Dimensions of superspreading
Identifieur interne : 001356 ( Pmc/Checkpoint ); précédent : 001355; suivant : 001357Dimensions of superspreading
Auteurs : Alison P. Galvani ; Robert M. MaySource :
- Nature [ 0028-0836 ] ; 2005.
Abstract
Analyses of contact-tracing data on the spread of infectious disease, combined with mathematical models, show that control measures require better knowledge of variability in individual infectiousness.
Url:
DOI: 10.1038/438293a
PubMed: 16292292
PubMed Central: 7095140
Affiliations:
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<front><journal-meta><journal-id journal-id-type="nlm-ta">Nature</journal-id><journal-id journal-id-type="iso-abbrev">Nature</journal-id><journal-title-group><journal-title>Nature</journal-title></journal-title-group><issn pub-type="ppub">0028-0836</issn><issn pub-type="epub">1476-4687</issn><publisher><publisher-name>Nature Publishing Group UK</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">16292292</article-id><article-id pub-id-type="pmc">7095140</article-id><article-id pub-id-type="publisher-id">BF438293a</article-id><article-id pub-id-type="doi">10.1038/438293a</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Dimensions of superspreading</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Galvani</surname><given-names>Alison P.</given-names></name><address><email>alison.galvani@yale.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>May</surname><given-names>Robert M.</given-names></name><address><email>robert.may@zoo.ox.ac.uk</email></address><xref ref-type="aff" rid="Aff2">2</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.47100.32</institution-id><institution-id institution-id-type="ISNI">0000000419368710</institution-id><institution>the Department of Epidemiology and Public Health,</institution><institution>Yale University School of Medicine,</institution></institution-wrap>New Haven, 06520 Connecticut USA</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.4991.5</institution-id><institution-id institution-id-type="ISNI">0000 0004 1936 8948</institution-id><institution>the Department of Zoology,</institution><institution>University of Oxford,</institution></institution-wrap>Oxford, OX1 3PS UK</aff></contrib-group><pub-date pub-type="epub"><day>16</day><month>11</month><year>2005</year></pub-date><pub-date pub-type="ppub"><year>2005</year></pub-date><volume>438</volume><issue>7066</issue><fpage>293</fpage><lpage>295</lpage><permissions><copyright-statement>© Nature Publishing Group 2005</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions><abstract id="Abs1" abstract-type="Standfirst"><p id="Par1">Analyses of contact-tracing data on the spread of infectious disease, combined with mathematical models, show that control measures require better knowledge of variability in individual infectiousness.</p></abstract><abstract id="Abs2" abstract-type="LongSummary"><title>Coughs and sneezes...</title><p id="Par2">From Typhoid Mary to SARS, it has long been known that some people spread disease more than others. But for diseases transmitted via casual contact, contagiousness arises from a plethora of social and physiological factors, so epidemiologists have tended to rely on population averages to assess a disease's potential to spread. A new analysis of outbreak data shows that individual differences in infectiousness exert powerful influences on the epidemiology of ten deadly diseases. SARS and measles (and perhaps avian influenza) show strong tendencies towards ‘superspreading events’ that can ignite explosive epidemics — but this same volatility makes outbreaks more likely to fizzle out. Smallpox and pneumonic plague, two potential bioterrorism agents, show steadier growth but still differ markedly from the traditional average-based view. These findings are relevant to how emerging diseases are detected and controlled.</p></abstract><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Springer Nature Limited 2005</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Galvani, Alison P" sort="Galvani, Alison P" uniqKey="Galvani A" first="Alison P." last="Galvani">Alison P. Galvani</name><name sortKey="May, Robert M" sort="May, Robert M" uniqKey="May R" first="Robert M." last="May">Robert M. May</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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