Serveur d'exploration H2N2

Attention, ce site est en cours de développement !
Attention, site généré par des moyens informatiques à partir de corpus bruts.
Les informations ne sont donc pas validées.

Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential.

Identifieur interne : 000074 ( 1957/Analysis ); précédent : 000073; suivant : 000075

Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential.

Auteurs : Hiroshi Nishiura [Japon]

Source :

RBID : pubmed:21077712

Descripteurs français

English descriptors

Abstract

Although the generation time of an infectious disease plays a key role in estimating its transmission potential, the impact of the sampling time of generation times on the estimation procedure has yet to be clarified. The present study defines the period and cohort generation times, both of which are time-inhomogeneous, as a function of the infection time of secondary and primary cases, respectively. By means of analytical and numerical approaches, it is shown that the period generation time increases with calendar time, whereas the cohort generation time decreases as the incidence increases. The initial growth phase of an epidemic of Asian influenza A (H2N2) in the Netherlands in 1957 was reanalyzed, and estimates of the basic reproduction number, , from the Lotka-Euler equation were examined. It was found that the sampling time of generation time during the course of the epidemic introduced a time-effect to the estimate of . Other historical data of a primary pneumonic plague in Manchuria in 1911 were also examined to help illustrate the empirical evidence of the period generation time. If the serial intervals, which eventually determine the generation times, are sampled during the course of an epidemic, direct application of the sampled generation-time distribution to the Lotka-Euler equation leads to a biased estimate of . An appropriate quantification of the transmission potential requires the estimation of the cohort generation time during the initial growth phase of an epidemic or adjustment of the time-effect (e.g., adjustment of the growth rate of the epidemic during the sampling time) on the period generation time. A similar issue also applies to the estimation of the effective reproduction number as a function of calendar time. Mathematical properties of the generation time distribution in a heterogeneously mixing population need to be clarified further.

DOI: 10.3934/mbe.2010.7.851
PubMed: 21077712


Affiliations:


Links toward previous steps (curation, corpus...)


