COVID-19 Intervention Scenarios for a Long-term Disease Management.
Identifieur interne : 001E92 ( Main/Corpus ); précédent : 001E91; suivant : 001E93COVID-19 Intervention Scenarios for a Long-term Disease Management.
Auteurs : Gudrun Wallentin ; Dana Kaziyeva ; Eva Reibersdorfer-AdelsbergerSource :
- International journal of health policy and management [ 2322-5939 ] ; 2020.
Abstract
BACKGROUND
The first outbreak of coronavirus disease 2019 (COVID-19) was successfully restrained in many countries around the world by means of a severe lockdown. Now, we are entering the second phase of the pandemics in which the spread of the virus needs to be contained within the limits that national health systems can cope with. This second phase of the epidemics is expected to last until a vaccination is available or herd immunity is reached. Long-term management strategies thus need to be developed.
METHODS
In this paper we present a new agent-based simulation model "COVID-19 ABM" with which we simulate 4 alternative scenarios for the second "new normality" phase that can help decision-makers to take adequate control and intervention measures.
RESULTS
The scenarios resulted in distinctly different outcomes. A continued lockdown could regionally eradicate the virus within a few months, whereas a relaxation back to 80% of former activity-levels was followed by a second outbreak. Contact-tracing as well as adaptive response strategies could keep COVID-19 within limits.
CONCLUSION
The main insights are that low-level voluntary use of tracing apps shows no relevant effects on containing the virus, whereas medium or high-level tracing allows maintaining a considerably higher level of social activity. Adaptive control strategies help in finding the level of least restrictions. A regional approach to adaptive management can further help in fine-tuning the response to regional dynamics and thus minimise negative economic effects.
DOI: 10.34172/ijhpm.2020.130
PubMed: 32729281
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">COVID-19 Intervention Scenarios for a Long-term Disease Management.</title><author><name sortKey="Wallentin, Gudrun" sort="Wallentin, Gudrun" uniqKey="Wallentin G" first="Gudrun" last="Wallentin">Gudrun Wallentin</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author><author><name sortKey="Kaziyeva, Dana" sort="Kaziyeva, Dana" uniqKey="Kaziyeva D" first="Dana" last="Kaziyeva">Dana Kaziyeva</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author><author><name sortKey="Reibersdorfer Adelsberger, Eva" sort="Reibersdorfer Adelsberger, Eva" uniqKey="Reibersdorfer Adelsberger E" first="Eva" last="Reibersdorfer-Adelsberger">Eva Reibersdorfer-Adelsberger</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32729281</idno><idno type="pmid">32729281</idno><idno type="doi">10.34172/ijhpm.2020.130</idno><idno type="wicri:Area/Main/Corpus">001E92</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001E92</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">COVID-19 Intervention Scenarios for a Long-term Disease Management.</title><author><name sortKey="Wallentin, Gudrun" sort="Wallentin, Gudrun" uniqKey="Wallentin G" first="Gudrun" last="Wallentin">Gudrun Wallentin</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author><author><name sortKey="Kaziyeva, Dana" sort="Kaziyeva, Dana" uniqKey="Kaziyeva D" first="Dana" last="Kaziyeva">Dana Kaziyeva</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author><author><name sortKey="Reibersdorfer Adelsberger, Eva" sort="Reibersdorfer Adelsberger, Eva" uniqKey="Reibersdorfer Adelsberger E" first="Eva" last="Reibersdorfer-Adelsberger">Eva Reibersdorfer-Adelsberger</name><affiliation><nlm:affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</nlm:affiliation></affiliation></author></analytic><series><title level="j">International journal of health policy and management</title><idno type="eISSN">2322-5939</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>The first outbreak of coronavirus disease 2019 (COVID-19) was successfully restrained in many countries around the world by means of a severe lockdown. Now, we are entering the second phase of the pandemics in which the spread of the virus needs to be contained within the limits that national health systems can cope with. This second phase of the epidemics is expected to last until a vaccination is available or herd immunity is reached. Long-term management strategies thus need to be developed.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>In this paper we present a new agent-based simulation model "COVID-19 ABM" with which we simulate 4 alternative scenarios for the second "new normality" phase that can help decision-makers to take adequate control and intervention measures.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>The scenarios resulted in distinctly different outcomes. A continued lockdown could regionally eradicate the virus within a few months, whereas a relaxation back to 80% of former activity-levels was followed by a second outbreak. Contact-tracing as well as adaptive response strategies could keep COVID-19 within limits.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>The main insights are that low-level voluntary use of tracing apps shows no relevant effects on containing the virus, whereas medium or high-level tracing allows maintaining a considerably higher level of social activity. Adaptive control strategies help in finding the level of least restrictions. A regional approach to adaptive management can further help in fine-tuning the response to regional dynamics and thus minimise negative economic effects.</p></div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32729281</PMID><DateRevised><Year>2020</Year><Month>07</Month><Day>30</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2322-5939</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Jul</Month><Day>26</Day></PubDate></JournalIssue><Title>International journal of health policy and management</Title><ISOAbbreviation>Int J Health Policy Manag</ISOAbbreviation></Journal><ArticleTitle>COVID-19 Intervention Scenarios for a Long-term Disease Management.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.34172/ijhpm.2020.130</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">The first outbreak of coronavirus disease 2019 (COVID-19) was successfully restrained in many countries around the world by means of a severe lockdown. Now, we are entering the second phase of the pandemics in which the spread of the virus needs to be contained within the limits that national health systems can cope with. This second phase of the epidemics is expected to last until a vaccination is available or herd immunity is reached. Long-term management strategies thus need to be developed.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">In this paper we present a new agent-based simulation model "COVID-19 ABM" with which we simulate 4 alternative scenarios for the second "new normality" phase that can help decision-makers to take adequate control and intervention measures.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">The scenarios resulted in distinctly different outcomes. A continued lockdown could regionally eradicate the virus within a few months, whereas a relaxation back to 80% of former activity-levels was followed by a second outbreak. Contact-tracing as well as adaptive response strategies could keep COVID-19 within limits.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">The main insights are that low-level voluntary use of tracing apps shows no relevant effects on containing the virus, whereas medium or high-level tracing allows maintaining a considerably higher level of social activity. Adaptive control strategies help in finding the level of least restrictions. A regional approach to adaptive management can further help in fine-tuning the response to regional dynamics and thus minimise negative economic effects.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wallentin</LastName><ForeName>Gudrun</ForeName><Initials>G</Initials><Identifier Source="ORCID">0000-0002-3845-7685</Identifier><AffiliationInfo><Affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kaziyeva</LastName><ForeName>Dana</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Reibersdorfer-Adelsberger</LastName><ForeName>Eva</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>26</Day></ArticleDate></Article><MedlineJournalInfo><Country>Iran</Country><MedlineTA>Int J Health Policy Manag</MedlineTA><NlmUniqueID>101619905</NlmUniqueID><ISSNLinking>2322-5939</ISSNLinking></MedlineJournalInfo><CitationSubset>H</CitationSubset><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Agent-Based Model</Keyword><Keyword MajorTopicYN="N">Containment</Keyword><Keyword MajorTopicYN="N">Corona Virus</Keyword><Keyword MajorTopicYN="N">Pandemic</Keyword><Keyword MajorTopicYN="N">Scenario Analysis</Keyword><Keyword MajorTopicYN="N">Simulation</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>04</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>07</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>7</Month><Day>31</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>7</Month><Day>31</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>7</Month><Day>31</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32729281</ArticleId><ArticleId IdType="doi">10.34172/ijhpm.2020.130</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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