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Article: Spatial distribution of infection risk of SARS transmission in a hospital ward
Title | Spatial distribution of infection risk of SARS transmission in a hospital ward | ||||||||
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Authors | |||||||||
Keywords | Airborne transmission of diseases CFD SARS Wells-Riley equation | ||||||||
Issue Date | 2009 | ||||||||
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/buildenv | ||||||||
Citation | Building And Environment, 2009, v. 44 n. 8, p. 1651-1658 How to Cite? | ||||||||
Abstract | The classical Wells-Riley model for predicting risk of airborne transmission of diseases assumes a uniform spatial distribution of the infected cases in an enclosed space. A new mathematical model is developed here for predicting the spatial distribution of infection risk of airborne transmitted diseases by integrating the Wells-Riley equation into computational fluid dynamics. We applied our new integrated model to analyze a large nosocomial SARS outbreak in Hong Kong during the 2003 SARS epidemics, which was studied in the literature with regard to the association between airflow and SARS infection. The predicted numbers of infected cases of medical students in the same cubicle, the adjacent cubicle and the distant cubicle were 6.39, 0.78 and 0.2 respectively while the observed numbers of infected medical students in the three cubicles were 7, 0 and 0 respectively during the morning of March 6th, which was the highest attack period. The predicted numbers of infected cases of inpatients during the morning of March 6th in the same cubicle, the adjacent cubic and the distance cubicle were 7.8, 5.1, and 4.8 respectively which also agree well with the observed distribution of the infected inpatients during the entire infection period. The new developed model provides a new modelling tool for investigating the airborne transmission of diseases in enclosed spaces. The model is applicable when the susceptible stays mostly at the same location in an enclosed space during the infectious period, such as inpatients in a hospital ward, passengers in an airplane etc. © 2008 Elsevier Ltd. All rights reserved. | ||||||||
Persistent Identifier | http://hdl.handle.net/10722/59086 | ||||||||
ISSN | 2023 Impact Factor: 7.1 2023 SCImago Journal Rankings: 1.647 | ||||||||
ISI Accession Number ID |
Funding Information: The work described in this paper was jointly supported by a grant from the Research Grants Council of the Hong Kong SAR Government (Project No. HKU 7115/04E), a Hospital authority-commissioned project under the Research Fund for the Control of Infectious Diseases (RFCID) by the Health, Welfare and Food Bureau of Hong Kong SAR government (Project No. HA-NS-002), and the Research Grants from National Nature and Science Foundation of China (NSFC) (Project No. 50808038). | ||||||||
References | |||||||||
Grants |
DC Field | Value | Language |
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dc.contributor.author | Qian, H | en_HK |
dc.contributor.author | Li, Y | en_HK |
dc.contributor.author | Nielsen, PV | en_HK |
dc.contributor.author | Huang, X | en_HK |
dc.date.accessioned | 2010-05-31T03:42:38Z | - |
dc.date.available | 2010-05-31T03:42:38Z | - |
dc.date.issued | 2009 | en_HK |
dc.identifier.citation | Building And Environment, 2009, v. 44 n. 8, p. 1651-1658 | en_HK |
dc.identifier.issn | 0360-1323 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/59086 | - |
dc.description.abstract | The classical Wells-Riley model for predicting risk of airborne transmission of diseases assumes a uniform spatial distribution of the infected cases in an enclosed space. A new mathematical model is developed here for predicting the spatial distribution of infection risk of airborne transmitted diseases by integrating the Wells-Riley equation into computational fluid dynamics. We applied our new integrated model to analyze a large nosocomial SARS outbreak in Hong Kong during the 2003 SARS epidemics, which was studied in the literature with regard to the association between airflow and SARS infection. The predicted numbers of infected cases of medical students in the same cubicle, the adjacent cubicle and the distant cubicle were 6.39, 0.78 and 0.2 respectively while the observed numbers of infected medical students in the three cubicles were 7, 0 and 0 respectively during the morning of March 6th, which was the highest attack period. The predicted numbers of infected cases of inpatients during the morning of March 6th in the same cubicle, the adjacent cubic and the distance cubicle were 7.8, 5.1, and 4.8 respectively which also agree well with the observed distribution of the infected inpatients during the entire infection period. The new developed model provides a new modelling tool for investigating the airborne transmission of diseases in enclosed spaces. The model is applicable when the susceptible stays mostly at the same location in an enclosed space during the infectious period, such as inpatients in a hospital ward, passengers in an airplane etc. © 2008 Elsevier Ltd. All rights reserved. | en_HK |
dc.language | eng | en_HK |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/buildenv | en_HK |
dc.relation.ispartof | Building and Environment | en_HK |
dc.subject | Airborne transmission of diseases | en_HK |
dc.subject | CFD | en_HK |
dc.subject | SARS | en_HK |
dc.subject | Wells-Riley equation | en_HK |
dc.title | Spatial distribution of infection risk of SARS transmission in a hospital ward | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0360-1323&volume=44&issue=8&spage=1651&epage=1658&date=2009&atitle=Spatial+distribution+of+infection+risk+of+SARS+transmission+in+a+hospital+ward | en_HK |
dc.identifier.email | Li, Y:liyg@hkucc.hku.hk | en_HK |
dc.identifier.authority | Li, Y=rp00151 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.buildenv.2008.11.002 | en_HK |
dc.identifier.scopus | eid_2-s2.0-61749095805 | en_HK |
dc.identifier.hkuros | 161291 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-61749095805&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 44 | en_HK |
dc.identifier.issue | 8 | en_HK |
dc.identifier.spage | 1651 | en_HK |
dc.identifier.epage | 1658 | en_HK |
dc.identifier.isi | WOS:000265171300012 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.relation.project | Understanding droplets due to the use of nebulizers and respiratory activities | - |
dc.relation.project | Dispersion and ventilation control of exhalation pollutants in hospital wards | - |
dc.identifier.scopusauthorid | Qian, H=36091859600 | en_HK |
dc.identifier.scopusauthorid | Li, Y=7502094052 | en_HK |
dc.identifier.scopusauthorid | Nielsen, PV=24773772900 | en_HK |
dc.identifier.scopusauthorid | Huang, X=16042364900 | en_HK |
dc.identifier.issnl | 0360-1323 | - |