Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach
Identifieur interne : 000452 ( Pmc/Checkpoint ); précédent : 000451; suivant : 000453Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach
Auteurs : Camille Pelat ; Neil M. Ferguson ; Peter J. White ; Carrie Reed ; Lyn Finelli ; Simon Cauchemez ; Christophe FraserSource :
- American Journal of Epidemiology [ 0002-9262 ] ; 2014.
Abstract
In the management of emerging infectious disease epidemics, precise and accurate estimation of severity indices, such as the probability of death after developing symptoms—the symptomatic case fatality ratio (sCFR)—is essential. Estimation of the sCFR may require merging data gathered through different surveillance systems and surveys. Since different surveillance strategies provide different levels of precision and accuracy, there is need for a theory to help investigators select the strategy that maximizes these properties. Here, we study the precision of sCFR estimators that combine data from several levels of the severity pyramid. We derive a formula for the standard error, which helps us find the estimator with the best precision given fixed resources. We further propose rules of thumb for guiding the choice of strategy: For example, should surveillance of a particular severity level be started? Which level should be preferred? We derive a formula for the optimal allocation of resources between chosen surveillance levels and provide a simple approximation that can be used in thinking more heuristically about planning surveillance. We illustrate these concepts with numerical examples corresponding to 3 influenza pandemic scenarios. Finally, we review the equally important issue of accuracy.
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DOI: 10.1093/aje/kwu213
PubMed: 25255809
PubMed Central: 4240167
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White</name></author><author><name sortKey="Reed, Carrie" sort="Reed, Carrie" uniqKey="Reed C" first="Carrie" last="Reed">Carrie Reed</name></author><author><name sortKey="Finelli, Lyn" sort="Finelli, Lyn" uniqKey="Finelli L" first="Lyn" last="Finelli">Lyn Finelli</name></author><author><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name></author><author><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25255809</idno><idno type="pmc">4240167</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4240167</idno><idno type="RBID">PMC:4240167</idno><idno type="doi">10.1093/aje/kwu213</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000904</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000904</idno><idno type="wicri:Area/Pmc/Curation">000904</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000904</idno><idno type="wicri:Area/Pmc/Checkpoint">000452</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000452</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach</title><author><name sortKey="Pelat, Camille" sort="Pelat, Camille" uniqKey="Pelat C" first="Camille" last="Pelat">Camille Pelat</name></author><author><name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M." last="Ferguson">Neil M. Ferguson</name></author><author><name sortKey="White, Peter J" sort="White, Peter J" uniqKey="White P" first="Peter J." last="White">Peter J. White</name></author><author><name sortKey="Reed, Carrie" sort="Reed, Carrie" uniqKey="Reed C" first="Carrie" last="Reed">Carrie Reed</name></author><author><name sortKey="Finelli, Lyn" sort="Finelli, Lyn" uniqKey="Finelli L" first="Lyn" last="Finelli">Lyn Finelli</name></author><author><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name></author><author><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name></author></analytic><series><title level="j">American Journal of Epidemiology</title><idno type="ISSN">0002-9262</idno><idno type="eISSN">1476-6256</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>In the management of emerging infectious disease epidemics, precise and accurate estimation of severity indices, such as the probability of death after developing symptoms—the symptomatic case fatality ratio (sCFR)—is essential. Estimation of the sCFR may require merging data gathered through different surveillance systems and surveys. Since different surveillance strategies provide different levels of precision and accuracy, there is need for a theory to help investigators select the strategy that maximizes these properties. Here, we study the precision of sCFR estimators that combine data from several levels of the severity pyramid. We derive a formula for the standard error, which helps us find the estimator with the best precision given fixed resources. We further propose rules of thumb for guiding the choice of strategy: For example, should surveillance of a particular severity level be started? Which level should be preferred? We derive a formula for the optimal allocation of resources between chosen surveillance levels and provide a simple approximation that can be used in thinking more heuristically about planning surveillance. We illustrate these concepts with numerical examples corresponding to 3 influenza pandemic scenarios. Finally, we review the equally important issue of accuracy.