Effective reproduction numbers are commonly overestimated early in a disease outbreak
Identifieur interne : 000509 ( Istex/Corpus ); précédent : 000508; suivant : 000510Effective reproduction numbers are commonly overestimated early in a disease outbreak
Auteurs : G. N. Mercer ; K. Glass ; N. G. BeckerSource :
- Statistics in Medicine [ 0277-6715 ] ; 2011-04-30.
English descriptors
- Teeft :
- American journal, Average number, Becker, Case ascertainment, Control measures, Copyright, Daily case numbers, Data sets, Disease incidence data, Disease outbreak, Early estimates, Early stages, Effective reproduction number, Effective reproduction numbers, Estimation, Estimation methods, Euro, Euro surveillance, Exponential growth rate, Greater overestimation, Importation, Importation status, Individual infects, Infectious disease, Infectious diseases, Infectious period, Infectious periods, Initial cases, Intervention measures, John wiley sons, June, Latent period, Local cases, Local transmission, Major outbreak, Many factors, National centre, Nishiura, Other factors, Outbreak, Overestimation, Pandemic, Pandemic outbreak, Policy decisions, Population health, Population size, Posterior probability distribution, Process model, Real data, Real time, Reproduction, Reproduction number, Reproduction numbers, Royal society interface, Secondary cases, Serial interval, Serial interval distribution, Simulation, Simulation data, Small number, Solid line, Statist, Stochastic version, Subpopulation, Successful outbreak, Time period, Transmission dynamics, Western australia.
Abstract
Reproduction numbers estimated from disease incidence data can give public health authorities valuable information about the progression and likely size of a disease outbreak. Here, we show that methods for estimating effective reproduction numbers commonly give overestimates early in an outbreak. This is due to many factors including the nature of outbreaks that are used for estimation, incorrectly accounting for imported cases and outbreaks arising in subpopulations with higher transmission rates. Awareness of this bias is necessary to correctly interpret estimates from early disease outbreak data. Copyright © 2011 John Wiley & Sons, Ltd.
Url:
DOI: 10.1002/sim.4174
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ISTEX:D182C1C8D86946FDF4A10F3B759366909A1F31FCLe document en format XML
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Med.</title></titleGroup></publicationMeta><publicationMeta level="part" position="90"><doi origin="wiley" registered="yes">10.1002/sim.v30.9</doi><numberingGroup><numbering type="journalVolume" number="30">30</numbering><numbering type="journalIssue">9</numbering></numberingGroup><coverDate startDate="2011-04-30">30 April 2011</coverDate></publicationMeta><publicationMeta level="unit" type="article" position="70" status="forIssue"><doi origin="wiley" registered="yes">10.1002/sim.4174</doi><idGroup><id type="unit" value="SIM4174"></id></idGroup><countGroup><count type="pageTotal" number="11"></count></countGroup><titleGroup><title type="articleCategory">Research Article</title><title type="tocHeading1">Research Articles</title></titleGroup><copyright ownership="publisher">Copyright © 2011 John Wiley & Sons, Ltd.</copyright><eventGroup><event type="manuscriptReceived" date="2010-08-18"></event><event type="manuscriptAccepted" date="2010-11-18"></event><event type="xmlConverted" agent="Converter:JWSART34_TO_WML3G version:2.4.8 mode:FullText mathml2tex" date="2011-04-26"></event><event type="publishedOnlineEarlyUnpaginated" date="2011-02-01"></event><event type="publishedOnlineFinalForm" date="2011-04-07"></event><event type="firstOnline" date="2011-02-01"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:3.8.8" date="2014-02-08"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.1.7 mode:FullText,remove_FC" date="2014-11-03"></event></eventGroup><numberingGroup><numbering type="pageFirst">984</numbering><numbering type="pageLast">994</numbering></numberingGroup><correspondenceTo>National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</correspondenceTo><linkGroup><link type="toTypesetVersion" href="file:SIM.SIM4174.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="figureTotal" number="7"></count><count type="tableTotal" number="0"></count><count type="referenceTotal" number="31"></count></countGroup><titleGroup><title type="main" xml:lang="en">Effective reproduction numbers are commonly overestimated early in a disease outbreak</title></titleGroup><creators><creator xml:id="au1" creatorRole="author" affiliationRef="#af1" corresponding="yes"><personName><givenNames>G. N.