Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia.
Identifieur interne : 000F18 ( Main/Corpus ); précédent : 000F17; suivant : 000F19Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia.
Auteurs : Siqin Wang ; Yan Liu ; Tao HuSource :
- International journal of environmental research and public health [ 1660-4601 ] ; 2020.
English descriptors
- KwdEn :
- Australia (epidemiology), Betacoronavirus (MeSH), COVID-19 (MeSH), Coronavirus Infections (epidemiology), Coronavirus Infections (prevention & control), Guideline Adherence (statistics & numerical data), Humans (MeSH), Pandemics (prevention & control), Pneumonia, Viral (epidemiology), Pneumonia, Viral (prevention & control), Public Policy (MeSH), Quarantine (MeSH), SARS-CoV-2 (MeSH), Travel (MeSH).
- MESH :
- geographic , epidemiology : Australia.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- prevention & control : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- statistics & numerical data : Guideline Adherence.
- Betacoronavirus, COVID-19, Humans, Public Policy, Quarantine, SARS-CoV-2, Travel.
Abstract
The policy induced decline of human mobility has been recognised as effective in controlling the spread of COVID-19, especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling the data of confirmed COVID-19 cases with the Google mobility data in Australia, we present a state-level empirical study to: (1) inspect the temporal variation of the COVID-19 spread and the change of human mobility adherent to social restriction policies; (2) examine the extent to which different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and (3) analyse the time lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time lag effect on the growth rates of COVID-19, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between human mobility and COVID-19 spread varies across space and time and is subject to the types of mobility. Thus, it is important for government to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.
DOI: 10.3390/ijerph17217930
PubMed: 33137958
PubMed Central: PMC7662641
Links to Exploration step
pubmed:33137958Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia.</title>
<author><name sortKey="Wang, Siqin" sort="Wang, Siqin" uniqKey="Wang S" first="Siqin" last="Wang">Siqin Wang</name>
<affiliation><nlm:affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Liu, Yan" sort="Liu, Yan" uniqKey="Liu Y" first="Yan" last="Liu">Yan Liu</name>
<affiliation><nlm:affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Hu, Tao" sort="Hu, Tao" uniqKey="Hu T" first="Tao" last="Hu">Tao Hu</name>
<affiliation><nlm:affiliation>Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA.</nlm:affiliation>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2020">2020</date>
<idno type="RBID">pubmed:33137958</idno>
<idno type="pmid">33137958</idno>
<idno type="doi">10.3390/ijerph17217930</idno>
<idno type="pmc">PMC7662641</idno>
<idno type="wicri:Area/Main/Corpus">000F18</idno>
<idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000F18</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia.</title>
<author><name sortKey="Wang, Siqin" sort="Wang, Siqin" uniqKey="Wang S" first="Siqin" last="Wang">Siqin Wang</name>
<affiliation><nlm:affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Liu, Yan" sort="Liu, Yan" uniqKey="Liu Y" first="Yan" last="Liu">Yan Liu</name>
<affiliation><nlm:affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Hu, Tao" sort="Hu, Tao" uniqKey="Hu T" first="Tao" last="Hu">Tao Hu</name>
<affiliation><nlm:affiliation>Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA.</nlm:affiliation>
</affiliation>
</author>
</analytic>
<series><title level="j">International journal of environmental research and public health</title>
<idno type="eISSN">1660-4601</idno>
<imprint><date when="2020" type="published">2020</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Australia (epidemiology)</term>
<term>Betacoronavirus (MeSH)</term>
<term>COVID-19 (MeSH)</term>
<term>Coronavirus Infections (epidemiology)</term>
<term>Coronavirus Infections (prevention & control)</term>
<term>Guideline Adherence (statistics & numerical data)</term>
<term>Humans (MeSH)</term>
<term>Pandemics (prevention & control)</term>
<term>Pneumonia, Viral (epidemiology)</term>
<term>Pneumonia, Viral (prevention & control)</term>
<term>Public Policy (MeSH)</term>
<term>Quarantine (MeSH)</term>
<term>SARS-CoV-2 (MeSH)</term>
<term>Travel (MeSH)</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Australia</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pandemics</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Guideline Adherence</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Betacoronavirus</term>
<term>COVID-19</term>
<term>Humans</term>
<term>Public Policy</term>
<term>Quarantine</term>
<term>SARS-CoV-2</term>
<term>Travel</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The policy induced decline of human mobility has been recognised as effective in controlling the spread of COVID-19, especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling the data of confirmed COVID-19 cases with the Google mobility data in Australia, we present a state-level empirical study to: (1) inspect the temporal variation of the COVID-19 spread and the change of human mobility adherent to social restriction policies; (2) examine the extent to which different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and (3) analyse the time lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time lag effect on the growth rates of COVID-19, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between human mobility and COVID-19 spread varies across space and time and is subject to the types of mobility. Thus, it is important for government to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">33137958</PMID>
<DateCompleted><Year>2020</Year>
<Month>11</Month>
<Day>12</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>12</Month>
<Day>18</Day>
</DateRevised>
<Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1660-4601</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>17</Volume>
<Issue>21</Issue>
<PubDate><Year>2020</Year>
