COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Medical decision making 2021-05, Vol.41 (4), p.419-429
Hauptverfasser: Lee, Serin, Zabinsky, Zelda B., Wasserheit, Judith N., Kofsky, Stephen M., Liu, Shan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 429
container_issue 4
container_start_page 419
container_title Medical decision making
container_volume 41
creator Lee, Serin
Zabinsky, Zelda B.
Wasserheit, Judith N.
Kofsky, Stephen M.
Liu, Shan
description As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.
doi_str_mv 10.1177/0272989X211003081
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2502804720</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_0272989X211003081</sage_id><sourcerecordid>2502804720</sourcerecordid><originalsourceid>FETCH-LOGICAL-c340t-d90b3e29c1a870a44f4e5ca204b37f642b03271da2f7db3783949c5cccbe6e403</originalsourceid><addsrcrecordid>eNp9kMtKxDAUhoMoOl4ewI1k6aaaWyeNOxlvA4OKN9yVND0dI21Sk1aYt7dl1I3g6sA53_fD-RE6pOSEUilPCZNMZeqVUUoIJxndQBOapiyZZvR1E03GezICO2g3xndCqFCZ2EY7nEvOFecT1M_uXuYXCVX4XrsSGmvwA8TWuwj40TZ9rTvrHbYOa7zQYQl4ZrvVGZ43rTYd9hW-9a5906HRBvrOGl3juesgfIIbzYgH-wF8C866JX70xkK32kdbla4jHHzPPfR8dfk0u0kWd9fz2fkiMVyQLikVKTgwZajOJNFCVAJSoxkRBZfVVLCCcCZpqVkly2GVcSWUSY0xBUxBEL6Hjte5bfAfPcQub2w0UNfage9jzlLCMiIkG1G6Rk3wMQao8jbYRodVTkk-tp3_aXtwjr7j-6KB8tf4qXcATtZA1EvI330f3PDuP4lfgUCHzQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2502804720</pqid></control><display><type>article</type><title>COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society</title><source>MEDLINE</source><source>SAGE Complete A-Z List</source><creator>Lee, Serin ; Zabinsky, Zelda B. ; Wasserheit, Judith N. ; Kofsky, Stephen M. ; Liu, Shan</creator><creatorcontrib>Lee, Serin ; Zabinsky, Zelda B. ; Wasserheit, Judith N. ; Kofsky, Stephen M. ; Liu, Shan</creatorcontrib><description>As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.</description><identifier>ISSN: 0272-989X</identifier><identifier>EISSN: 1552-681X</identifier><identifier>DOI: 10.1177/0272989X211003081</identifier><identifier>PMID: 33733933</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Communicable Disease Control - methods ; Computer Simulation ; Contact Tracing ; COVID-19 - prevention &amp; control ; Disease Outbreaks ; Humans ; Masks ; Pandemics ; Physical Distancing ; SARS-CoV-2 ; Social Conditions ; Urban Population ; Washington</subject><ispartof>Medical decision making, 2021-05, Vol.41 (4), p.419-429</ispartof><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c340t-d90b3e29c1a870a44f4e5ca204b37f642b03271da2f7db3783949c5cccbe6e403</citedby><cites>FETCH-LOGICAL-c340t-d90b3e29c1a870a44f4e5ca204b37f642b03271da2f7db3783949c5cccbe6e403</cites><orcidid>0000-0003-1838-4981 ; 0000-0003-1459-8923 ; 0000-0002-5343-7244</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0272989X211003081$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0272989X211003081$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21810,27915,27916,43612,43613</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33733933$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Serin</creatorcontrib><creatorcontrib>Zabinsky, Zelda B.</creatorcontrib><creatorcontrib>Wasserheit, Judith N.</creatorcontrib><creatorcontrib>Kofsky, Stephen M.</creatorcontrib><creatorcontrib>Liu, Shan</creatorcontrib><title>COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society</title><title>Medical decision making</title><addtitle>Med Decis Making</addtitle><description>As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.