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Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data

Identifieur interne : 000C65 ( Main/Exploration ); précédent : 000C64; suivant : 000C66

Estimating Infection Attack Rates and Severity in Real Time during an Influenza Pandemic: Analysis of Serial Cross-Sectional Serologic Surveillance Data

Auteurs : Joseph T. Wu [République populaire de Chine] ; Andrew Ho [République populaire de Chine] ; Edward S. K. Ma [République populaire de Chine] ; Cheuk Kwong Lee [République populaire de Chine] ; Daniel K. W. Chu [République populaire de Chine] ; Po-Lai Ho [République populaire de Chine] ; Ivan F. N. Hung [République populaire de Chine] ; Lai Ming Ho [République populaire de Chine] ; Che Kit Lin [République populaire de Chine] ; Thomas Tsang [République populaire de Chine] ; Su-Vui Lo [République populaire de Chine] ; Yu-Lung Lau [République populaire de Chine] ; Gabriel M. Leung [République populaire de Chine] ; Benjamin J. Cowling [République populaire de Chine] ; J. S. Malik Peiris [République populaire de Chine]

Source :

RBID : PMC:3186812

Abstract

This study reports that using serological data coupled with clinical surveillance data can provide real-time estimates of the infection attack rates and severity in an emerging influenza pandemic.


Url:
DOI: 10.1371/journal.pmed.1001103
PubMed: 21990967
PubMed Central: 3186812


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region</wicri:regionArea>
<wicri:noRegion>Hong Kong Special Administrative Region</wicri:noRegion>
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<affiliation wicri:level="1">
<nlm:aff id="aff9">
<addr-line>HKU-Pasteur Research Center, Hong Kong Special Administrative Region, People's Republic of China</addr-line>
</nlm:aff>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>HKU-Pasteur Research Center, Hong Kong Special Administrative Region</wicri:regionArea>
<wicri:noRegion>Hong Kong Special Administrative Region</wicri:noRegion>
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</author>
</analytic>
<series>
<title level="j">PLoS Medicine</title>
<idno type="ISSN">1549-1277</idno>
<idno type="eISSN">1549-1676</idno>
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<date when="2011">2011</date>
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</fileDesc>
<profileDesc>
<textClass></textClass>
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</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<p>This study reports that using serological data coupled with clinical surveillance data can provide real-time estimates of the infection attack rates and severity in an emerging influenza pandemic.</p>
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