The ideal reporting interval for an epidemic to objectively interpret the epidemiological time course
Identifieur interne : 001F43 ( Istex/Curation ); précédent : 001F42; suivant : 001F44The ideal reporting interval for an epidemic to objectively interpret the epidemiological time course
Auteurs : Hiroshi Nishiura [Pays-Bas] ; Gerardo Chowell [États-Unis] ; Hans Heesterbeek [Pays-Bas] ; Jacco Wallinga [Pays-Bas]Source :
- Journal of the Royal Society Interface [ 1742-5689 ] ; 2010.
Abstract
The reporting interval of infectious diseases is often determined as a time unit in the calendar regardless of the epidemiological characteristics of the disease. No guidelines have been proposed to choose the reporting interval of infectious diseases. The present study aims at translating coarsely reported epidemic data into the reproduction number and clarifying the ideal reporting interval to offer detailed insights into the time course of an epidemic. We briefly revisit the dispersibility ratio, i.e. ratio of cases in successive reporting intervals, proposed by Clare Oswald Stallybrass, detecting technical flaws in the historical studies. We derive a corrected expression for this quantity and propose simple algorithms to estimate the effective reproduction number as a function of time, adjusting the reporting interval to the generation time of a disease and demonstrating a clear relationship among the generation-time distribution, reporting interval and growth rate of an epidemic. Our exercise suggests that an ideal reporting interval is the mean generation time, so that the ratio of cases in successive intervals can yield the reproduction number. When it is impractical to report observations every mean generation time, we also present an alternative method that enables us to obtain straightforward estimates of the reproduction number for any reporting interval that suits the practical purpose of infection control.
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DOI: 10.1098/rsif.2009.0153
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first="Gerardo" last="Chowell">Gerardo Chowell</name><affiliation wicri:level="1"><mods:affiliation>School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, USA</mods:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona</wicri:regionArea></affiliation></author><author><name sortKey="Heesterbeek, Hans" sort="Heesterbeek, Hans" uniqKey="Heesterbeek H" first="Hans" last="Heesterbeek">Hans Heesterbeek</name><affiliation wicri:level="1"><mods:affiliation>Theoretical Epidemiology, University of Utrecht, Utrecht, The Netherlands</mods:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Theoretical Epidemiology, University of Utrecht, Utrecht</wicri:regionArea></affiliation></author><author><name sortKey="Wallinga, Jacco" sort="Wallinga, Jacco" uniqKey="Wallinga J" first="Jacco" last="Wallinga">Jacco Wallinga</name><affiliation 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R. Soc. Interface</title><idno type="ISSN">1742-5689</idno><idno type="eISSN">1742-5662</idno><imprint><publisher>The Royal Society</publisher><date type="published">2010</date><date type="e-published">2009</date><biblScope unit="vol">7</biblScope><biblScope unit="issue">43</biblScope><biblScope unit="page" from="297">297</biblScope><biblScope unit="page" to="307">307</biblScope></imprint><idno type="ISSN">1742-5689</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1742-5689</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract">The reporting interval of infectious diseases is often determined as a time unit in the calendar regardless of the epidemiological characteristics of the disease. No guidelines have been proposed to choose the reporting interval of infectious diseases. The present study aims at translating coarsely reported epidemic data into the reproduction number and clarifying the ideal reporting interval to offer detailed insights into the time course of an epidemic. We briefly revisit the dispersibility ratio, i.e. ratio of cases in successive reporting intervals, proposed by Clare Oswald Stallybrass, detecting technical flaws in the historical studies. We derive a corrected expression for this quantity and propose simple algorithms to estimate the effective reproduction number as a function of time, adjusting the reporting interval to the generation time of a disease and demonstrating a clear relationship among the generation-time distribution, reporting interval and growth rate of an epidemic. Our exercise suggests that an ideal reporting interval is the mean generation time, so that the ratio of cases in successive intervals can yield the reproduction number. When it is impractical to report observations every mean generation time, we also present an alternative method that enables us to obtain straightforward estimates of the reproduction number for any reporting interval that suits the practical purpose of infection control.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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