A mathematical model of COVID-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies
Novel coronavirus (named SARS-CoV-2) can spread widely in confined settings including hospitals, cruise ships, prisons, and places of worship. In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of dif...
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| Veröffentlicht in: | PloS one 2020-10, Vol.15 (10), p.e0241169-e0241169 |
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| creator | Baek, Yae Jee Lee, Taeyong Cho, Yunsuk Hyun, Jong Hoon Kim, Moo Hyun Sohn, Yujin Kim, Jung Ho Ahn, Jin Young Jeong, Su Jin Ku, Nam Su Yeom, Joon-Sup Lee, Jeehyun Choi, Jun Yong |
| description | Novel coronavirus (named SARS-CoV-2) can spread widely in confined settings including hospitals, cruise ships, prisons, and places of worship. In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak. |
| doi_str_mv | 10.1371/journal.pone.0241169 |
| format | Article |
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In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0241169</identifier><identifier>PMID: 33104736</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aerosols ; Asymptomatic ; Betacoronavirus ; Caregivers ; China ; Clinical Laboratory Techniques ; Control ; Coronaviridae ; Coronavirus Infections - diagnosis ; Coronavirus Infections - epidemiology ; Coronavirus Infections - prevention & control ; Coronavirus Infections - transmission ; Coronaviruses ; COVID-19 ; COVID-19 Testing ; Cross Infection - epidemiology ; Cross Infection - prevention & control ; Cross Infection - transmission ; Cruise ships ; Departments ; Disease transmission ; Distribution ; Early Diagnosis ; Emergency medical care ; Emergency medical services ; Emergency Service, Hospital ; Engineering and Technology ; Epidemics ; Evaluation ; Health care ; Hospital Departments ; Hospitals ; Humans ; Incidence ; Infection Control - methods ; Infections ; Internal medicine ; Mass Screening ; Mathematical analysis ; Mathematical models ; Medical equipment ; Medical personnel ; Medical schools ; Medical Staff, Hospital ; Medicine ; Medicine and Health Sciences ; Models, Theoretical ; Nurses ; Nursing Staff, Hospital ; Outbreaks ; Outpatient Clinics, Hospital ; Pandemics - prevention & control ; Patients ; Patients' Rooms ; People and Places ; Personal Protective Equipment ; Physicians ; Pneumonia, Viral - epidemiology ; Pneumonia, Viral - prevention & control ; Pneumonia, Viral - transmission ; Prisons ; Protective equipment ; Quarantine ; Republic of Korea - epidemiology ; SARS-CoV-2 ; Sensitivity and Specificity ; Severe acute respiratory syndrome coronavirus 2 ; Ships ; Symptom Assessment ; Tertiary Care Centers ; Viral diseases ; Visitors to Patients</subject><ispartof>PloS one, 2020-10, Vol.15 (10), p.e0241169-e0241169</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Baek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak.</description><subject>Aerosols</subject><subject>Asymptomatic</subject><subject>Betacoronavirus</subject><subject>Caregivers</subject><subject>China</subject><subject>Clinical Laboratory Techniques</subject><subject>Control</subject><subject>Coronaviridae</subject><subject>Coronavirus Infections - diagnosis</subject><subject>Coronavirus Infections - epidemiology</subject><subject>Coronavirus Infections - prevention & control</subject><subject>Coronavirus Infections - transmission</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 Testing</subject><subject>Cross Infection - epidemiology</subject><subject>Cross Infection - prevention & control</subject><subject>Cross Infection - transmission</subject><subject>Cruise ships</subject><subject>Departments</subject><subject>Disease transmission</subject><subject>Distribution</subject><subject>Early Diagnosis</subject><subject>Emergency medical care</subject><subject>Emergency medical services</subject><subject>Emergency Service, Hospital</subject><subject>Engineering and Technology</subject><subject>Epidemics</subject><subject>Evaluation</subject><subject>Health