<Month>10</Month>
<Day>29</Day>
</PubDate>
</JournalIssue>
<Title>International journal of environmental research and public health</Title>
<ISOAbbreviation>Int J Environ Res Public Health</ISOAbbreviation>
</Journal>
<ArticleTitle>Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia.</ArticleTitle>
<ELocationID EIdType="pii" ValidYN="Y">E7930</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.3390/ijerph17217930</ELocationID>
<Abstract><AbstractText>The policy induced decline of human mobility has been recognised as effective in controlling the spread of COVID-19, especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling the data of confirmed COVID-19 cases with the Google mobility data in Australia, we present a state-level empirical study to: (1) inspect the temporal variation of the COVID-19 spread and the change of human mobility adherent to social restriction policies; (2) examine the extent to which different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and (3) analyse the time lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time lag effect on the growth rates of COVID-19, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between human mobility and COVID-19 spread varies across space and time and is subject to the types of mobility. Thus, it is important for government to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Siqin</ForeName>
<Initials>S</Initials>
<Identifier Source="ORCID">0000-0002-1809-7088</Identifier>
<AffiliationInfo><Affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Liu</LastName>
<ForeName>Yan</ForeName>
<Initials>Y</Initials>
<Identifier Source="ORCID">0000-0002-1612-779X</Identifier>
<AffiliationInfo><Affiliation>School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD 4067, Australia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hu</LastName>
<ForeName>Tao</ForeName>
<Initials>T</Initials>
<Identifier Source="ORCID">0000-0002-8557-8017</Identifier>
<AffiliationInfo><Affiliation>Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>DP170104235</GrantID>
<Agency>Australian Research Council</Agency>
<Country>International</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>10</Month>
<Day>29</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>Switzerland</Country>
<MedlineTA>Int J Environ Res Public Health</MedlineTA>
<NlmUniqueID>101238455</NlmUniqueID>
<ISSNLinking>1660-4601</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D001315" MajorTopicYN="N" Type="Geographic">Australia</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="Y">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D019983" MajorTopicYN="N">Guideline Adherence</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
<QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011640" MajorTopicYN="Y">Public Policy</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011790" MajorTopicYN="Y">Quarantine</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D014195" MajorTopicYN="N">Travel</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Australia</Keyword>
<Keyword MajorTopicYN="Y">COVID-19 spread</Keyword>
<Keyword MajorTopicYN="Y">global pandemic</Keyword>
<Keyword MajorTopicYN="Y">human mobility</Keyword>
<Keyword MajorTopicYN="Y">social restriction policy</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year>
<Month>09</Month>
<Day>07</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2020</Year>
<Month>10</Month>
<Day>26</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>10</Month>
<Day>27</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>11</Month>
<Day>3</Day>
<Hour>1</Hour>
<Minute>2</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>11</Month>
<Day>4</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>11</Month>
<Day>13</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>epublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">33137958</ArticleId>
<ArticleId IdType="pii">ijerph17217930</ArticleId>
<ArticleId IdType="doi">10.3390/ijerph17217930</ArticleId>
<ArticleId IdType="pmc">PMC7662641</ArticleId>
</ArticleIdList>
<ReferenceList><Reference><Citation>Sci Total Environ. 2020 Nov 1;741:140489</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32599395</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Transp Policy (Oxf). 2020 Sep;96:76-93</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32834680</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Med. 2020 Sep;26(9):1398-1404</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32647358</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Ann Intern Med. 2020 May 5;172(9):577-582</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32150748</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Commun. 2020 Nov 11;11(1):5710</Citation>
<ArticleIdList><ArticleId IdType="pubmed">33177507</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Public Health. 2020 Aug;185:364-367</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32739776</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Math Biosci Eng. 2020 Jul 13;17(5):4891-4904</Citation>
<ArticleIdList><ArticleId IdType="pubmed">33120533</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Jul 10;725:138436</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32298883</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Science. 2020 Apr 24;368(6489):395-400</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32144116</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/LockdownV1/Data/Main/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000F18 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Corpus/biblio.hfd -nk 000F18 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Sante |area= LockdownV1 |flux= Main |étape= Corpus |type= RBID |clé= pubmed:33137958 |texte= Examining the Change of Human Mobility Adherent to Social Restriction Policies and Its Effect on COVID-19 Cases in Australia. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Corpus/RBID.i -Sk "pubmed:33137958" \ | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Corpus/biblio.hfd \ | NlmPubMed2Wicri -a LockdownV1
![]() | This area was generated with Dilib version V0.6.38. | ![]() |