An exploratory method for estimating the changing speed of epidemic waves from historical data
Identifieur interne : 001412 ( Main/Exploration ); précédent : 001411; suivant : 001413An exploratory method for estimating the changing speed of epidemic waves from historical data
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
- KwdFr :
- Analyse de survie, Espagne (épidémiologie), Femelle, Flambées de maladies, Grippe humaine (diagnostic), Grippe humaine (épidémiologie), Hong Kong (épidémiologie), Humains, Islande (épidémiologie), Modèles théoriques, Morbidité (tendances), Mâle, Prévalence, Royaume-Uni (épidémiologie), Sensibilité et spécificité, Sous-type H1N1 du virus de la grippe A, Sous-type H2N2 du virus de la grippe A, Sous-type H3N2 du virus de la grippe A, Surveillance sentinelle, Valeur prédictive des tests, Études de cohortes.
- MESH :
- diagnostic : Grippe humaine.
- tendances : Morbidité.
- épidémiologie : Espagne, Grippe humaine, Hong Kong, Islande, Royaume-Uni.
- Analyse de survie, Femelle, Flambées de maladies, Humains, Modèles théoriques, Mâle, Prévalence, Sensibilité et spécificité, Sous-type H1N1 du virus de la grippe A, Sous-type H2N2 du virus de la grippe A, Sous-type H3N2 du virus de la grippe A, Surveillance sentinelle, Valeur prédictive des tests, Études de cohortes.
English descriptors
- KwdEn :
- Cohort Studies, Disease Outbreaks, Female, Hong Kong (epidemiology), Humans, Iceland (epidemiology), Influenza A Virus, H1N1 Subtype, Influenza A Virus, H2N2 Subtype, Influenza A Virus, H3N2 Subtype, Influenza, Human (diagnosis), Influenza, Human (epidemiology), Male, Models, Theoretical, Morbidity (trends), Predictive Value of Tests, Prevalence, Sensitivity and Specificity, Sentinel Surveillance, Spain (epidemiology), Survival Analysis, United Kingdom (epidemiology).
- MESH :
- diagnosis : Influenza, Human.
- epidemiology : Hong Kong, Iceland, Influenza, Human, Spain, United Kingdom.
- trends : Morbidity.
- Cohort Studies, Disease Outbreaks, Female, Humans, Influenza A Virus, H1N1 Subtype, Influenza A Virus, H2N2 Subtype, Influenza A Virus, H3N2 Subtype, Male, Models, Theoretical, Predictive Value of Tests, Prevalence, Sensitivity and Specificity, Sentinel Surveillance, Survival Analysis.
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.
Url:
DOI: 10.1093/ije/dym240
Affiliations:
- Royaume-Uni
- Angleterre, Angleterre de l'Est, Nottinghamshire
- Cambridge, Nottingham
- Université de Cambridge, Université de Nottingham
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Le document en format XML
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(trends)</term><term>Predictive Value of Tests</term><term>Prevalence</term><term>Sensitivity and Specificity</term><term>Sentinel Surveillance</term><term>Spain (epidemiology)</term><term>Survival Analysis</term><term>United Kingdom (epidemiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de survie</term><term>Espagne (épidémiologie)</term><term>Femelle</term><term>Flambées de maladies</term><term>Grippe humaine (diagnostic)</term><term>Grippe humaine (épidémiologie)</term><term>Hong Kong (épidémiologie)</term><term>Humains</term><term>Islande (épidémiologie)</term><term>Modèles théoriques</term><term>Morbidité (tendances)</term><term>Mâle</term><term>Prévalence</term><term>Royaume-Uni (épidémiologie)</term><term>Sensibilité et spécificité</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Sous-type H2N2 du virus de la grippe A</term><term>Sous-type H3N2 du virus de la grippe A</term><term>Surveillance sentinelle</term><term>Valeur prédictive des tests</term><term>Études de cohortes</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Hong Kong</term><term>Iceland</term><term>Influenza, Human</term><term>Spain</term><term>United Kingdom</term></keywords><keywords scheme="MESH" qualifier="tendances" xml:lang="fr"><term>Morbidité</term></keywords><keywords scheme="MESH" qualifier="trends" xml:lang="en"><term>Morbidity</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Espagne</term><term>Grippe humaine</term><term>Hong Kong</term><term>Islande</term><term>Royaume-Uni</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cohort Studies</term><term>Disease Outbreaks</term><term>Female</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Influenza A Virus, H2N2 Subtype</term><term>Influenza A Virus, H3N2 Subtype</term><term>Male</term><term>Models, Theoretical</term><term>Predictive Value of Tests</term><term>Prevalence</term><term>Sensitivity and Specificity</term><term>Sentinel Surveillance</term><term>Survival Analysis</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de survie</term><term>Femelle</term><term>Flambées de maladies</term><term>Humains</term><term>Modèles théoriques</term><term>Mâle</term><term>Prévalence</term><term>Sensibilité et spécificité</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Sous-type H2N2 du virus de la grippe A</term><term>Sous-type H3N2 du virus de la grippe A</term><term>Surveillance sentinelle</term><term>Valeur prédictive des tests</term><term>Études de cohortes</term></keywords></textClass></profileDesc></teiHeader><front><div type="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.</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="Haggett, Peter" sort="Haggett, Peter" uniqKey="Haggett P" first="Peter" last="Haggett">Peter Haggett</name><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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