</description><subject>Communicable Disease Control - methods</subject><subject>Computer Simulation</subject><subject>Contact Tracing</subject><subject>COVID-19 - prevention &amp; control</subject><subject>Disease Outbreaks</subject><subject>Humans</subject><subject>Masks</subject><subject>Pandemics</subject><subject>Physical Distancing</subject><subject>SARS-CoV-2</subject><subject>Social Conditions</subject><subject>Urban Population</subject><subject>Washington</subject><issn>0272-989X</issn><issn>1552-681X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kMtKxDAUhoMoOl4ewI1k6aaaWyeNOxlvA4OKN9yVND0dI21Sk1aYt7dl1I3g6sA53_fD-RE6pOSEUilPCZNMZeqVUUoIJxndQBOapiyZZvR1E03GezICO2g3xndCqFCZ2EY7nEvOFecT1M_uXuYXCVX4XrsSGmvwA8TWuwj40TZ9rTvrHbYOa7zQYQl4ZrvVGZ43rTYd9hW-9a5906HRBvrOGl3juesgfIIbzYgH-wF8C866JX70xkK32kdbla4jHHzPPfR8dfk0u0kWd9fz2fkiMVyQLikVKTgwZajOJNFCVAJSoxkRBZfVVLCCcCZpqVkly2GVcSWUSY0xBUxBEL6Hjte5bfAfPcQub2w0UNfage9jzlLCMiIkG1G6Rk3wMQao8jbYRodVTkk-tp3_aXtwjr7j-6KB8tf4qXcATtZA1EvI330f3PDuP4lfgUCHzQ</recordid><startdate>202105</startdate><enddate>202105</enddate><creator>Lee, Serin</creator><creator>Zabinsky, Zelda B.</creator><creator>Wasserheit, Judith N.</creator><creator>Kofsky, Stephen M.</creator><creator>Liu, Shan</creator><general>SAGE Publications</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-1838-4981</orcidid><orcidid>https://orcid.org/0000-0003-1459-8923</orcidid><orcidid>https://orcid.org/0000-0002-5343-7244</orcidid></search><sort><creationdate>202105</creationdate><title>COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society</title><author>Lee, Serin ; Zabinsky, Zelda B. ; Wasserheit, Judith N. ; Kofsky, Stephen M. ; Liu, Shan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c340t-d90b3e29c1a870a44f4e5ca204b37f642b03271da2f7db3783949c5cccbe6e403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Communicable Disease Control - methods</topic><topic>Computer Simulation</topic><topic>Contact Tracing</topic><topic>COVID-19 - prevention &amp; control</topic><topic>Disease Outbreaks</topic><topic>Humans</topic><topic>Masks</topic><topic>Pandemics</topic><topic>Physical Distancing</topic><topic>SARS-CoV-2</topic><topic>Social Conditions</topic><topic>Urban Population</topic><topic>Washington</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Serin</creatorcontrib><creatorcontrib>Zabinsky, Zelda B.</creatorcontrib><creatorcontrib>Wasserheit, Judith N.</creatorcontrib><creatorcontrib>Kofsky, Stephen M.</creatorcontrib><creatorcontrib>Liu, Shan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Medical decision making</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Serin</au><au>Zabinsky, Zelda B.</au><au>Wasserheit, Judith N.</au><au>Kofsky, Stephen M.</au><au>Liu, Shan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society</atitle><jtitle>Medical decision making</jtitle><addtitle>Med Decis Making</addtitle><date>2021-05</date><risdate>2021</risdate><volume>41</volume><issue>4</issue><spage>419</spage><epage>429</epage><pages>419-429</pages><issn>0272-989X</issn><eissn>1552-681X</eissn><abstract>As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>33733933</pmid><doi>10.1177/0272989X211003081</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-1838-4981</orcidid><orcidid>https://orcid.org/0000-0003-1459-8923</orcidid><orcidid>https://orcid.org/0000-0002-5343-7244</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0272-989X
ispartof Medical decision making, 2021-05, Vol.41 (4), p.419-429
issn 0272-989X
1552-681X
language eng
recordid cdi_proquest_miscellaneous_2502804720
source MEDLINE; SAGE Complete A-Z List
subjects Communicable Disease Control - methods
Computer Simulation
Contact Tracing
COVID-19 - prevention & control
Disease Outbreaks
Humans
Masks
Pandemics
Physical Distancing
SARS-CoV-2
Social Conditions
Urban Population
Washington
title COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T04%3A34%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=COVID-19%20Pandemic%20Response%20Simulation%20in%20a%20Large%20City:%20Impact%20of%20Nonpharmaceutical%20Interventions%20on%20Reopening%20Society&rft.jtitle=Medical%20decision%20making&rft.au=Lee,%20Serin&rft.date=2021-05&rft.volume=41&rft.issue=4&rft.spage=419&rft.epage=429&rft.pages=419-429&rft.issn=0272-989X&rft.eissn=1552-681X&rft_id=info:doi/10.1177/0272989X211003081&rft_dat=%3Cproquest_cross%3E2502804720%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2502804720&rft_id=info:pmid/33733933&rft_sage_id=10.1177_0272989X211003081&rfr_iscdi=true