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Reed, C" uniqKey="Reed C">C Reed</name></author><author><name sortKey="Biggerstaff, M" uniqKey="Biggerstaff M">M Biggerstaff</name></author><author><name sortKey="Finelli, L" uniqKey="Finelli L">L Finelli</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fraser, C" uniqKey="Fraser C">C Fraser</name></author><author><name sortKey="Donnelly, Ca" uniqKey="Donnelly C">CA Donnelly</name></author><author><name sortKey="Cauchemez, S" uniqKey="Cauchemez S">S Cauchemez</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Collins, Sd" uniqKey="Collins S">SD Collins</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Garske, T" uniqKey="Garske T">T Garske</name></author><author><name sortKey="Legrand, J" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Am J Epidemiol</journal-id><journal-id journal-id-type="iso-abbrev">Am. J. Epidemiol</journal-id><journal-id journal-id-type="publisher-id">aje</journal-id><journal-id journal-id-type="hwp">amjepid</journal-id><journal-title-group><journal-title>American Journal of Epidemiology</journal-title></journal-title-group><issn pub-type="ppub">0002-9262</issn><issn pub-type="epub">1476-6256</issn><publisher><publisher-name>Oxford University Press</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25255809</article-id><article-id pub-id-type="pmc">4240167</article-id><article-id pub-id-type="doi">10.1093/aje/kwu213</article-id><article-id pub-id-type="publisher-id">kwu213</article-id><article-categories><subj-group subj-group-type="heading"><subject>Practice of Epidemiology</subject></subj-group></article-categories><title-group><article-title>Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Pelat</surname><given-names>Camille</given-names></name><xref ref-type="corresp" rid="cor1">*</xref></contrib><contrib contrib-type="author"><name><surname>Ferguson</surname><given-names>Neil M.</given-names></name></contrib><contrib contrib-type="author"><name><surname>White</surname><given-names>Peter J.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Reed</surname><given-names>Carrie</given-names></name></contrib><contrib contrib-type="author"><name><surname>Finelli</surname><given-names>Lyn</given-names></name></contrib><contrib contrib-type="author"><name><surname>Cauchemez</surname><given-names>Simon</given-names></name></contrib><contrib contrib-type="author"><name><surname>Fraser</surname><given-names>Christophe</given-names></name></contrib></contrib-group><author-notes><corresp id="cor1"><label>*</label>Correspondence to Dr. Camille Pelat, Institut de Veille Sanitaire, Département des Maladies Infectieuses, 12 rue du Val d'Osne, 94415 Saint-Maurice Cedex, France (e-mail: <email>c.pelat@invs.sante.fr</email>).</corresp><fn fn-type="con" id="AN1"><p>Abbreviations: sCFR, symptomatic case fatality ratio; SE, standard error.</p></fn></author-notes><pub-date pub-type="ppub"><day>15</day><month>11</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>25</day><month>9</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>25</day><month>9</month><year>2014</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
<volume>180</volume><issue>10</issue><fpage>1036</fpage><lpage>1046</lpage><history><date date-type="received"><day>28</day><month>3</month><year>2013</year></date><date date-type="accepted"><day>17</day><month>7</month><year>2014</year></date></history><permissions><copyright-statement>© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.</copyright-statement><copyright-year>2014</copyright-year><license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<uri xlink:type="simple" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</uri>), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri content-type="pdf" xlink:type="simple" xlink:href="kwu213.pdf"></self-uri><abstract><p>In the management of emerging infectious disease epidemics, precise and accurate estimation of severity indices, such as the probability of death after developing symptoms—the symptomatic case fatality ratio (sCFR)—is essential. Estimation of the sCFR may require merging data gathered through different surveillance systems and surveys. Since different surveillance strategies provide different levels of precision and accuracy, there is need for a theory to help investigators select the strategy that maximizes these properties. Here, we study the precision of sCFR estimators that combine data from several levels of the severity pyramid. We derive a formula for the standard error, which helps us find the estimator with the best precision given fixed resources. We further propose rules of thumb for guiding the choice of strategy: For example, should surveillance of a particular severity level be started? Which level should be preferred? We derive a formula for the optimal allocation of resources between chosen surveillance levels and provide a simple approximation that can be used in thinking more heuristically about planning surveillance. We illustrate these concepts with numerical examples corresponding to 3 influenza pandemic scenarios. Finally, we review the equally important issue of accuracy.</p></abstract><kwd-group><kwd>case fatality ratio</kwd><kwd>emerging infectious diseases</kwd><kwd>influenza</kwd><kwd>pandemics</kwd><kwd>statistical planning</kwd><kwd>surveillance protocol</kwd></kwd-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name><name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M." last="Ferguson">Neil M. Ferguson</name><name sortKey="Finelli, Lyn" sort="Finelli, Lyn" uniqKey="Finelli L" first="Lyn" last="Finelli">Lyn Finelli</name><name sortKey="Fraser, Christophe" sort="Fraser, Christophe" uniqKey="Fraser C" first="Christophe" last="Fraser">Christophe Fraser</name><name sortKey="Pelat, Camille" sort="Pelat, Camille" uniqKey="Pelat C" first="Camille" last="Pelat">Camille Pelat</name><name sortKey="Reed, Carrie" sort="Reed, Carrie" uniqKey="Reed C" first="Carrie" last="Reed">Carrie Reed</name><name sortKey="White, Peter J" sort="White, Peter J" uniqKey="White P" first="Peter J." last="White">Peter J. White</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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