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Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses
ObjectivesUniversities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 tran...
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description | ObjectivesUniversities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions.InterventionsTesting of students 0, 1 and 2 times prior to campus arrival.Primary outcomesNumber of active infections and time until isolation bed capacity is reached.SettingWe set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R0=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester.ResultsWithout presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R0=1.5) to 10 481 under ineffective mitigation strategies (R0=4), and exhausted isolation bed capacity within 10 (R0=4) to 25 days (R0=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R0=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester.ConclusionsPresemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity. |
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National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions.InterventionsTesting of students 0, 1 and 2 times prior to campus arrival.Primary outcomesNumber of active infections and time until isolation bed capacity is reached.SettingWe set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R0=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester.ResultsWithout presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R0=1.5) to 10 481 under ineffective mitigation strategies (R0=4), and exhausted isolation bed capacity within 10 (R0=4) to 25 days (R0=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R0=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester.ConclusionsPresemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity.</description><identifier>ISSN: 2044-6055</identifier><identifier>EISSN: 2044-6055</identifier><identifier>DOI: 10.1136/bmjopen-2020-042578</identifier><identifier>PMID: 33323447</identifier><language>eng</language><publisher>England: British Medical Journal Publishing Group</publisher><subject><![CDATA[College campuses ; Colleges & universities ; Communicable Disease Control - methods ; Contact tracing ; Coronaviruses ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - prevention & control ; COVID-19 Testing ; Disease Outbreaks - prevention & control ; Disease transmission ; Epidemics ; health policy ; Humans ; infection control ; Infections ; Infectious Diseases ; Mass Screening - methods ; Models, Theoretical ; Population ; Public health ; Severe acute respiratory syndrome coronavirus 2 ; South Carolina ; statistics & research methods ; Students ; Students - statistics & numerical data ; Universities - organization & administration]]></subject><ispartof>BMJ open, 2020-12, Vol.10 (12), p.e042578-e042578</ispartof><rights>Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b578t-dfb26df380fa59b76b790cc48f072db3f0c27b5b7ba85d3b4a0dfc0434da88a53</citedby><cites>FETCH-LOGICAL-b578t-dfb26df380fa59b76b790cc48f072db3f0c27b5b7ba85d3b4a0dfc0434da88a53</cites><orcidid>0000-0001-5275-7273</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2470159621?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2470159621?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>112,113,230,314,727,780,784,885,3194,25753,27549,27550,27924,27925,37012,37013,38516,43895,44590,53791,53793,55341,55350,74412,75126,77594,77595,77596,77597,77601,77632,77660,77686</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33323447$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rennert, Lior</creatorcontrib><creatorcontrib>Kalbaugh, Corey Andrew</creatorcontrib><creatorcontrib>Shi, Lu</creatorcontrib><creatorcontrib>McMahan, Christopher</creatorcontrib><title>Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses</title><title>BMJ open</title><addtitle>BMJ Open</addtitle><addtitle>BMJ Open</addtitle><description>ObjectivesUniversities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions.InterventionsTesting of students 0, 1 and 2 times prior to campus arrival.Primary outcomesNumber of active infections and time until isolation bed capacity is reached.SettingWe set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R0=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester.ResultsWithout presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R0=1.5) to 10 481 under ineffective mitigation strategies (R0=4), and exhausted isolation bed capacity within 10 (R0=4) to 25 days (R0=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R0=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester.ConclusionsPresemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity.</description><subject>College campuses</subject><subject>Colleges & universities</subject><subject>Communicable Disease Control - methods</subject><subject>Contact tracing</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - diagnosis</subject><subject>COVID-19 - prevention & control</subject><subject>COVID-19 Testing</subject><subject>Disease Outbreaks - prevention & control</subject><subject>Disease transmission</subject><subject>Epidemics</subject><subject>health policy</subject><subject>Humans</subject><subject>infection control</subject><subject>Infections</subject><subject>Infectious Diseases</subject><subject>Mass Screening - methods</subject><subject>Models, Theoretical</subject><subject>Population</subject><subject>Public health</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>South Carolina</subject><subject>statistics & research methods</subject><subject>Students</subject><subject>Students - statistics & numerical data</subject><subject>Universities - organization & administration</subject><issn>2044-6055</issn><issn>2044-6055</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>9YT</sourceid><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkktv1DAUhSMEolXpL0BCltiwSetn7GyQ0BToSEXdAGJn-ZWphyQOtlOp_x5PMx1aFghvrmV_5-j6-lTVawTPECLNuR62YXJjjSGGNaSYcfGsOsaQ0rqBjD1_tD-qTlPawrIoaxnDL6sjQggmlPLj6seXYF3f-3ED8o0DfpiUySB0YIouucGl7CLIpeyIMILV9ff1RY1aEOaso1M_E_AjmEd_62Ly-Q4YNUxzculV9aJTfXKn-3pSffv08evqsr66_rxefbiqdWk517bTuLEdEbBTrNW80byFxlDRQY6tJh00mGumuVaCWaKpgrYzkBJqlRCKkZNqvfjaoLZyin5Q8U4G5eX9QYgbqWL2pndSaKwQNULApqHGti2yLbQccc4t50gUr_eL1zTrwVnjxhxV_8T06c3ob-Qm3ErOKaOMFIN3e4MYfs1lanLwyZT5qtGFOUlMOWywQBQX9O1f6DbMcSyjuqcQaxuMCkUWysSQUnTdoRkE5S4Ich8EuQuCXIJQVG8ev-Ogefj2ApwtQFH_p-P5H8Gh0X8pfgMS0M4Q</recordid><startdate>20201215</startdate><enddate>20201215</enddate><creator>Rennert, Lior</creator><creator>Kalbaugh, Corey Andrew</creator><creator>Shi, Lu</creator><creator>McMahan, Christopher</creator><general>British Medical Journal Publishing Group</general><general>BMJ Publishing Group LTD</general><general>BMJ Publishing Group</general><scope>9YT</scope><scope>ACMMV</scope><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>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-5275-7273</orcidid></search><sort><creationdate>20201215</creationdate><title>Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses</title><author>Rennert, Lior ; Kalbaugh, Corey Andrew ; Shi, Lu ; McMahan, Christopher</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b578t-dfb26df380fa59b76b790cc48f072db3f0c27b5b7ba85d3b4a0dfc0434da88a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>College campuses</topic><topic>Colleges & universities</topic><topic>Communicable Disease Control - methods</topic><topic>Contact tracing</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 - diagnosis</topic><topic>COVID-19 - prevention & control</topic><topic>COVID-19 Testing</topic><topic>Disease Outbreaks - prevention & control</topic><topic>Disease transmission</topic><topic>Epidemics</topic><topic>health policy</topic><topic>Humans</topic><topic>infection control</topic><topic>Infections</topic><topic>Infectious Diseases</topic><topic>Mass Screening - methods</topic><topic>Models, Theoretical</topic><topic>Population</topic><topic>Public health</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>South Carolina</topic><topic>statistics & research methods</topic><topic>Students</topic><topic>Students - statistics & numerical data</topic><topic>Universities - organization & administration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rennert, Lior</creatorcontrib><creatorcontrib>Kalbaugh, Corey Andrew</creatorcontrib><creatorcontrib>Shi, Lu</creatorcontrib><creatorcontrib>McMahan, Christopher</creatorcontrib><collection>BMJ Open Access Journals</collection><collection>BMJ Journals:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Family Health</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology Journals</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMJ open</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rennert, Lior</au><au>Kalbaugh, Corey Andrew</au><au>Shi, Lu</au><au>McMahan, Christopher</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses</atitle><jtitle>BMJ open</jtitle><stitle>BMJ Open</stitle><addtitle>BMJ Open</addtitle><date>2020-12-15</date><risdate>2020</risdate><volume>10</volume><issue>12</issue><spage>e042578</spage><epage>e042578</epage><pages>e042578-e042578</pages><issn>2044-6055</issn><eissn>2044-6055</eissn><abstract>ObjectivesUniversities are exploring strategies to mitigate the spread of COVID-19 prior to reopening their campuses. National guidelines do not currently recommend testing students prior to campus arrival. However, the impact of presemester testing has not been studied.DesignDynamic SARS-CoV-2 transmission models are used to explore the effects of three presemester testing interventions.InterventionsTesting of students 0, 1 and 2 times prior to campus arrival.Primary outcomesNumber of active infections and time until isolation bed capacity is reached.SettingWe set on-campus and off-campus populations to 7500 and 17 500 students, respectively. We assumed 2% prevalence of active cases at the semester start, and that one-third of infected students will be detected and isolated throughout the semester. Isolation bed capacity was set at 500. We varied disease transmission rates (R0=1.5, 2, 3, 4) to represent the effectiveness of mitigation strategies throughout the semester.ResultsWithout presemester screening, peak number of active infections ranged from 4114 under effective mitigation strategies (R0=1.5) to 10 481 under ineffective mitigation strategies (R0=4), and exhausted isolation bed capacity within 10 (R0=4) to 25 days (R0=1.5). Mandating at least one test prior to campus arrival delayed the timing and reduced the size of the peak, while delaying the time until isolation bed capacity was reached. Testing twice in conjunction with effective mitigation strategies (R0=1.5) was the only scenario that did not exhaust isolation bed capacity during the semester.ConclusionsPresemester screening is necessary to avert early and large surges of active COVID-19 infections. Therefore, we recommend testing within 1 week prior to and on campus return. While this strategy is sufficient for delaying the timing of the peak outbreak, presemester testing would need to be implemented in conjunction with effective mitigation strategies to significantly reduce outbreak size and preserve isolation bed capacity.</abstract><cop>England</cop><pub>British Medical Journal Publishing Group</pub><pmid>33323447</pmid><doi>10.1136/bmjopen-2020-042578</doi><orcidid>https://orcid.org/0000-0001-5275-7273</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | College campuses Colleges & universities Communicable Disease Control - methods Contact tracing Coronaviruses COVID-19 COVID-19 - diagnosis COVID-19 - prevention & control COVID-19 Testing Disease Outbreaks - prevention & control Disease transmission Epidemics health policy Humans infection control Infections Infectious Diseases Mass Screening - methods Models, Theoretical Population Public health Severe acute respiratory syndrome coronavirus 2 South Carolina statistics & research methods Students Students - statistics & numerical data Universities - organization & administration |
title | Modelling the impact of presemester testing on COVID-19 outbreaks in university campuses |
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