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Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong
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...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
National Institue of Environmental Health Sciences
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1247620/ https://www.ncbi.nlm.nih.gov/pubmed/15531441 http://dx.doi.org/10.1289/ehp.7117 |
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author | Lai, P.C. Wong, C.M. Hedley, A.J. Lo, S.V. Leung, P.Y. Kong, J. Leung, G.M. |
author_facet | Lai, P.C. Wong, C.M. Hedley, A.J. Lo, S.V. Leung, P.Y. Kong, J. Leung, G.M. |
author_sort | Lai, P.C. |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-1247620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | National Institue of Environmental Health Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-12476202005-11-08 Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong Lai, P.C. Wong, C.M. Hedley, A.J. Lo, S.V. Leung, P.Y. Kong, J. Leung, G.M. Environ Health Perspect Research 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. National Institue of Environmental Health Sciences 2004-11 2004-07-27 /pmc/articles/PMC1247620/ /pubmed/15531441 http://dx.doi.org/10.1289/ehp.7117 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Research Lai, P.C. Wong, C.M. Hedley, A.J. Lo, S.V. Leung, P.Y. Kong, J. Leung, G.M. 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 |
title_full | Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong |
title_fullStr | Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong |
title_full_unstemmed | Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong |
title_short | Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong |
title_sort | understanding the spatial clustering of severe acute respiratory syndrome (sars) in hong kong |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1247620/ https://www.ncbi.nlm.nih.gov/pubmed/15531441 http://dx.doi.org/10.1289/ehp.7117 |
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