An exploratory method for estimating the changing speed of epidemic waves from historical data : Communicable disease
Identifieur interne : 001349 ( Main/Exploration ); précédent : 001348; suivant : 001350An exploratory method for estimating the changing speed of epidemic waves from historical data : Communicable disease
Auteurs : Andrew D. Cliff [Royaume-Uni] ; Peter Haggett [Royaume-Uni] ; Matthew Smallman-Raynor [Royaume-Uni]Source :
- International journal of epidemiology [ 0300-5771 ] ; 2008.
Descripteurs français
- Pascal (Inist)
- Wicri :
- geographic : Islande.
- topic : Historique, Homme.
English descriptors
- KwdEn :
Abstract
Background Historical data are necessary to establish long-term trends in disease incidence but pose analytical problems since their accuracy and reliability may be poorly specified. Methods A robust measure of the spatial velocity, R0A, of epidemic waves from space-time series is proposed using binary data. The method was applied to the historical records of influenza morbidity for the island of Iceland over a 61-year period of influenza seasons from 1915-16 to 1975-76. Results The onset of influenza waves tended to speed up over the period studied and the three pandemic waves associated with viral shifts in influenza A [Spanish influenza H1N1 (1918-19), Asian influenza H2N2 (1957-58) and Hong Kong influenza H3N2 (1968-69)] spread more rapidly around the island and struck earlier in the influenza season than did inter-pandemic waves, even when the latter were equally intensive as measured by total number of cases and case incidence. Discussion The potential for using R0A in a real-time context is explored using French influenza data. Conclusions The new measure of wave velocity appears to be applicable to those historical time series where breakdown into regional or local areas is available. The study is being extended to (i) other countries where similar influenza time series are available and (ii) to other diseases within Iceland.
Affiliations:
- Royaume-Uni
- Angleterre, Angleterre de l'Est, Nottinghamshire
- Cambridge, Nottingham
- Université de Cambridge, Université de Nottingham
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Cliff</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Department of Geography, University of Cambridge</s1><s2>Cambridge CB2 3EN</s2><s3>GBR</s3><sZ>1 aut.</sZ></inist:fA14><country>Royaume-Uni</country><placeName><settlement type="city">Cambridge</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Angleterre de l'Est</region></placeName><orgName type="university">Université de Cambridge</orgName></affiliation></author><author><name sortKey="Haggett, Peter" sort="Haggett, Peter" uniqKey="Haggett P" first="Peter" last="Haggett">Peter Haggett</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Institute for Advanced Studies, University of Bristol, BS8 IUR</s1><s2>Bristol</s2><s3>GBR</s3><sZ>2 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Bristol</wicri:noRegion></affiliation></author><author><name sortKey="Smallman Raynor, Matthew" sort="Smallman Raynor, Matthew" uniqKey="Smallman Raynor M" first="Matthew" last="Smallman-Raynor">Matthew Smallman-Raynor</name><affiliation wicri:level="4"><inist:fA14 i1="03"><s1>School of Geography, University of Nottingham</s1><s2>Nottingham NG7 2RD</s2><s3>GBR</s3><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><placeName><settlement type="city">Nottingham</settlement><region type="nation">Angleterre</region><region type="région" nuts="1">Nottinghamshire</region></placeName><orgName type="university">Université de Nottingham</orgName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">08-0163570</idno><date when="2008">2008</date><idno type="stanalyst">PASCAL 08-0163570 INIST</idno><idno type="RBID">Pascal:08-0163570</idno><idno type="wicri:Area/PascalFrancis/Corpus">000033</idno><idno type="wicri:Area/PascalFrancis/Curation">000041</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000033</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">000033</idno><idno type="wicri:doubleKey">0300-5771:2008:Cliff A:an:exploratory:method</idno><idno type="wicri:Area/Main/Merge">001362</idno><idno type="wicri:Area/Main/Curation">001349</idno><idno type="wicri:Area/Main/Exploration">001349</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">An exploratory method for estimating the changing speed of epidemic waves from historical data : Communicable disease</title><author><name sortKey="Cliff, Andrew D" sort="Cliff, Andrew D" uniqKey="Cliff A" first="Andrew D." last="Cliff">Andrew D. Cliff</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Department of Geography, University of Cambridge</s1><s2>Cambridge CB2 3EN</s2><s3>GBR</s3><sZ>1 aut.