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Refined Estimate of the Incubation Period of Severe Acute Respiratory Syndrome and Related Influencing Factors

Identifieur interne : 001299 ( Ncbi/Merge ); précédent : 001298; suivant : 001300

Refined Estimate of the Incubation Period of Severe Acute Respiratory Syndrome and Related Influencing Factors

Auteurs : Quan-Cai Cai ; Qin-Feng Xu ; Jian-Ming Xu ; Qiang Guo ; Xiang Cheng ; Gen-Ming Zhao ; Qing-Wen Sun ; Jian Lu ; Qing-Wu Jiang

Source :

RBID : PMC:7109871

Abstract

Abstract

Many epidemiologists have agreed that a refined estimate of the incubation period of severe acute respiratory syndrome (SARS) would need a sample size of about 200 cases and appropriate statistical methods enabling the inclusion of cases with defined periods of exposure. However, no such studies have been reported so far. Besides, determinants of the SARS incubation period remain unclear. In this study, 209 probable SARS cases with documented episodes of exposure between March 1 and May 31, 2003, in mainland China were included. A nonparametric method was used to analyze these data with defined periods of exposure to obtain the refined estimate of the SARS incubation period. Furthermore, the authors also explored the influence of various factors on the SARS incubation period by analysis of variance, linear regression analysis, and analysis of covariance. The estimates of mean and variance of the SARS incubation period were 5.29 days and 12.33 days2, respectively; 90% of patients would have an incubation period of less than 11.58 days with a probability of 0.8, and 99% of patients would have an incubation of less than 22.22 days with a probability of 0.9. The affected area showed a highly significant effect on the incubation period (p < 0.001), but the contact pattern, occupation, gender, and age did not.


Url:
DOI: 10.1093/aje/kwj034
PubMed: 16339050
PubMed Central: 7109871

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<p>Many epidemiologists have agreed that a refined estimate of the incubation period of severe acute respiratory syndrome (SARS) would need a sample size of about 200 cases and appropriate statistical methods enabling the inclusion of cases with defined periods of exposure. However, no such studies have been reported so far. Besides, determinants of the SARS incubation period remain unclear. In this study, 209 probable SARS cases with documented episodes of exposure between March 1 and May 31, 2003, in mainland China were included. A nonparametric method was used to analyze these data with defined periods of exposure to obtain the refined estimate of the SARS incubation period. Furthermore, the authors also explored the influence of various factors on the SARS incubation period by analysis of variance, linear regression analysis, and analysis of covariance. The estimates of mean and variance of the SARS incubation period were 5.29 days and 12.33 days
<sup>2</sup>
, respectively; 90% of patients would have an incubation period of less than 11.58 days with a probability of 0.8, and 99% of patients would have an incubation of less than 22.22 days with a probability of 0.9. The affected area showed a highly significant effect on the incubation period (
<italic>p</italic>
< 0.001), but the contact pattern, occupation, gender, and age did not.</p>
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<article-title>Refined Estimate of the Incubation Period of Severe Acute Respiratory Syndrome and Related Influencing Factors</article-title>
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<name>
<surname>Cai</surname>
<given-names>Quan-Cai</given-names>
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<name>
<surname>Xu</surname>
<given-names>Qin-Feng</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Jian-Ming</given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Guo</surname>
<given-names>Qiang</given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheng</surname>
<given-names>Xiang</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Gen-Ming</given-names>
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<contrib contrib-type="author">
<name>
<surname>Sun</surname>
<given-names>Qing-Wen</given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lu</surname>
<given-names>Jian</given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jiang</surname>
<given-names>Qing-Wu</given-names>
</name>
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<aff id="AFF1">
<label>1</label>
Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China</aff>
<aff id="AFF2">
<label>2</label>
Department of Epidemiology, Second Military Medical University, Shanghai, China</aff>
<aff id="AFF3">
<label>3</label>
Department of Statistics, Fudan University, Shanghai, China</aff>
<aff id="AFF4">
<label>4</label>
Department of Organic Chemistry, Second Military Medical University, Shanghai, China</aff>
<aff id="AFF5">
<label>5</label>
Department of Training, Second Military Medical University, Shanghai, China</aff>
<aff id="AFF6">
<label>6</label>
Department of Mathematics and Physics, Second Military Medical University, Shanghai, China</aff>
<aff id="AFF7">
<label>7</label>
Department of Statistics, Second Military Medical University, Shanghai, China</aff>
<author-notes>
<corresp id="d326996e259">Reprint requests to Dr. Qing-Wu Jiang, Department of Epidemiology, School of Public Health, Fudan University, 138 Yi Xue Yuan Road, Shanghai 200032, China (e-mail:
<email>qwjiang@shmu.edu.cn</email>
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<pub-date pub-type="epub" iso-8601-date="2005-12-07">
<day>7</day>
<month>12</month>
<year>2005</year>
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<volume>163</volume>
<issue>3</issue>
<fpage>211</fpage>
<lpage>216</lpage>
<history>
<date date-type="accepted">
<day>7</day>
<month>9</month>
<year>2005</year>
</date>
<date date-type="received">
<day>5</day>
<month>11</month>
<year>2004</year>
</date>
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<permissions>
<copyright-statement>American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.</copyright-statement>
<copyright-year>2006</copyright-year>
<license>
<license-p>This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.</license-p>
</license>
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<self-uri xlink:href="kwj034.pdf"></self-uri>
<abstract>
<title>Abstract</title>
<p>Many epidemiologists have agreed that a refined estimate of the incubation period of severe acute respiratory syndrome (SARS) would need a sample size of about 200 cases and appropriate statistical methods enabling the inclusion of cases with defined periods of exposure. However, no such studies have been reported so far. Besides, determinants of the SARS incubation period remain unclear. In this study, 209 probable SARS cases with documented episodes of exposure between March 1 and May 31, 2003, in mainland China were included. A nonparametric method was used to analyze these data with defined periods of exposure to obtain the refined estimate of the SARS incubation period. Furthermore, the authors also explored the influence of various factors on the SARS incubation period by analysis of variance, linear regression analysis, and analysis of covariance. The estimates of mean and variance of the SARS incubation period were 5.29 days and 12.33 days
<sup>2</sup>
, respectively; 90% of patients would have an incubation period of less than 11.58 days with a probability of 0.8, and 99% of patients would have an incubation of less than 22.22 days with a probability of 0.9. The affected area showed a highly significant effect on the incubation period (
<italic>p</italic>
< 0.001), but the contact pattern, occupation, gender, and age did not.</p>
</abstract>
<kwd-group kwd-group-type="KWD">
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