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Article: Spatial distribution of infection risk of SARS transmission in a hospital ward

TitleSpatial distribution of infection risk of SARS transmission in a hospital ward
Authors
KeywordsAirborne transmission of diseases
CFD
SARS
Wells-Riley equation
Issue Date2009
PublisherPergamon. 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?
AbstractThe 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 Identifierhttp://hdl.handle.net/10722/59086
ISSN
2022 Impact Factor: 7.4
2020 SCImago Journal Rankings: 1.736
ISI Accession Number ID
Funding AgencyGrant Number
Research Grants Council of the Hong Kong SAR GovernmentHKU 7115/04E
Health, Welfare and Food Bureau of Hong KongHA-NS-002
National Nature and Science Foundation of China (NSFC)50808038
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 FieldValueLanguage
dc.contributor.authorQian, Hen_HK
dc.contributor.authorLi, Yen_HK
dc.contributor.authorNielsen, PVen_HK
dc.contributor.authorHuang, Xen_HK
dc.date.accessioned2010-05-31T03:42:38Z-
dc.date.available2010-05-31T03:42:38Z-
dc.date.issued2009en_HK
dc.identifier.citationBuilding And Environment, 2009, v. 44 n. 8, p. 1651-1658en_HK
dc.identifier.issn0360-1323en_HK
dc.identifier.urihttp://hdl.handle.net/10722/59086-
dc.description.abstractThe 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.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/buildenven_HK
dc.relation.ispartofBuilding and Environmenten_HK
dc.subjectAirborne transmission of diseasesen_HK
dc.subjectCFDen_HK
dc.subjectSARSen_HK
dc.subjectWells-Riley equationen_HK
dc.titleSpatial distribution of infection risk of SARS transmission in a hospital warden_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://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+warden_HK
dc.identifier.emailLi, Y:liyg@hkucc.hku.hken_HK
dc.identifier.authorityLi, Y=rp00151en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.buildenv.2008.11.002en_HK
dc.identifier.scopuseid_2-s2.0-61749095805en_HK
dc.identifier.hkuros161291en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-61749095805&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume44en_HK
dc.identifier.issue8en_HK
dc.identifier.spage1651en_HK
dc.identifier.epage1658en_HK
dc.identifier.isiWOS:000265171300012-
dc.publisher.placeUnited Kingdomen_HK
dc.relation.projectUnderstanding droplets due to the use of nebulizers and respiratory activities-
dc.relation.projectDispersion and ventilation control of exhalation pollutants in hospital wards-
dc.identifier.scopusauthoridQian, H=36091859600en_HK
dc.identifier.scopusauthoridLi, Y=7502094052en_HK
dc.identifier.scopusauthoridNielsen, PV=24773772900en_HK
dc.identifier.scopusauthoridHuang, X=16042364900en_HK
dc.identifier.issnl0360-1323-

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