Links to Exploration step

pubmed:21077712

Le document en format XML

<record>
<TEI>
<teiHeader>
<fileDesc>
<titleStmt>
<title xml:lang="en">Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential.</title>
<author>
<name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name>
<affiliation wicri:level="1">
<nlm:affiliation>PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan. h.nishiura@uu.nl</nlm:affiliation>
<country xml:lang="fr">Japon</country>
<wicri:regionArea>PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012</wicri:regionArea>
<wicri:noRegion>Saitama 332-0012</wicri:noRegion>
</affiliation>
</author>
</titleStmt>
<publicationStmt>
<idno type="wicri:source">PubMed</idno>
<date when="2010">2010</date>
<idno type="RBID">pubmed:21077712</idno>
<idno type="pmid">21077712</idno>
<idno type="doi">10.3934/mbe.2010.7.851</idno>
<idno type="wicri:Area/PubMed/Corpus">000184</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000184</idno>
<idno type="wicri:Area/PubMed/Curation">000184</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000184</idno>
<idno type="wicri:Area/PubMed/Checkpoint">000172</idno>
<idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000172</idno>
<idno type="wicri:Area/Ncbi/Merge">000585</idno>
<idno type="wicri:Area/Ncbi/Curation">000585</idno>
<idno type="wicri:Area/Ncbi/Checkpoint">000585</idno>
<idno type="wicri:Area/Main/Merge">000E08</idno>
<idno type="wicri:Area/Main/Curation">000E02</idno>
<idno type="wicri:Area/Main/Exploration">000E02</idno>
<idno type="wicri:Area/1957/Extraction">000074</idno>
</publicationStmt>
<sourceDesc>
<biblStruct>
<analytic>
<title xml:lang="en">Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential.</title>
<author>
<name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name>
<affiliation wicri:level="1">
<nlm:affiliation>PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan. h.nishiura@uu.nl</nlm:affiliation>
<country xml:lang="fr">Japon</country>
<wicri:regionArea>PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012</wicri:regionArea>
<wicri:noRegion>Saitama 332-0012</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series>
<title level="j">Mathematical biosciences and engineering : MBE</title>
<idno type="eISSN">1551-0018</idno>
<imprint>
<date when="2010" type="published">2010</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Basic Reproduction Number</term>
<term>China (epidemiology)</term>
<term>Communicable Diseases (epidemiology)</term>
<term>Communicable Diseases (history)</term>
<term>Communicable Diseases (transmission)</term>
<term>History, 20th Century</term>
<term>Humans</term>
<term>Incidence</term>
<term>Influenza A Virus, H2N2 Subtype</term>
<term>Influenza, Human (epidemiology)</term>
<term>Influenza, Human (history)</term>
<term>Influenza, Human (transmission)</term>
<term>Models, Biological</term>
<term>Netherlands (epidemiology)</term>
<term>Plague (epidemiology)</term>
<term>Plague (history)</term>
<term>Plague (transmission)</term>
<term>Selection Bias</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr">
<term>Biais de sélection</term>
<term>Chine (épidémiologie)</term>
<term>Grippe humaine (histoire)</term>
<term>Grippe humaine (transmission)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Histoire du 20ème siècle</term>
<term>Humains</term>
<term>Incidence</term>
<term>Maladies transmissibles (histoire)</term>
<term>Maladies transmissibles (transmission)</term>
<term>Maladies transmissibles (épidémiologie)</term>
<term>Modèles biologiques</term>
<term>Nombre de reproduction de base</term>
<term>Pays-Bas (épidémiologie)</term>
<term>Peste (histoire)</term>
<term>Peste (transmission)</term>
<term>Peste (épidémiologie)</term>
<term>Sous-type H2N2 du virus de la grippe A</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en">
<term>China</term>
<term>Netherlands</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en">
<term>Communicable Diseases</term>
<term>Influenza, Human</term>
<term>Plague</term>
</keywords>
<keywords scheme="MESH" qualifier="histoire" xml:lang="fr">
<term>Grippe humaine</term>
<term>Maladies transmissibles</term>
<term>Peste</term>
</keywords>
<keywords scheme="MESH" qualifier="history" xml:lang="en">
<term>Communicable Diseases</term>
<term>Influenza, Human</term>
<term>Plague</term>
</keywords>
<keywords scheme="MESH" qualifier="transmission" xml:lang="en">
<term>Communicable Diseases</term>
<term>Influenza, Human</term>
<term>Plague</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr">
<term>Chine</term>
<term>Grippe humaine</term>
<term>Maladies transmissibles</term>
<term>Pays-Bas</term>
<term>Peste</term>
</keywords>
<keywords scheme="MESH" xml:lang="en">
<term>Basic Reproduction Number</term>
<term>History, 20th Century</term>
<term>Humans</term>
<term>Incidence</term>
<term>Influenza A Virus, H2N2 Subtype</term>
<term>Models, Biological</term>
<term>Selection Bias</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr">
<term>Biais de sélection</term>
<term>Histoire du 20ème siècle</term>
<term>Humains</term>
<term>Incidence</term>
<term>Modèles biologiques</term>
<term>Nombre de reproduction de base</term>
<term>Sous-type H2N2 du virus de la grippe A</term>
</keywords>
<keywords scheme="Wicri" type="geographic" xml:lang="fr">
<term>République populaire de Chine</term>
<term>Pays-Bas</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">Although the generation time of an infectious disease plays a key role in estimating its transmission potential, the impact of the sampling time of generation times on the estimation procedure has yet to be clarified. The present study defines the period and cohort generation times, both of which are time-inhomogeneous, as a function of the infection time of secondary and primary cases, respectively. By means of analytical and numerical approaches, it is shown that the period generation time increases with calendar time, whereas the cohort generation time decreases as the incidence increases. The initial growth phase of an epidemic of Asian influenza A (H2N2) in the Netherlands in 1957 was reanalyzed, and estimates of the basic reproduction number, , from the Lotka-Euler equation were examined. It was found that the sampling time of generation time during the course of the epidemic introduced a time-effect to the estimate of . Other historical data of a primary pneumonic plague in Manchuria in 1911 were also examined to help illustrate the empirical evidence of the period generation time. If the serial intervals, which eventually determine the generation times, are sampled during the course of an epidemic, direct application of the sampled generation-time distribution to the Lotka-Euler equation leads to a biased estimate of . An appropriate quantification of the transmission potential requires the estimation of the cohort generation time during the initial growth phase of an epidemic or adjustment of the time-effect (e.g., adjustment of the growth rate of the epidemic during the sampling time) on the period generation time. A similar issue also applies to the estimation of the effective reproduction number as a function of calendar time. Mathematical properties of the generation time distribution in a heterogeneously mixing population need to be clarified further.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>Japon</li>
</country>
</list>
<tree>
<country name="Japon">
<noRegion>
<name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Sante/explor/H2N2V1/Data/1957/Analysis
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000074 | SxmlIndent | more

Ou

HfdSelect -h $EXPLOR_AREA/Data/1957/Analysis/biblio.hfd -nk 000074 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Sante
   |area=    H2N2V1
   |flux=    1957
   |étape=   Analysis
   |type=    RBID
   |clé=     pubmed:21077712
   |texte=   Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential.
}}

Pour générer des pages wiki

HfdIndexSelect -h $EXPLOR_AREA/Data/1957/Analysis/RBID.i   -Sk "pubmed:21077712" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/1957/Analysis/biblio.hfd   \
       | NlmPubMed2Wicri -a H2N2V1 

Wicri

This area was generated with Dilib version V0.6.33.
Data generation: Tue Apr 14 19:59:40 2020. Site generation: Thu Mar 25 15:38:26 2021