Bayesian Analysis of Severe Acute Respiratory Syndrome: The 2003 Hong Kong Epidemic
Identifieur interne : 000E40 ( Pmc/Curation ); précédent : 000E39; suivant : 000E41Bayesian Analysis of Severe Acute Respiratory Syndrome: The 2003 Hong Kong Epidemic
Auteurs : Phenyo E. LekoneSource :
- Biometrical Journal. Biometrische Zeitschrift [ 0323-3847 ] ; 2008.
Abstract
This paper analyzes data arising from a Severe Acute Respiratory Syndrome (SARS) epidemic in Hong Kong in 2003 involving 1755 cases. A discrete time stochastic model that uses a back‐projection approach is proposed. Markov Chain Monte Carlo (MCMC) methods are developed for estimation of model parameters. The algorithm is further extended to integrate numerically over unobserved variables of the model. Applying the method to SARS data from Hong Kong, a value of 3.88 with a posterior standard deviation of 0.09 was estimated for the basic reproduction number. An estimate of the transmission parameter at the beginning of the epidemic was also obtained as 0.149 with a posterior standard deviation of 0.003. A reduction in the transmission parameter during the course of the epidemic forced the effective reproduction number to cross the threshold value of one, seven days after control interventions were introduced. At the end of the epidemic, the effective reproduction number was as low as 0.001 suggesting that the epidemic was brought under control by the intervention measures introduced. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Url:
DOI: 10.1002/bimj.200710431
PubMed: 18615412
PubMed Central: 7161832
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<front><journal-meta><journal-id journal-id-type="nlm-ta">Biom J</journal-id><journal-id journal-id-type="iso-abbrev">Biom J</journal-id><journal-id journal-id-type="doi">10.1002/(ISSN)1521-4036</journal-id><journal-id journal-id-type="publisher-id">BIMJ</journal-id><journal-title-group><journal-title>Biometrical Journal. Biometrische Zeitschrift</journal-title></journal-title-group><issn pub-type="ppub">0323-3847</issn><issn pub-type="epub">1521-4036</issn><publisher><publisher-name>WILEY‐VCH Verlag</publisher-name><publisher-loc>Weinheim</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">18615412</article-id><article-id pub-id-type="pmc">7161832</article-id><article-id pub-id-type="doi">10.1002/bimj.200710431</article-id><article-id pub-id-type="publisher-id">BIMJ200710431</article-id><article-categories><subj-group subj-group-type="overline"><subject>Statistical Methods in Epidemiology</subject></subj-group><subj-group subj-group-type="heading"><subject>Statistical Methods in Epidemiology</subject></subj-group></article-categories><title-group><article-title>Bayesian Analysis of Severe Acute Respiratory Syndrome: The 2003 Hong Kong Epidemic</article-title><alt-title alt-title-type="right-running-head">Bayesian Analysis of the 2003 SARS Epidermic</alt-title></title-group><contrib-group><contrib id="au1" contrib-type="author" corresp="yes"><name><surname>Lekone</surname><given-names>Phenyo E.</given-names></name><xref ref-type="aff" rid="a1"><sup>1</sup></xref><address><email>lekonepe@mopipi.ub.bw</email></address></contrib></contrib-group><aff id="a1"><label><sup>1</sup></label>Mathematics Department, University of Botswana, Private Bag 0022, Gaborone, Botswana</aff><author-notes><corresp id="correspondenceTo"><label>*</label>Phone: +00267 355 2127, Fax: +00267 355 2784</corresp></author-notes><pub-date pub-type="epub"><day>09</day><month>7</month><year>2008</year></pub-date><pub-date pub-type="ppub"><month>8</month><year>2008</year></pub-date><volume>50</volume><issue>4</issue><issue-id pub-id-type="doi">10.1002/bimj.v50:4</issue-id><fpage>597</fpage><lpage>607</lpage><history><date date-type="received"><day>30</day><month>10</month><year>2007</year></date><date date-type="rev-recd"><day>03</day><month>3</month><year>2008</year></date><date date-type="accepted"><day>19</day><month>3</month><year>2008</year></date></history><permissions><copyright-statement content-type="article-copyright">Copyright © 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim</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></license></permissions><self-uri content-type="pdf" xlink:href="file:BIMJ-50-597.pdf"></self-uri><abstract><title>Abstract</title><p>This paper analyzes data arising from a Severe Acute Respiratory Syndrome (SARS) epidemic in Hong Kong in 2003 involving 1755 cases. A discrete time stochastic model that uses a back‐projection approach is proposed. Markov Chain Monte Carlo (MCMC) methods are developed for estimation of model parameters. The algorithm is further extended to integrate numerically over unobserved variables of the model. Applying the method to SARS data from Hong Kong, a value of 3.88 with a posterior standard deviation of 0.09 was estimated for the basic reproduction number. An estimate of the transmission parameter at the beginning of the epidemic was also obtained as 0.149 with a posterior standard deviation of 0.003. A reduction in the transmission parameter during the course of the epidemic forced the effective reproduction number to cross the threshold value of one, seven days after control interventions were introduced. At the end of the epidemic, the effective reproduction number was as low as 0.001 suggesting that the epidemic was brought under control by the intervention measures introduced. (© 2008 WILEY‐VCH Verlag GmbH & Co. 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