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A comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan

Identifieur interne : 000A75 ( 2020/Analysis ); précédent : 000A74; suivant : 000A76

A 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 :

RBID : PMC:2846944

Abstract

Background

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.

Methods

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.

Results

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).

Conclusion

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.

Electronic supplementary material

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


Affiliations:


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PMC:2846944

Le document en format XML

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<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>
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<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>
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<p>The online version of this article (doi:10.1186/1471-2334-10-50) contains supplementary material, which is available to authorized users.</p>
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<name sortKey="Mclaws, Ml" uniqKey="Mclaws M">ML McLaws</name>
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<name sortKey="Liu, M" uniqKey="Liu M">M Liu</name>
</author>
<author>
<name sortKey="Mi, J" uniqKey="Mi J">J Mi</name>
</author>
<author>
<name sortKey="Chan, Dk" uniqKey="Chan D">DK Chan</name>
</author>
</analytic>
</biblStruct>
<biblStruct>
<analytic>
<author>
<name sortKey="Leung, Gm" uniqKey="Leung G">GM Leung</name>
</author>
<author>
<name sortKey="Lim, Ww" uniqKey="Lim W">WW Lim</name>
</author>
<author>
<name sortKey="Ho, Lm" uniqKey="Ho L">LM Ho</name>
</author>
<author>
<name sortKey="Lam, Th" uniqKey="Lam T">TH Lam</name>
</author>
<author>
<name sortKey="Ghani, Ac" uniqKey="Ghani A">AC Ghani</name>
</author>
<author>
<name sortKey="Donnelly, Ca" uniqKey="Donnelly C">CA Donnelly</name>
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<name sortKey="Anderson, Rm" uniqKey="Anderson R">RM Anderson</name>
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<list>
<country>
<li>Hong Kong</li>
<li>Taïwan</li>
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</list>
<tree>
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<name sortKey="Donnelly, Christl A" sort="Donnelly, Christl A" uniqKey="Donnelly C" first="Christl A" last="Donnelly">Christl A. Donnelly</name>
<name sortKey="Hsiung, C Agnes" sort="Hsiung, C Agnes" uniqKey="Hsiung C" first="C Agnes" last="Hsiung">C Agnes Hsiung</name>
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<name sortKey="Lau, Eric Hy" sort="Lau, Eric Hy" uniqKey="Lau E" first="Eric Hy" last="Lau">Eric Hy Lau</name>
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<name sortKey="Cowling, Benjamin J" sort="Cowling, Benjamin J" uniqKey="Cowling B" first="Benjamin J" last="Cowling">Benjamin J. Cowling</name>
<name sortKey="Ho, Lai Ming" sort="Ho, Lai Ming" uniqKey="Ho L" first="Lai-Ming" last="Ho">Lai-Ming Ho</name>
<name sortKey="Leung, Gabriel M" sort="Leung, Gabriel M" uniqKey="Leung G" first="Gabriel M" last="Leung">Gabriel M. Leung</name>
<name sortKey="Tsang, Thomas" sort="Tsang, Thomas" uniqKey="Tsang T" first="Thomas" last="Tsang">Thomas Tsang</name>
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<name sortKey="Chen, Chang Hsun" sort="Chen, Chang Hsun" uniqKey="Chen C" first="Chang-Hsun" last="Chen">Chang-Hsun Chen</name>
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<name sortKey="Chang, Chiu Wen" sort="Chang, Chiu Wen" uniqKey="Chang C" first="Chiu-Wen" last="Chang">Chiu-Wen Chang</name>
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