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Estimation of the Basic Reproductive Number and Mean Serial Interval of a Novel Pathogen in a Small, Well-Observed Discrete Population.

Identifieur interne : 000C60 ( PubMed/Checkpoint ); précédent : 000C59; suivant : 000C61

Estimation of the Basic Reproductive Number and Mean Serial Interval of a Novel Pathogen in a Small, Well-Observed Discrete Population.

Auteurs : Kendra M. Wu ; Steven Riley [Royaume-Uni]

Source :

RBID : pubmed:26849644

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English descriptors

Abstract

Accurately assessing the transmissibility and serial interval of a novel human pathogen is public health priority so that the timing and required strength of interventions may be determined. Recent theoretical work has focused on making best use of data from the initial exponential phase of growth of incidence in large populations.

DOI: 10.1371/journal.pone.0148061
PubMed: 26849644


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pubmed:26849644

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<title xml:lang="en">Estimation of the Basic Reproductive Number and Mean Serial Interval of a Novel Pathogen in a Small, Well-Observed Discrete Population.</title>
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<name sortKey="Wu, Kendra M" sort="Wu, Kendra M" uniqKey="Wu K" first="Kendra M" last="Wu">Kendra M. Wu</name>
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<nlm:affiliation>School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.</nlm:affiliation>
<wicri:noCountry code="subField">Hong Kong SAR</wicri:noCountry>
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<name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name>
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<nlm:affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.</nlm:affiliation>
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<title xml:lang="en">Estimation of the Basic Reproductive Number and Mean Serial Interval of a Novel Pathogen in a Small, Well-Observed Discrete Population.</title>
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<name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name>
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<nlm:affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.</nlm:affiliation>
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<idno type="eISSN">1932-6203</idno>
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<term>Basic Reproduction Number</term>
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<term>Influenza A Virus, H1N1 Subtype (physiology)</term>
<term>Influenza, Human (epidemiology)</term>
<term>Influenza, Human (transmission)</term>
<term>SARS Virus (physiology)</term>
<term>Severe Acute Respiratory Syndrome (epidemiology)</term>
<term>Severe Acute Respiratory Syndrome (transmission)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr">
<term>Flambées de maladies</term>
<term>Grippe humaine (transmission)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Humains</term>
<term>Nombre de reproduction de base</term>
<term>Sous-type H1N1 du virus de la grippe A (physiologie)</term>
<term>Syndrome respiratoire aigu sévère (transmission)</term>
<term>Syndrome respiratoire aigu sévère (épidémiologie)</term>
<term>Virus du SRAS (physiologie)</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en">
<term>Influenza, Human</term>
<term>Severe Acute Respiratory Syndrome</term>
</keywords>
<keywords scheme="MESH" qualifier="physiologie" xml:lang="fr">
<term>Sous-type H1N1 du virus de la grippe A</term>
<term>Virus du SRAS</term>
</keywords>
<keywords scheme="MESH" qualifier="physiology" xml:lang="en">
<term>Influenza A Virus, H1N1 Subtype</term>
<term>SARS Virus</term>
</keywords>
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<term>Influenza, Human</term>
<term>Severe Acute Respiratory Syndrome</term>
</keywords>
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<term>Grippe humaine</term>
<term>Syndrome respiratoire aigu sévère</term>
</keywords>
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<term>Basic Reproduction Number</term>
<term>Disease Outbreaks</term>
<term>Humans</term>
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<term>Flambées de maladies</term>
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<term>Nombre de reproduction de base</term>
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<div type="abstract" xml:lang="en">Accurately assessing the transmissibility and serial interval of a novel human pathogen is public health priority so that the timing and required strength of interventions may be determined. Recent theoretical work has focused on making best use of data from the initial exponential phase of growth of incidence in large populations.</div>
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<Year>2016</Year>
<Month>07</Month>
<Day>11</Day>
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<DateRevised>
<Year>2019</Year>
<Month>02</Month>
<Day>22</Day>
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<ISSN IssnType="Electronic">1932-6203</ISSN>
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<Issue>2</Issue>
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<Title>PloS one</Title>
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<ArticleTitle>Estimation of the Basic Reproductive Number and Mean Serial Interval of a Novel Pathogen in a Small, Well-Observed Discrete Population.</ArticleTitle>
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<AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Accurately assessing the transmissibility and serial interval of a novel human pathogen is public health priority so that the timing and required strength of interventions may be determined. Recent theoretical work has focused on making best use of data from the initial exponential phase of growth of incidence in large populations.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We measured generational transmissibility by the basic reproductive number R0 and the serial interval by its mean Tg. First, we constructed a simulation algorithm for case data arising from a small population of known size with R0 and Tg also known. We then developed an inferential model for the likelihood of these case data as a function of R0 and Tg. The model was designed to capture a) any signal of the serial interval distribution in the initial stochastic phase b) the growth rate of the exponential phase and c) the unique combination of R0 and Tg that generates a specific shape of peak incidence when the susceptible portion of a small population is depleted.</AbstractText>
<AbstractText Label="FINDINGS" NlmCategory="RESULTS">Extensive repeat simulation and parameter estimation revealed no bias in univariate estimates of either R0 and Tg. We were also able to simultaneously estimate both R0 and Tg. However, accurate final estimates could be obtained only much later in the outbreak. In particular, estimates of Tg were considerably less accurate in the bivariate case until the peak of incidence had passed.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The basic reproductive number and mean serial interval can be estimated simultaneously in real time during an outbreak of an emerging pathogen. Repeated application of these methods to small scale outbreaks at the start of an epidemic would permit accurate estimates of key parameters.</AbstractText>
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<Affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.</Affiliation>
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<GrantID>U01 GM110721</GrantID>
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<Grant>
<GrantID>093488/Z/10/Z</GrantID>
<Agency>Wellcome Trust</Agency>
<Country>United Kingdom</Country>
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<Grant>
<GrantID>R01 TW008246-01</GrantID>
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<DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName>
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