A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan
Identifieur interne : 000297 ( Pmc/Curation ); précédent : 000296; suivant : 000298A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan
Auteurs : Eric Hy Lau [Hong Kong] ; C Agnes Hsiung ; Benjamin J. Cowling [Hong Kong] ; Chang-Hsun Chen [Taïwan] ; Lai-Ming Ho [Hong Kong] ; Thomas Tsang [Hong Kong] ; Chiu-Wen Chang [Taïwan] ; Christl A. Donnelly ; Gabriel M. Leung [Hong Kong]Source :
- BMC Infectious Diseases [ 1471-2334 ] ; 2010.
Abstract
The 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak infected 8,422 individuals leading to 916 deaths around the world. However, there have been few epidemiological studies of SARS comparing epidemiologic features across regions. The aim of this study is to identify similarities and differences in SARS epidemiology in three populations with similar host and viral genotype.
We present a comparative epidemiologic analysis of SARS, based on an integrated dataset with 3,336 SARS patients from Hong Kong, Beijing and Taiwan, epidemiological and clinical characteristics such as incubation, onset-to-admission, onset-to-discharge and onset-to-death periods, case fatality ratios (CFRs) and presenting symptoms are described and compared between regions. We further explored the influence of demographic and clinical variables on the apparently large differences in CFRs between the three regions.
All three regions showed similar incubation periods and progressive shortening of the onset-to-admission interval through the epidemic. Adjusted for sex, health care worker status and nosocomial setting, older age was associated with a higher fatality, with adjusted odds ratio (AOR): 2.10 (95% confidence interval: 1.45, 3.04) for those aged 51-60; AOR: 4.57 (95% confidence interval: 3.32, 7.30) for those aged above 60 compared to those aged 41-50 years. Presence of pre-existing comorbid conditions was also associated with greater mortality (AOR: 1.74; 95% confidence interval: 1.36, 2.21).
The large discrepancy in crude fatality ratios across the three regions can only be partly explained by epidemiological and clinical heterogeneities. Our findings underline the importance of a common data collection platform, especially in an emerging epidemic, in order to identify and explain consistencies and differences in the eventual clinical and public health outcomes of infectious disease outbreaks, which is becoming increasingly important in our highly interconnected world.
The online version of this article (doi:10.1186/1471-2334-10-50) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/1471-2334-10-50
PubMed: 20205928
PubMed Central: 2846944
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>The 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak infected 8,422 individuals leading to 916 deaths around the world. However, there have been few epidemiological studies of SARS comparing epidemiologic features across regions. The aim of this study is to identify similarities and differences in SARS epidemiology in three populations with similar host and viral genotype.</p>
</sec>
<sec><title>Methods</title>
<p>We present a comparative epidemiologic analysis of SARS, based on an integrated dataset with 3,336 SARS patients from Hong Kong, Beijing and Taiwan, epidemiological and clinical characteristics such as incubation, onset-to-admission, onset-to-discharge and onset-to-death periods, case fatality ratios (CFRs) and presenting symptoms are described and compared between regions. We further explored the influence of demographic and clinical variables on the apparently large differences in CFRs between the three regions.</p>
</sec>
<sec><title>Results</title>
<p>All three regions showed similar incubation periods and progressive shortening of the onset-to-admission interval through the epidemic. Adjusted for sex, health care worker status and nosocomial setting, older age was associated with a higher fatality, with adjusted odds ratio (AOR): 2.10 (95% confidence interval: 1.45, 3.04) for those aged 51-60; AOR: 4.57 (95% confidence interval: 3.32, 7.30) for those aged above 60 compared to those aged 41-50 years. Presence of pre-existing comorbid conditions was also associated with greater mortality (AOR: 1.74; 95% confidence interval: 1.36, 2.21).</p>
</sec>
<sec><title>Conclusion</title>
<p>The large discrepancy in crude fatality ratios across the three regions can only be partly explained by epidemiological and clinical heterogeneities. Our findings underline the importance of a common data collection platform, especially in an emerging epidemic, in order to identify and explain consistencies and differences in the eventual clinical and public health outcomes of infectious disease outbreaks, which is becoming increasingly important in our highly interconnected world.</p>
</sec>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/1471-2334-10-50) contains supplementary material, which is available to authorized users.</p>
</sec>
</div>
</front>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Infect Dis</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Infect. Dis</journal-id>
<journal-title-group><journal-title>BMC Infectious Diseases</journal-title>
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<publisher><publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
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<article-id pub-id-type="pmc">2846944</article-id>
<article-id pub-id-type="publisher-id">1030</article-id>
<article-id pub-id-type="doi">10.1186/1471-2334-10-50</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
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<title-group><article-title>A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan</article-title>
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</contrib>
