Article: Understanding the spatial clustering of severe acute respiratory syndrome (SARS) in Hong Kong
| Title | Understanding the spatial clustering of severe acute respiratory syndrome (SARS) in Hong Kong |
|---|---|
| Authors | Lai, PC2 Wong, CM2 Hedley, AJ2 Lo, SV3 Leung, PY Kong, J1 Leung, GM2 |
| Keywords | Geographic information systems GIS SARS Severe acute respiratory syndrome Spatial distribution |
| Issue Date | 2004 |
| Publisher | US Department of Health and Human Services, National Institute of Environmental Health Sciences. The Journal's web site is located at http://ehp.niehs.nih.gov/ |
| Citation | Environmental Health Perspectives, 2004, v. 112 n. 15, p. 1550-1556 [How to Cite?] DOI: http://dx.doi.org/10.1289/ehp.7117 |
| Abstract | We applied cartographic and geostatistical methods in analyzing the patterns of disease spread during the 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong using geographic information system (GIS) technology. We analyzed an integrated database that contained clinical and personal details on all 1,755 patients confirmed to have SARS from 15 February to 22 June 2003. Elementary mapping of disease occurrences in space and time simultaneously revealed the geographic extent of spread throughout the territory. Statistical surfaces created by the kernel method confirmed that SARS cases were highly clustered and identified distinct disease "hot spots." Contextual analysis of mean and standard deviation of different density classes indicated that the period from day 1 (18 February) through day 16 (6 March) was the prodrome of the epidemic, whereas days 86 (15 May) to 106 (4 June) marked the declining phase of the outbreak. Origin-and-destination plots showed the directional bias and radius of spread of superspreading events. Integration of GIS technology into routine field epidemiologic surveillance can offer a real-time quantitative method for identifying and tracking the geospatial spread of infectious diseases, as our experience with SARS has demonstrated. |
| ISSN | 0091-6765 2011 Impact Factor: 7.036 2011 SCImago Journal Rankings: 0.373 |
| DOI | http://dx.doi.org/10.1289/ehp.7117 |
| ISI Accession Number ID | WOS:000224972500044 |
| PubMed Central ID | PMC1247620 |
| References | References in Scopus |
| dc.contributor.author | Lai, PC |
|---|---|
| dc.contributor.author | Wong, CM |
| dc.contributor.author | Hedley, AJ |
| dc.contributor.author | Lo, SV |
| dc.contributor.author | Leung, PY |
| dc.contributor.author | Kong, J |
| dc.contributor.author | Leung, GM |
| dc.date.accessioned | 2008-06-12T06:40:53Z |
| dc.date.available | 2008-06-12T06:40:53Z |
| dc.date.issued | 2004 |
| dc.description.abstract | We applied cartographic and geostatistical methods in analyzing the patterns of disease spread during the 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong using geographic information system (GIS) technology. We analyzed an integrated database that contained clinical and personal details on all 1,755 patients confirmed to have SARS from 15 February to 22 June 2003. Elementary mapping of disease occurrences in space and time simultaneously revealed the geographic extent of spread throughout the territory. Statistical surfaces created by the kernel method confirmed that SARS cases were highly clustered and identified distinct disease "hot spots." Contextual analysis of mean and standard deviation of different density classes indicated that the period from day 1 (18 February) through day 16 (6 March) was the prodrome of the epidemic, whereas days 86 (15 May) to 106 (4 June) marked the declining phase of the outbreak. Origin-and-destination plots showed the directional bias and radius of spread of superspreading events. Integration of GIS technology into routine field epidemiologic surveillance can offer a real-time quantitative method for identifying and tracking the geospatial spread of infectious diseases, as our experience with SARS has demonstrated. |
| dc.description.nature | published_or_final_version |
| dc.format.extent | 388 bytes |
| dc.format.mimetype | text/html |
| dc.identifier.citation | Environmental Health Perspectives, 2004, v. 112 n. 15, p. 1550-1556 [How to Cite?] DOI: http://dx.doi.org/10.1289/ehp.7117 |
| dc.identifier.doi | http://dx.doi.org/10.1289/ehp.7117 |
| dc.identifier.epage | 1556 |
| dc.identifier.hkuros | 92402 |
| dc.identifier.isi | WOS:000224972500044 |
| dc.identifier.issn | 0091-6765 2011 Impact Factor: 7.036 2011 SCImago Journal Rankings: 0.373 |
| dc.identifier.issue | 15 |
| dc.identifier.openurl | ![]() |
| dc.identifier.pmcid | PMC1247620 |
| dc.identifier.pmid | 15531441 |
| dc.identifier.scopus | eid_2-s2.0-7244259666 |
| dc.identifier.spage | 1550 |
| dc.identifier.uri | http://hdl.handle.net/10722/49379 |
| dc.identifier.volume | 112 |
| dc.language | eng |
| dc.publisher | US Department of Health and Human Services, National Institute of Environmental Health Sciences. The Journal's web site is located at http://ehp.niehs.nih.gov/ |
| dc.publisher.place | United States |
| dc.relation.ispartof | Environmental Health Perspectives |
| dc.relation.references | References in Scopus |
| dc.rights | Creative Commons: Attribution 3.0 Hong Kong License |
| dc.subject.mesh | Disease Outbreaks |
| dc.subject.mesh | Geographic Information Systems |
| dc.subject.mesh | Population Surveillance |
| dc.subject.mesh | Severe Acute Respiratory Syndrome - epidemiology |
| dc.subject.mesh | Databases, Factual |
| dc.subject | Geographic information systems |
| dc.subject | GIS |
| dc.subject | SARS |
| dc.subject | Severe acute respiratory syndrome |
| dc.subject | Spatial distribution |
| dc.title | Understanding the spatial clustering of severe acute respiratory syndrome (SARS) in Hong Kong |
| dc.type | Article |
Author Affiliations
- Hong Kong Hospital Authority
- The University of Hong Kong
- Food and Health Bureau


