Superspreading and the effect of individual variation on disease emergence
Identifieur interne : 000449 ( Pmc/Curation ); précédent : 000448; suivant : 000450Superspreading and the effect of individual variation on disease emergence
Auteurs : J. O. Lloyd-Smith [États-Unis] ; S. J. Schreiber [États-Unis] ; P. E. Kopp [Royaume-Uni] ; W. M. Getz [États-Unis]Source :
- Nature [ 0028-0836 ] ; 2005.
Abstract
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.
The online version of this article (doi:10.1038/nature04153) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1038/nature04153
PubMed: 16292310
PubMed Central: 7094981
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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">16292310</article-id><article-id pub-id-type="pmc">7094981</article-id><article-id pub-id-type="publisher-id">BFnature04153</article-id><article-id pub-id-type="doi">10.1038/nature04153</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Superspreading and the effect of individual variation on disease emergence</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Lloyd-Smith</surname><given-names>J. O.</given-names></name><address><email>jls@nature.berkeley.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Schreiber</surname><given-names>S. J.</given-names></name><xref ref-type="aff" rid="Aff3">3</xref></contrib><contrib contrib-type="author"><name><surname>Kopp</surname><given-names>P. E.</given-names></name><xref ref-type="aff" rid="Aff4">4</xref></contrib><contrib contrib-type="author"><name><surname>Getz</surname><given-names>W. M.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.47840.3f</institution-id><institution-id institution-id-type="ISNI">0000 0001 2181 7878</institution-id><institution>Department of Environmental Science,</institution><institution>Policy and Management, University of California,</institution></institution-wrap>140 Mulford Hall, California 94720-3114 Berkeley, USA</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.47840.3f</institution-id><institution-id institution-id-type="ISNI">0000 0001 2181 7878</institution-id><institution>Biophysics Graduate Group,</institution><institution>University of California,</institution></institution-wrap>California 94720-3200 Berkeley, USA</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="GRID">grid.264889.9</institution-id><institution-id institution-id-type="ISNI">0000 0001 1940 3051</institution-id><institution>Department of Mathematics,</institution><institution>The College of William and Mary,</institution></institution-wrap>Virginia 23187-8975 Williamsburg, USA</aff><aff id="Aff4"><label>4</label><institution-wrap><institution-id institution-id-type="GRID">grid.9481.4</institution-id><institution-id institution-id-type="ISNI">0000 0004 0412 8669</institution-id><institution>Centre for Mathematics,</institution><institution>University of Hull,</institution></institution-wrap>HU6 7RX Hull, UK</aff></contrib-group><pub-date pub-type="ppub"><year>2005</year></pub-date><volume>438</volume><issue>7066</issue><fpage>355</fpage><lpage>359</lpage><history><date date-type="received"><day>1</day><month>3</month><year>2005</year></date><date date-type="accepted"><day>22</day><month>8</month><year>2005</year></date></history><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="LongSummary"><title>Coughs and sneezes...</title><p id="Par1">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><sec><title>Supplementary information</title><p>The online version of this article (doi:10.1038/nature04153) contains supplementary material, which is available to authorized users.</p></sec></abstract><abstract id="Abs2"><p id="Par2">Population-level analyses often use average quantities to describe heterogeneous systems, particularly when variation does not arise from identifiable groups<sup><xref ref-type="bibr" rid="CR1">1</xref>,<xref ref-type="bibr" rid="CR2">2</xref></sup>. A prominent example, central to our current understanding of epidemic spread, is the basic reproductive number, <italic>R</italic><sub>0</sub>, which is defined as the mean number of infections caused by an infected individual in a susceptible population<sup><xref ref-type="bibr" rid="CR3">3</xref>,<xref ref-type="bibr" rid="CR4">4</xref></sup>. Population estimates of <italic>R</italic><sub>0</sub> can obscure considerable individual variation in infectiousness, as highlighted during the global emergence of severe acute respiratory syndrome (SARS) by numerous ‘superspreading events’ in which certain individuals infected unusually large numbers of secondary cases<sup><xref ref-type="bibr" rid="CR5">5</xref>,<xref ref-type="bibr" rid="CR6">6</xref>,<xref ref-type="bibr" rid="CR7">7</xref>,<xref ref-type="bibr" rid="CR8">8</xref>,<xref ref-type="bibr" rid="CR9">9</xref>,<xref ref-type="bibr" rid="CR10">10</xref></sup>. For diseases transmitted by non-sexual direct contacts, such as SARS or smallpox, individual variation is difficult to measure empirically, and thus its importance for outbreak dynamics has been unclear<sup><xref ref-type="bibr" rid="CR2">2</xref>,<xref ref-type="bibr" rid="CR10">10</xref>,<xref ref-type="bibr" rid="CR11">11</xref></sup>. Here we present an integrated theoretical and statistical analysis of the influence of individual variation in infectiousness on disease emergence. Using contact tracing data from eight directly transmitted diseases, we show that the distribution of individual infectiousness around <italic>R</italic><sub>0</sub> is often highly skewed. Model predictions accounting for this variation differ sharply from average-based approaches, with disease extinction more likely and outbreaks rarer but more explosive. Using these models, we explore implications for outbreak control, showing that individual-specific control measures outperform population-wide measures. Moreover, the dramatic improvements achieved through targeted control policies emphasize the need to identify predictive correlates of higher infectiousness. Our findings indicate that superspreading is a normal feature of disease spread, and to frame ongoing discussion we propose a rigorous definition for superspreading events and a method to predict their frequency.</p><sec><title>Supplementary information</title><p>The online version of this article (doi:10.1038/nature04153) contains supplementary material, which is available to authorized users.</p></sec></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></record>Pour manipuler ce document sous Unix (Dilib)
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