New approaches to quantifying the spread of infection
Identifieur interne : 004740 ( Main/Curation ); précédent : 004739; suivant : 004741New approaches to quantifying the spread of infection
Auteurs : Louise Matthews ; Mark WoolhouseSource :
- Nature Reviews. Microbiology [ 1740-1526 ] ; 2005.
Abstract
The last decade has seen considerable advances in statistical, mathematical and computational techniques that are available for the analysis of outbreak data. These advances have greatly increased our capacity to generate meaningful epidemiological information from relatively small numbers of cases of an infection by better representation of the stochastic nature of the outbreak events and improved methods for estimating parameters from such data. This review focuses on the application of such models, which capture the highly variable dynamics of infection spread amongst small numbers of individuals, in the following areas: quantifying the basic reproduction ratio An important development is the integration of clinical, surveillance and contact-tracing data into the modelling process. This leads to models that are better able to capture the underlying variability in the transmission dynamics and can do so with minimal assumptions. In particular, heterogeneities in the number of secondary infections generated by an infected case (as exemplified by the super-spreaders of the SARS outbreak) mean that contact tracing is essential for a proper quantification of uncertainty in the reproduction ratio. Advances in the analysis of outbreak data in the near future will probably come from the further development of molecular techniques (to assist contact tracing) and from the better integration of disease data with demographic and environmental information.
Url:
DOI: 10.1038/nrmicro1178
PubMed: 15995653
PubMed Central: 7096817
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">New approaches to quantifying the spread of infection</title><author><name sortKey="Matthews, Louise" sort="Matthews, Louise" uniqKey="Matthews L" first="Louise" last="Matthews">Louise Matthews</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Woolhouse, Mark" sort="Woolhouse, Mark" uniqKey="Woolhouse M" first="Mark" last="Woolhouse">Mark Woolhouse</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">15995653</idno><idno type="pmc">7096817</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096817</idno><idno type="RBID">PMC:7096817</idno><idno type="doi">10.1038/nrmicro1178</idno><date when="2005">2005</date><idno type="wicri:Area/Pmc/Corpus">000565</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000565</idno><idno type="wicri:Area/Pmc/Curation">000565</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000565</idno><idno type="wicri:Area/Pmc/Checkpoint">001287</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">001287</idno><idno type="wicri:Area/Ncbi/Merge">001040</idno><idno type="wicri:Area/Ncbi/Curation">001040</idno><idno type="wicri:Area/Ncbi/Checkpoint">001040</idno><idno type="wicri:doubleKey">1740-1526:2005:Matthews L:new:approaches:to</idno><idno type="wicri:Area/Main/Merge">004A13</idno><idno type="wicri:Area/Main/Curation">004740</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">New approaches to quantifying the spread of infection</title><author><name sortKey="Matthews, Louise" sort="Matthews, Louise" uniqKey="Matthews L" first="Louise" last="Matthews">Louise Matthews</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Woolhouse, Mark" sort="Woolhouse, Mark" uniqKey="Woolhouse M" first="Mark" last="Woolhouse">Mark Woolhouse</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">Nature Reviews. Microbiology</title><idno type="ISSN">1740-1526</idno><idno type="eISSN">1740-1534</idno><imprint><date when="2005">2005</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Key Points</title><p id="Par3"><list list-type="bullet"><list-item><p id="Par4">The last decade has seen considerable advances in statistical, mathematical and computational techniques that are available for the analysis of outbreak data. These advances have greatly increased our capacity to generate meaningful epidemiological information from relatively small numbers of cases of an infection by better representation of the stochastic nature of the outbreak events and improved methods for estimating parameters from such data.</p></list-item><list-item><p id="Par5">This review focuses on the application of such models, which capture the highly variable dynamics of infection spread amongst small numbers of individuals, in the following areas: quantifying the basic reproduction ratio <italic>R</italic><sub>0</sub> in the early stages of an outbreak (for foot-and-mouth disease and severe acute respiratory syndrome (SARS)); short-term predictions of outbreak progress (foot-and-mouth disease); trends towards disease emergence or re-emergence (measles in the UK); as an early warning system when there is the threat of a major outbreak (avian influenza); and capturing transmission dynamics within small populations (antibiotic-resistant nosocomial infections).</p></list-item><list-item><p id="Par6">An important development is the integration of clinical, surveillance and contact-tracing data into the modelling process. This leads to models that are better able to capture the underlying variability in the transmission dynamics and can do so with minimal assumptions. In particular, heterogeneities in the number of secondary infections generated by an infected case (as exemplified by the super-spreaders of the SARS outbreak) mean that contact tracing is essential for a proper quantification of uncertainty in the reproduction ratio.</p></list-item><list-item><p id="Par7">Advances in the analysis of outbreak data in the near future will probably come from the further development of molecular techniques (to assist contact tracing) and from the better integration of disease data with demographic and environmental information.</p></list-item></list></p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Vinten Johansen, P" uniqKey="Vinten Johansen P">P Vinten-Johansen</name></author><author><name sortKey="Brody, H" uniqKey="Brody H">H Brody</name></author><author><name sortKey="Paneth, N" uniqKey="Paneth N">N Paneth</name></author><author><name sortKey="Rachman, S" uniqKey="Rachman S">S 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