Estimation and management of pandemic influenza transmission risk at mass immunization clinics
Mass immunization clinics (MICs) have become an essential component of pandemic influenza response strategies. By deploying large volumes of vaccines at centralized locations, public health authorities can reduce the complexity of emergency vaccine distribution while also enabling rapid, large-scale...
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creator | Beeler, Michael F. Aleman, Dionne M. Carter, Michael W. |
description | Mass immunization clinics (MICs) have become an essential component of pandemic influenza response strategies. By deploying large volumes of vaccines at centralized locations, public health authorities can reduce the complexity of emergency vaccine distribution while also enabling rapid, large-scale vaccination. The risk of influenza transmission at MICs must be understood and mitigated to maximize their effectiveness. We have developed a discrete-event simulation of an MIC that can estimate the expected number of infections resulting from disease transmission within the facility. A simulation experiment is conducted that varies MIC crowdedness, staffing levels and the percentage of infectious individuals entering the MIC-symptomatic or not-to assess the impact of these factors on expected infections. It is shown that the number of expected infections occurring in the MIC, though a small fraction of the influenza cases likely averted due to vaccination, is large enough to warrant mitigation measures. |
doi_str_mv | 10.1109/WSC.2011.6147834 |
format | Conference Proceeding |
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By deploying large volumes of vaccines at centralized locations, public health authorities can reduce the complexity of emergency vaccine distribution while also enabling rapid, large-scale vaccination. The risk of influenza transmission at MICs must be understood and mitigated to maximize their effectiveness. We have developed a discrete-event simulation of an MIC that can estimate the expected number of infections resulting from disease transmission within the facility. A simulation experiment is conducted that varies MIC crowdedness, staffing levels and the percentage of infectious individuals entering the MIC-symptomatic or not-to assess the impact of these factors on expected infections. 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By deploying large volumes of vaccines at centralized locations, public health authorities can reduce the complexity of emergency vaccine distribution while also enabling rapid, large-scale vaccination. The risk of influenza transmission at MICs must be understood and mitigated to maximize their effectiveness. We have developed a discrete-event simulation of an MIC that can estimate the expected number of infections resulting from disease transmission within the facility. A simulation experiment is conducted that varies MIC crowdedness, staffing levels and the percentage of infectious individuals entering the MIC-symptomatic or not-to assess the impact of these factors on expected infections. It is shown that the number of expected infections occurring in the MIC, though a small fraction of the influenza cases likely averted due to vaccination, is large enough to warrant mitigation measures.</description><subject>Atmospheric modeling</subject><subject>Computational modeling</subject><subject>Hazards</subject><subject>Microwave integrated circuits</subject><subject>Space stations</subject><subject>Vaccines</subject><issn>0891-7736</issn><issn>1558-4305</issn><isbn>1457721082</isbn><isbn>9781457721083</isbn><isbn>1457721074</isbn><isbn>9781457721076</isbn><isbn>9781457721090</isbn><isbn>1457721090</isbn><isbn>1457721066</isbn><isbn>9781457721069</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFUEtLxDAYjC-wu3oXvOQPtOZL2ubrUcquCgseVLy5pHlItMkuTffg_noru-BpYIYZZoaQG2AFAGvu3l_agjOAooZSoihPyAzKSkoOTJanJIOqwrwUrDr7F5Cfk4xhA7mUor4ks5S-GAOsgGfkY5FGH9ToN5GqaGhQUX3aYONIN45uJ8oGr6mPrt_ZuFd0HFRMwaf05xh8-qZqnFwpUR_CLvr9IUv3PnqdrsiFU32y10eck7fl4rV9zFfPD0_t_Sr3HOSYO3QCDCI2pdOcydpOzbWpuKsb1hnNOomd0sIxI53SBrngyMEp4zquEcSc3B5yvbV2vR2mScPP-niS-AVel1mD</recordid><startdate>201112</startdate><enddate>201112</enddate><creator>Beeler, Michael F.</creator><creator>Aleman, Dionne M.</creator><creator>Carter, Michael W.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201112</creationdate><title>Estimation and management of pandemic influenza transmission risk at mass immunization clinics</title><author>Beeler, Michael F. ; Aleman, Dionne M. ; Carter, Michael W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i217t-f8f31d88894fc2076e772cd52f690bdc0b78bac3f0d7facd8232821fadfb2c813</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Atmospheric modeling</topic><topic>Computational modeling</topic><topic>Hazards</topic><topic>Microwave integrated circuits</topic><topic>Space stations</topic><topic>Vaccines</topic><toplevel>online_resources</toplevel><creatorcontrib>Beeler, Michael F.</creatorcontrib><creatorcontrib>Aleman, Dionne M.</creatorcontrib><creatorcontrib>Carter, Michael W.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Beeler, Michael F.</au><au>Aleman, Dionne M.</au><au>Carter, Michael W.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Estimation and management of pandemic influenza transmission risk at mass immunization clinics</atitle><btitle>Proceedings of the 2011 Winter Simulation Conference (WSC)</btitle><stitle>WSC</stitle><date>2011-12</date><risdate>2011</risdate><spage>1117</spage><epage>1124</epage><pages>1117-1124</pages><issn>0891-7736</issn><eissn>1558-4305</eissn><isbn>1457721082</isbn><isbn>9781457721083</isbn><eisbn>1457721074</eisbn><eisbn>9781457721076</eisbn><eisbn>9781457721090</eisbn><eisbn>1457721090</eisbn><eisbn>1457721066</eisbn><eisbn>9781457721069</eisbn><abstract>Mass immunization clinics (MICs) have become an essential component of pandemic influenza response strategies. By deploying large volumes of vaccines at centralized locations, public health authorities can reduce the complexity of emergency vaccine distribution while also enabling rapid, large-scale vaccination. The risk of influenza transmission at MICs must be understood and mitigated to maximize their effectiveness. We have developed a discrete-event simulation of an MIC that can estimate the expected number of infections resulting from disease transmission within the facility. A simulation experiment is conducted that varies MIC crowdedness, staffing levels and the percentage of infectious individuals entering the MIC-symptomatic or not-to assess the impact of these factors on expected infections. It is shown that the number of expected infections occurring in the MIC, though a small fraction of the influenza cases likely averted due to vaccination, is large enough to warrant mitigation measures.</abstract><pub>IEEE</pub><doi>10.1109/WSC.2011.6147834</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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ispartof | Proceedings of the 2011 Winter Simulation Conference (WSC), 2011, p.1117-1124 |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Atmospheric modeling Computational modeling Hazards Microwave integrated circuits Space stations Vaccines |
title | Estimation and management of pandemic influenza transmission risk at mass immunization clinics |
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