Evidence map›Paper›PMID 33312379›Full record

ArticleAmerican journal of translational research2020

State heterogeneity in the associations of human mobility with COVID-19 epidemics in the European Union.

Xiaoling Yuan, Kun Hu, Jie Xu, Xuchen Zhang, Wei Bao, Charles F Lynch, Lanjing Zhang

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 45% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Xiaoling YuanDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai, China.
Kun HuDepartment of Pathology, University at Buffalo Buffalo, NY, USA.
Jie XuDepartment of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine Shanghai, China.
Xuchen ZhangDepartment of Pathology, Yale University School of Medicine New Haven, CT, USA.
Wei BaoDepartment of Epidemiology, College of Public Health, University of Iowa Iowa City, IA, USA.
Charles F LynchDepartment of Epidemiology, College of Public Health, University of Iowa Iowa City, IA, USA.
Lanjing ZhangDepartment of Biological Sciences, Rutgers University Newark NJ, USA.
Shanghai Ninth People's Hospital · CN

Funding

Pulmonary Toxicology Facility CoreP30ES005605 · NIEHS · UNIVERSITY OF IOWA · PI Jong Sung Kim · 1990 to 2026
$40.5M
NIEHS NIH HHS P30 ES005605
6 · The paper itself

Abstract

backgroundHuman mobility was associated with epidemic changes of coronavirus disease 2019 (COVID-19) in the countries, where strict public health interventions reduced human mobility and COVID-19 epidemics. But its association with COVID-19 epidemics in the European Union (EU) is unclear.

methodsIn this quasi-experimental interrupted time-series study, we modelled trends in human mobility and epidemics of COVID-19 in 27 EU states between January 15 and May 9, 2020. The associations of lockdown-date, and turning points of these trends were assessed.

resultsThere were 982,332 laboratory-confirmed COVID-19 cases in the EU states (median 7,896, interquartile 1,689 to 25,702 for individual states) during the study-period. COVID-19 and human mobility had 3 trend-segments, including an upward trend in COVID-19 daily incidence and a downward trend in most human mobilities in the middle segment. Compared with the states farther from Italy, the state-wide lockdown dates were more likely linked to turning points of human mobilities in the states closer to Italy, which were also more likely linked to second turning points of COVID-19 epidemics. Among the examined human mobilities, the second turning points in driving mobility and the first turning points in parks mobility were the best factors that connected lockdown dates and COVID-19 epidemics in the EU states closer to Italy.

conclusionsWe show state- and mobility-heterogeneity in the associations of public health interventions and human mobility with the changes of COVID-19 epidemics in the EU. These findings may help inform policymakers on the best timing and monitoring-parameters of state-level interventions in the EU.

Indexed as

Coronavirus 2019epidemicsgeographicpublic health interventiontrends

Identifiers

PMID33312379
PMCPMC7724319
OpenAlexW3112099552

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.