Real‐time epidemiology
Identifieur interne : 003F83 ( Ncbi/Merge ); précédent : 003F82; suivant : 003F84Real‐time epidemiology
Auteurs : Christl Donnelly ; Azra GhaniSource :
- Significance (Oxford, England) [ 1740-9705 ] ; 2004.
Abstract
Fitting transmission models to outbreak data allows key epidemiological parameters to be estimated and the impact of control measures to be evaluated.
Url:
DOI: 10.1111/j.1740-9713.2004.00066.x
PubMed: NONE
PubMed Central: 7169536
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PMC:7169536Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Fitting transmission models to outbreak data allows key epidemiological parameters to be estimated and the impact of control measures to be evaluated. <bold>Christl Donnelly</bold>
and <bold>Azra Ghani</bold>
describe the use of such models in the 2003 SARS epidemic in Hong Kong.</p>
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<title-group><article-title>Real‐time epidemiology</article-title>
<subtitle>Understanding the spread of SARS</subtitle>
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<pub-date pub-type="ppub"><month>12</month>
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<volume>1</volume>
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<fpage>176</fpage>
<lpage>179</lpage>
<permissions><pmc-comment> © 2004 The Royal Statistical Society </pmc-comment>
<copyright-statement content-type="article-copyright">© 2004 The Royal Statistical Society</copyright-statement>
<license><license-p>This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.</license-p>
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<abstract><p>Fitting transmission models to outbreak data allows key epidemiological parameters to be estimated and the impact of control measures to be evaluated. <bold>Christl Donnelly</bold>
and <bold>Azra Ghani</bold>
describe the use of such models in the 2003 SARS epidemic in Hong Kong.</p>
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