Evidence map›Paper›PMID 35757462›Full record

ArticleInternational journal of applied earth observation and geoinformation : ITC journal2022

COVID-19 lockdown introduces human mobility pattern changes for both Guangdong-Hong Kong-Macao greater bay area and the San Francisco bay area.

Leiyang Zhong, Ying Zhou, Song Gao, Zhaoyang Yu, Zhifeng Ma, Xiaoming Li, Yang Yue, Jizhe Xia

Open access · goldAbstract read
In one paragraph

Article in International journal of applied earth observation and geoinformation : ITC journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

4 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

8 authors at 4 institutions in 2 countries.

Leiyang ZhongGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Ying ZhouCollege of Public Health, Shenzhen University, Shenzhen 518060, China.
Song GaoGeospatial Data Science Lab, Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA.
Zhaoyang YuGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Zhifeng MaGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Xiaoming LiGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Yang YueGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Jizhe XiaGuangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China.
Ministry of Natural Resources · CNShenzhen University · CNShenzhen Bay Laboratory · CNUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In response to the coronavirus disease 2019 (COVID-19) pandemic, various countries have sought to control COVID-19 transmission by introducing non-pharmaceutical interventions. Restricting population mobility, by introducing social distancing, is one of the most widely used non-pharmaceutical interventions. Although similar population mobility restriction interventions were introduced, their impacts on COVID-19 transmission are often inconsistent across different regions and different time periods. These differences may provide critical information for tailoring COVID-19 control strategies. In this paper, anonymized high spatiotemporal resolution mobile-phone location data were employed to empirically analyze and quantify the impact of lockdowns on population mobility. Both the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China and the San Francisco Bay Area (SBA) in the United States were studied. In response to the lockdowns, a general reduction in population mobility was observed, but the structural changes in mobility are very different between the two bays: 1) GBA mobility decreased by approximately 74.0-80.1% while the decrease of SBA was about 25.0-42.1%; 2) compared to SBA, the GBA had smoother volatility in daily volume during the lockdown. The volatility change indexes for GBA and SBA were 2.55% and 7.52%, respectively; 3) the effect of lockdown on short- to long-distance mobility was similar in GBA while the medium- and long-distance impact was more pronounced in SBA.

Indexed as

COVID-19Guangdong-Hong Kong-Macao Greater Bay AreaHuman mobilityNon-pharmaceutical interventionsSan Francisco Bay AreaSpatiotemporal pattern discovery

Identifiers

PMID35757462
PMCPMC9212878
OpenAlexW4283220678

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.