<contrib contrib-type="author"><name><surname>Tsang</surname>
<given-names>Thomas</given-names>
</name>
<address><email>thomas_tsang@dh.gov.hk</email>
</address>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chang</surname>
<given-names>Chiu-Wen</given-names>
</name>
<address><email>ccwen@cdc.gov.tw</email>
</address>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Donnelly</surname>
<given-names>Christl A</given-names>
</name>
<address><email>c.donnelly@imperial.ac.uk</email>
</address>
<xref ref-type="aff" rid="Aff5">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Leung</surname>
<given-names>Gabriel M</given-names>
</name>
<address><email>gmleung@hku.hk</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<aff id="Aff1"><label>1</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.194645.b</institution-id>
<institution-id institution-id-type="ISNI">0000000121742757</institution-id>
<institution>School of Public Health,</institution>
<institution>The University of Hong Kong,</institution>
</institution-wrap>
Pokfulam Road, Hong Kong</aff>
<aff id="Aff2"><label>2</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.59784.37</institution-id>
<institution-id institution-id-type="ISNI">0000000406229172</institution-id>
<institution>Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences,</institution>
<institution>National Health Research Institutes,</institution>
</institution-wrap>
35, Keyan Road, Zhunan, Miaoli County 35053 Taiwan</aff>
<aff id="Aff3"><label>3</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.417579.9</institution-id>
<institution-id institution-id-type="ISNI">0000000406279655</institution-id>
<institution>Second Division of Centers for Disease Control,</institution>
</institution-wrap>
No 6, Linshen South Road, Taipei, Taiwan</aff>
<aff id="Aff4"><label>4</label>
Centre for Health Protection, Department of Health, Government of the Hong Kong Special Administrative Region, 147C Argyle Street, Kowloon, Hong Kong</aff>
<aff id="Aff5"><label>5</label>
<institution-wrap><institution-id institution-id-type="GRID">grid.7445.2</institution-id>
<institution-id institution-id-type="ISNI">0000000121138111</institution-id>
<institution>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology,</institution>
<institution>Imperial College,</institution>
</institution-wrap>
St Mary's Campus, Norfolk Place, London, W2 1PG UK</aff>
</contrib-group>
<pub-date pub-type="epub"><day>6</day>
<month>3</month>
<year>2010</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>6</day>
<month>3</month>
<year>2010</year>
</pub-date>
<pub-date pub-type="collection"><year>2010</year>
</pub-date>
<volume>10</volume>
<elocation-id>50</elocation-id>
<history><date date-type="received"><day>17</day>
<month>9</month>
<year>2009</year>
</date>
<date date-type="accepted"><day>6</day>
<month>3</month>
<year>2010</year>
</date>
</history>
<permissions><copyright-statement>© Lau et al; licensee BioMed Central Ltd. 2010</copyright-statement>
<license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p>
</license>
</permissions>
<abstract id="Abs1"><sec><title>Background</title>
<p>The 2002-2003 Severe Acute Respiratory Syndrome (SARS) outbreak infected 8,422 individuals leading to 916 deaths around the world. However, there have been few epidemiological studies of SARS comparing epidemiologic features across regions. The aim of this study is to identify similarities and differences in SARS epidemiology in three populations with similar host and viral genotype.</p>
</sec>
<sec><title>Methods</title>
<p>We present a comparative epidemiologic analysis of SARS, based on an integrated dataset with 3,336 SARS patients from Hong Kong, Beijing and Taiwan, epidemiological and clinical characteristics such as incubation, onset-to-admission, onset-to-discharge and onset-to-death periods, case fatality ratios (CFRs) and presenting symptoms are described and compared between regions. We further explored the influence of demographic and clinical variables on the apparently large differences in CFRs between the three regions.</p>
</sec>
<sec><title>Results</title>
<p>All three regions showed similar incubation periods and progressive shortening of the onset-to-admission interval through the epidemic. Adjusted for sex, health care worker status and nosocomial setting, older age was associated with a higher fatality, with adjusted odds ratio (AOR): 2.10 (95% confidence interval: 1.45, 3.04) for those aged 51-60; AOR: 4.57 (95% confidence interval: 3.32, 7.30) for those aged above 60 compared to those aged 41-50 years. Presence of pre-existing comorbid conditions was also associated with greater mortality (AOR: 1.74; 95% confidence interval: 1.36, 2.21).</p>
</sec>
<sec><title>Conclusion</title>
<p>The large discrepancy in crude fatality ratios across the three regions can only be partly explained by epidemiological and clinical heterogeneities. Our findings underline the importance of a common data collection platform, especially in an emerging epidemic, in order to identify and explain consistencies and differences in the eventual clinical and public health outcomes of infectious disease outbreaks, which is becoming increasingly important in our highly interconnected world.</p>
</sec>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/1471-2334-10-50) contains supplementary material, which is available to authorized users.</p>
</sec>
</abstract>
<kwd-group xml:lang="en"><title>Keywords</title>
<kwd>Severe Acute Respiratory Syndrome</kwd>
<kwd>Probable Case</kwd>
<kwd>Severe Acute Respiratory Syndrome</kwd>
<kwd>Fatality Ratio</kwd>
<kwd>Severe Acute Respiratory Syndrome Patient</kwd>
</kwd-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2010</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
</record>
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