aims to evaluate the influences of restriction policies on human mobility variations associated with socio-demographic groups in England, UK. Methods: Using mobile phone global positioning system (GPS) trajectory data, we measured variations in human mobility across socio-demographic groups during different restriction periods from Oct 14, 2020 to Sep 15, 2021. The six restriction periods which varied in degree of mobility restriction policies, denoted as "Three-tier Restriction," "Second National Lockdown," "Four-tier Restriction," "Third National Lockdown," "Steps out of Lockdown," and "Post-restriction," respectively. Individual human mobility was measured with respect to the time period people stayed at home, visited places outside the home, and traveled long distances. We compared these indicators across the six restriction periods and across socio-demographic groups. Results: All human mobility indicators significantly differed across the six restriction periods, and the influences of restriction policies on individual mobility behaviors are correlated with socio-demographic groups. In particular, influences relating to mobility behaviors are stronger in younger and low-income groups in the second and third national lockdowns. Conclusions: This study enhances our understanding of the influences of COVID-19 pandemic restriction policies on human mobility behaviors within different social groups in England. The findings can be usefully extended to support policy-making by investigating human mobility and differences in policy effects across not only age and income groups, but also across geographical regions.

Indexed as

COVID-19Communicable Disease ControlHumansPandemicsPolicyUnited KingdomCOVID-19GPS data analysishuman mobilitymobility inequalitypandemicphysical activity

Identifiers

PMID36330119
PMCPMC9623896

What OpenQuestion holds

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LicenceCC BY
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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.