</sZ></inist:fA14><country>Royaume-Uni</country><placeName><settlement type="city">Cambridge</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Angleterre de l'Est</region></placeName><orgName type="university">Université de Cambridge</orgName></affiliation></author><author><name sortKey="Haggett, Peter" sort="Haggett, Peter" uniqKey="Haggett P" first="Peter" last="Haggett">Peter Haggett</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Institute for Advanced Studies, University of Bristol, BS8 IUR</s1><s2>Bristol</s2><s3>GBR</s3><sZ>2 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Bristol</wicri:noRegion></affiliation></author><author><name sortKey="Smallman Raynor, Matthew" sort="Smallman Raynor, Matthew" uniqKey="Smallman Raynor M" first="Matthew" last="Smallman-Raynor">Matthew Smallman-Raynor</name><affiliation wicri:level="4"><inist:fA14 i1="03"><s1>School of Geography, University of Nottingham</s1><s2>Nottingham NG7 2RD</s2><s3>GBR</s3><sZ>3 aut.</sZ></inist:fA14><country>Royaume-Uni</country><placeName><settlement type="city">Nottingham</settlement><region type="nation">Angleterre</region><region type="région" nuts="1">Nottinghamshire</region></placeName><orgName type="university">Université de Nottingham</orgName></affiliation></author></analytic><series><title level="j" type="main">International journal of epidemiology</title><title level="j" type="abbreviated">Int. j. epidemiol.</title><idno type="ISSN">0300-5771</idno><imprint><date when="2008">2008</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">International journal of epidemiology</title><title level="j" type="abbreviated">Int. j. epidemiol.</title><idno type="ISSN">0300-5771</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Case history</term><term>Epidemiology</term><term>Estimation</term><term>Human</term><term>Iceland</term><term>Influenza</term><term>Method</term><term>Pandemic</term><term>Propagation velocity</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Grippe</term><term>Epidémiologie</term><term>Vitesse propagation</term><term>Islande</term><term>Historique</term><term>Méthode</term><term>Estimation</term><term>Homme</term><term>Pandémie</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Islande</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Historique</term><term>Homme</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Background Historical data are necessary to establish long-term trends in disease incidence but pose analytical problems since their accuracy and reliability may be poorly specified. Methods A robust measure of the spatial velocity, R<sub>0A</sub>, of epidemic waves from space-time series is proposed using binary data. The method was applied to the historical records of influenza morbidity for the island of Iceland over a 61-year period of influenza seasons from 1915-16 to 1975-76. Results The onset of influenza waves tended to speed up over the period studied and the three pandemic waves associated with viral shifts in influenza A [Spanish influenza H<sub>1</sub>N<sub>1</sub> (1918-19), Asian influenza H<sub>2</sub>N<sub>2</sub> (1957-58) and Hong Kong influenza H<sub>3</sub>N<sub>2</sub> (1968-69)] spread more rapidly around the island and struck earlier in the influenza season than did inter-pandemic waves, even when the latter were equally intensive as measured by total number of cases and case incidence. Discussion The potential for using R<sub>0A</sub> in a real-time context is explored using French influenza data. Conclusions The new measure of wave velocity appears to be applicable to those historical time series where breakdown into regional or local areas is available. The study is being extended to (i) other countries where similar influenza time series are available and (ii) to other diseases within Iceland.</div></front></TEI><affiliations><list><country><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Angleterre de l'Est</li><li>Nottinghamshire</li></region><settlement><li>Cambridge</li><li>Nottingham</li></settlement><orgName><li>Université de Cambridge</li><li>Université de Nottingham</li></orgName></list><tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Cliff, Andrew D" sort="Cliff, Andrew D" uniqKey="Cliff A" first="Andrew D." last="Cliff">Andrew D. Cliff</name></region><name sortKey="Haggett, Peter" sort="Haggett, Peter" uniqKey="Haggett P" first="Peter" last="Haggett">Peter Haggett</name><name sortKey="Smallman Raynor, Matthew" sort="Smallman Raynor, Matthew" uniqKey="Smallman Raynor M" first="Matthew" last="Smallman-Raynor">Matthew Smallman-Raynor</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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