Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment
Identifieur interne : 001373 ( Pmc/Checkpoint ); précédent : 001372; suivant : 001374Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment
Auteurs : Michael Small ; C. K. TseSource :
- Physica a [ 0378-4371 ] ; 2005.
Abstract
We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3–5 days the extent of the SARS epidemic would have been minimal.
Url:
DOI: 10.1016/j.physa.2005.01.009
PubMed: NONE
PubMed Central: 7126158
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K." last="Tse">C. K. Tse</name></author></analytic><series><title level="j">Physica a</title><idno type="ISSN">0378-4371</idno><idno type="eISSN">0378-4371</idno><imprint><date when="2005">2005</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3–5 days the extent of the SARS epidemic would have been minimal.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Riley, S" uniqKey="Riley S">S. Riley</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wong, G W K" uniqKey="Wong G">G.W.K. Wong</name></author><author><name sortKey="Hui, D S C" uniqKey="Hui D">D.S.C. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Physica A</journal-id><journal-id journal-id-type="iso-abbrev">Physica A</journal-id><journal-title-group><journal-title>Physica a</journal-title></journal-title-group><issn pub-type="ppub">0378-4371</issn><issn pub-type="epub">0378-4371</issn><publisher><publisher-name>Elsevier B.V.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmc">7126158</article-id><article-id pub-id-type="publisher-id">S0378-4371(05)00030-0</article-id><article-id pub-id-type="doi">10.1016/j.physa.2005.01.009</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Clustering model for transmission of the SARS virus: application to epidemic control and risk assessment</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Small</surname><given-names>Michael</given-names></name><email>ensmall@polyu.edu.hk</email><xref rid="cor1" ref-type="corresp">*</xref></contrib><contrib contrib-type="author"><name><surname>Tse</surname><given-names>C.K.</given-names></name></contrib></contrib-group><aff>Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Hong Kong</aff><author-notes><corresp id="cor1"><label>*</label>Corresponding author. Tel.: +852 2766 4744; fax: +852 2362 8439. <email>ensmall@polyu.edu.hk</email></corresp></author-notes><pub-date pub-type="pmc-release"><day>26</day><month>1</month><year>2005</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub"><day>15</day><month>6</month><year>2005</year></pub-date><pub-date pub-type="epub"><day>26</day><month>1</month><year>2005</year></pub-date><volume>351</volume><issue>2</issue><fpage>499</fpage><lpage>511</lpage><permissions><copyright-statement>Copyright © 2005 Elsevier B.V. All rights reserved.</copyright-statement><copyright-year>2005</copyright-year><copyright-holder>Elsevier B.V.</copyright-holder><license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p></license></permissions><abstract><p>We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and “super-spreaders”. Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that “super-spreaders” may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3–5 days the extent of the SARS epidemic would have been minimal.</p></abstract><kwd-group><title>Keywords</title><kwd>Severe acute respiratory syndrome</kwd><kwd>Nonlinear dynamics</kwd><kwd>Disease transmission</kwd><kwd>Epidemiological methods</kwd><kwd>Small world networks</kwd></kwd-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Small, Michael" sort="Small, Michael" uniqKey="Small M" first="Michael" last="Small">Michael Small</name><name sortKey="Tse, C K" sort="Tse, C K" uniqKey="Tse C" first="C. K." last="Tse">C. K. Tse</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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