</givenNames><familyName>Mercer</familyName></personName><contactDetails><email>Geoff.Mercer@anu.edu.au</email></contactDetails></creator><creator xml:id="au2" creatorRole="author" affiliationRef="#af1"><personName><givenNames>K.</givenNames><familyName>Glass</familyName></personName></creator><creator xml:id="au3" creatorRole="author" affiliationRef="#af1"><personName><givenNames>N. G.</givenNames><familyName>Becker</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="af1" countryCode="AU" type="organization"><unparsedAffiliation>National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en" type="author"><keyword xml:id="kwd1">reproduction number</keyword><keyword xml:id="kwd2">bias</keyword><keyword xml:id="kwd3">importation</keyword><keyword xml:id="kwd4">influenza</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><title type="main">Abstract</title><p>Reproduction numbers estimated from disease incidence data can give public health authorities valuable information about the progression and likely size of a disease outbreak. Here, we show that methods for estimating effective reproduction numbers commonly give overestimates early in an outbreak. This is due to many factors including the nature of outbreaks that are used for estimation, incorrectly accounting for imported cases and outbreaks arising in subpopulations with higher transmission rates. Awareness of this bias is necessary to correctly interpret estimates from early disease outbreak data. Copyright © 2011 John Wiley & Sons, Ltd.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Effective reproduction numbers are commonly overestimated early in a disease outbreak</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Effective reproduction numbers are commonly overestimated early in a disease outbreak</title></titleInfo><name type="personal"><namePart type="given">G. N.</namePart><namePart type="family">Mercer</namePart><affiliation>National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</affiliation><affiliation>E-mail: Geoff.Mercer@anu.edu.au</affiliation><affiliation>Correspondence address: National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">K.</namePart><namePart type="family">Glass</namePart><affiliation>National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">N. G.</namePart><namePart type="family">Becker</namePart><affiliation>National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT 0200, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article" authority="ISTEX" authorityURI="https://content-type.data.istex.fr" valueURI="https://content-type.data.istex.fr/ark:/67375/XTP-6N5SZHKN-D">article</genre><originInfo><publisher>John Wiley & Sons, Ltd.</publisher><place><placeTerm type="text">Chichester, UK</placeTerm></place><dateIssued encoding="w3cdtf">2011-04-30</dateIssued><dateCaptured encoding="w3cdtf">2010-08-18</dateCaptured><dateValid encoding="w3cdtf">2010-11-18</dateValid><copyrightDate encoding="w3cdtf">2011</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><extent unit="figures">7</extent><extent unit="tables">0</extent><extent unit="references">31</extent></physicalDescription><abstract lang="en">Reproduction numbers estimated from disease incidence data can give public health authorities valuable information about the progression and likely size of a disease outbreak. Here, we show that methods for estimating effective reproduction numbers commonly give overestimates early in an outbreak. This is due to many factors including the nature of outbreaks that are used for estimation, incorrectly accounting for imported cases and outbreaks arising in subpopulations with higher transmission rates. Awareness of this bias is necessary to correctly interpret estimates from early disease outbreak data. Copyright © 2011 John Wiley & Sons, Ltd.</abstract><subject lang="en"><genre>keywords</genre><topic>reproduction number</topic><topic>bias</topic><topic>importation</topic><topic>influenza</topic></subject><relatedItem type="host"><titleInfo><title>Statistics in Medicine</title></titleInfo><titleInfo type="abbreviated"><title>Statist. 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|texte= Effective reproduction numbers are commonly overestimated early in a disease outbreak
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