care</subject><subject>Hospital Departments</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Incidence</subject><subject>Infection Control - methods</subject><subject>Infections</subject><subject>Internal medicine</subject><subject>Mass Screening</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Medical equipment</subject><subject>Medical personnel</subject><subject>Medical schools</subject><subject>Medical Staff, Hospital</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Models, Theoretical</subject><subject>Nurses</subject><subject>Nursing Staff, Hospital</subject><subject>Outbreaks</subject><subject>Outpatient Clinics, Hospital</subject><subject>Pandemics - prevention & control</subject><subject>Patients</subject><subject>Patients' Rooms</subject><subject>People and Places</subject><subject>Personal Protective Equipment</subject><subject>Physicians</subject><subject>Pneumonia, Viral - epidemiology</subject><subject>Pneumonia, Viral - prevention & control</subject><subject>Pneumonia, Viral - transmission</subject><subject>Prisons</subject><subject>Protective equipment</subject><subject>Quarantine</subject><subject>Republic of Korea - epidemiology</subject><subject>SARS-CoV-2</subject><subject>Sensitivity and Specificity</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Ships</subject><subject>Symptom Assessment</subject><subject>Tertiary Care Centers</subject><subject>Viral diseases</subject><subject>Visitors to Patients</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9uK2zAQhk1p6W63fYPSGgqlvUiqk-X4phDSU2Ah0MPeirE0ThRsK2vJS_sEfe3KjXeJy14Ugz2Svv-XZ6RJkueUzCnP6bu967sW6vnBtTgnTFAqiwfJOS04m0lG-MOT-Cx54v2ekIwvpHycnHFOici5PE9-L9MGwg7jy2qo08YZrFNXpavN1frDjBZp6KD1jfXeuja1bQppwC5Y6H6lO-cPNkQVtCYF79H7BtswyKNlilWFOvhhaGyMu2HNtlF-E6PBzkfzgFuL_mnyqILa47Pxe5H8-PTx--rL7HLzeb1aXs60LFiYLUqDktM8N9qIEg0rM01yrrWkVUYoQVMKalAIUwIhXFImoQLNq5wRAYLwi-Tl0fdQO6_GGnrFRCZ4schyGYn1kTAO9urQ2SamqhxY9XfCdVsFMX9doxLGaFFIKCuZC11wkLLM2AIIakII5tHr_bhbXzZodEy7g3piOl1p7U5t3Y3Ks8WCZCwavBkNOnfdow8qnoTGuoYWXX_8b5lxKgf01T_o_dmN1BZiAratXNxXD6ZqKXmRMcoYjdT8Hio-Bhur44WrbJyfCN5OBJEJ-DNsofderb99_X92czVlX5-wO4Q67Lyr--H2-CkojqDunPcdVndFpkQN_XJbDTX0ixr7JcpenB7Qnei2QfgfK_URwA</recordid><startdate>20201026</startdate><enddate>20201026</enddate><creator>Baek, Yae Jee</creator><creator>Lee, Taeyong</creator><creator>Cho, Yunsuk</creator><creator>Hyun, Jong Hoon</creator><creator>Kim, Moo Hyun</creator><creator>Sohn, Yujin</creator><creator>Kim, Jung Ho</creator><creator>Ahn, Jin Young</creator><creator>Jeong, Su Jin</creator><creator>Ku, Nam Su</creator><creator>Yeom, Joon-Sup</creator><creator>Lee, Jeehyun</creator><creator>Choi, Jun Yong</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8940-7170</orcidid><orcidid>https://orcid.org/0000-0002-9717-4327</orcidid><orcidid>https://orcid.org/0000-0002-2775-3315</orcidid><orcidid>https://orcid.org/0000-0002-1940-0210</orcidid></search><sort><creationdate>20201026</creationdate><title>A mathematical model of COVID-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies</title><author>Baek, Yae Jee ; Lee, Taeyong ; Cho, Yunsuk ; Hyun, Jong Hoon ; Kim, Moo Hyun ; Sohn, Yujin ; Kim, Jung Ho ; Ahn, Jin Young ; Jeong, Su Jin ; Ku, Nam Su ; Yeom, Joon-Sup ; Lee, Jeehyun ; Choi, Jun Yong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-8bde63177dcd4bed2b5c073cc61f5010edb41de44dba0036126afac3f7204a403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aerosols</topic><topic>Asymptomatic</topic><topic>Betacoronavirus</topic><topic>Caregivers</topic><topic>China</topic><topic>Clinical Laboratory Techniques</topic><topic>Control</topic><topic>Coronaviridae</topic><topic>Coronavirus Infections - 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prevention & control</topic><topic>Patients</topic><topic>Patients' Rooms</topic><topic>People and Places</topic><topic>Personal Protective Equipment</topic><topic>Physicians</topic><topic>Pneumonia, Viral - epidemiology</topic><topic>Pneumonia, Viral - prevention & control</topic><topic>Pneumonia, Viral - transmission</topic><topic>Prisons</topic><topic>Protective equipment</topic><topic>Quarantine</topic><topic>Republic of Korea - epidemiology</topic><topic>SARS-CoV-2</topic><topic>Sensitivity and Specificity</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Ships</topic><topic>Symptom Assessment</topic><topic>Tertiary Care Centers</topic><topic>Viral diseases</topic><topic>Visitors to Patients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Baek, Yae Jee</creatorcontrib><creatorcontrib>Lee, Taeyong</creatorcontrib><creatorcontrib>Cho, Yunsuk</creatorcontrib><creatorcontrib>Hyun, Jong Hoon</creatorcontrib><creatorcontrib>Kim, Moo Hyun</creatorcontrib><creatorcontrib>Sohn, Yujin</creatorcontrib><creatorcontrib>Kim, Jung Ho</creatorcontrib><creatorcontrib>Ahn, Jin Young</creatorcontrib><creatorcontrib>Jeong, Su Jin</creatorcontrib><creatorcontrib>Ku, Nam Su</creatorcontrib><creatorcontrib>Yeom, Joon-Sup</creatorcontrib><creatorcontrib>Lee, Jeehyun</creatorcontrib><creatorcontrib>Choi, Jun Yong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Baek, Yae Jee</au><au>Lee, Taeyong</au><au>Cho, Yunsuk</au><au>Hyun, Jong Hoon</au><au>Kim, Moo Hyun</au><au>Sohn, Yujin</au><au>Kim, Jung Ho</au><au>Ahn, Jin Young</au><au>Jeong, Su Jin</au><au>Ku, Nam Su</au><au>Yeom, Joon-Sup</au><au>Lee, Jeehyun</au><au>Choi, Jun Yong</au><au>Lazzeri, Chiara</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A mathematical model of COVID-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-10-26</date><risdate>2020</risdate><volume>15</volume><issue>10</issue><spage>e0241169</spage><epage>e0241169</epage><pages>e0241169-e0241169</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Novel coronavirus (named SARS-CoV-2) can spread widely in confined settings including hospitals, cruise ships, prisons, and places of worship. In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33104736</pmid><doi>10.1371/journal.pone.0241169</doi><tpages>e0241169</tpages><orcidid>https://orcid.org/0000-0001-8940-7170</orcidid><orcidid>https://orcid.org/0000-0002-9717-4327</orcidid><orcidid>https://orcid.org/0000-0002-2775-3315</orcidid><orcidid>https://orcid.org/0000-0002-1940-0210</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2020-10, Vol.15 (10), p.e0241169-e0241169 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2454398576 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Aerosols Asymptomatic Betacoronavirus Caregivers China Clinical Laboratory Techniques Control Coronaviridae Coronavirus Infections - diagnosis Coronavirus Infections - epidemiology Coronavirus Infections - prevention & control Coronavirus Infections - transmission Coronaviruses COVID-19 COVID-19 Testing Cross Infection - epidemiology Cross Infection - prevention & control Cross Infection - transmission Cruise ships Departments Disease transmission Distribution Early Diagnosis Emergency medical care Emergency medical services Emergency Service, Hospital Engineering and Technology Epidemics Evaluation Health care Hospital Departments Hospitals Humans Incidence Infection Control - methods Infections Internal medicine Mass Screening Mathematical analysis Mathematical models Medical equipment Medical personnel Medical schools Medical Staff, Hospital Medicine Medicine and Health Sciences Models, Theoretical Nurses Nursing Staff, Hospital Outbreaks Outpatient Clinics, Hospital Pandemics - prevention & control Patients Patients' Rooms People and Places Personal Protective Equipment Physicians Pneumonia, Viral - epidemiology Pneumonia, Viral - prevention & control Pneumonia, Viral - transmission Prisons Protective equipment Quarantine Republic of Korea - epidemiology SARS-CoV-2 Sensitivity and Specificity Severe acute respiratory syndrome coronavirus 2 Ships Symptom Assessment Tertiary Care Centers Viral diseases Visitors to Patients |
| title | A mathematical model of COVID-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies |
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