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Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Identifieur interne : 000274 ( Pmc/Checkpoint ); précédent : 000273; suivant : 000275

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Auteurs : R. N. Thompson [Royaume-Uni] ; J. E. Stockwin [Royaume-Uni] ; R. D. Van Gaalen [Pays-Bas] ; J. A. Polonsky [Suisse] ; Z. N. Kamvar [Royaume-Uni] ; P. A. Demarsh [Canada] ; E. Dahlqwist [Suède] ; S. Li [Suède] ; E. Miguel [France] ; T. Jombart [Royaume-Uni] ; J. Lessler [États-Unis] ; S. Cauchemez [France] ; A. Cori [Royaume-Uni]

Source :

RBID : PMC:7105007

Abstract

Highlights

Real-time estimation of reproduction numbers during outbreaks can guide control.

Using up-to-date serial interval data and accounting for imported cases is vital.

We develop a framework for estimating pathogen transmissibility appropriately.

We demonstrate it using data from outbreaks of influenza, Ebola and MERS.

Our approach is implemented in R package EpiEstim and online application EpiEstim App.


Url:
DOI: 10.1016/j.epidem.2019.100356
PubMed: 31624039
PubMed Central: 7105007


Affiliations:


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PMC:7105007

Le document en format XML

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<title level="j">Epidemics</title>
<idno type="ISSN">1755-4365</idno>
<idno type="eISSN">1878-0067</idno>
<imprint>
<date when="2019">2019</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<title>Highlights</title>
<p>
<list list-type="simple" id="lis0005">
<list-item id="lsti0005">
<label></label>
<p id="par0005">Real-time estimation of reproduction numbers during outbreaks can guide control.</p>
</list-item>
<list-item id="lsti0010">
<label></label>
<p id="par0010">Using up-to-date serial interval data and accounting for imported cases is vital.</p>
</list-item>
<list-item id="lsti0015">
<label></label>
<p id="par0015">We develop a framework for estimating pathogen transmissibility appropriately.</p>
</list-item>
<list-item id="lsti0020">
<label></label>
<p id="par0020">We demonstrate it using data from outbreaks of influenza, Ebola and MERS.</p>
</list-item>
<list-item id="lsti0025">
<label></label>
<p id="par0025">Our approach is implemented in R package
<italic>EpiEstim</italic>
and online application
<italic>EpiEstim App</italic>
.</p>
</list-item>
</list>
</p>
</div>
</front>
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<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Epidemics</journal-id>
<journal-id journal-id-type="iso-abbrev">Epidemics</journal-id>
<journal-title-group>
<journal-title>Epidemics</journal-title>
</journal-title-group>
<issn pub-type="ppub">1755-4365</issn>
<issn pub-type="epub">1878-0067</issn>
<publisher>
<publisher-name>The Authors. Published by Elsevier B.V.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">31624039</article-id>
<article-id pub-id-type="pmc">7105007</article-id>
<article-id pub-id-type="publisher-id">S1755-4365(19)30035-0</article-id>
<article-id pub-id-type="doi">10.1016/j.epidem.2019.100356</article-id>
<article-id pub-id-type="publisher-id">100356</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Improved inference of time-varying reproduction numbers during infectious disease outbreaks</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" id="aut0005">
<name>
<surname>Thompson</surname>
<given-names>R.N.</given-names>
</name>
<email>robin.thompson@chch.ox.ac.uk</email>
<xref rid="aff0005" ref-type="aff">a</xref>
<xref rid="aff0010" ref-type="aff">b</xref>
<xref rid="aff0015" ref-type="aff">c</xref>
<xref rid="cor0005" ref-type="corresp"></xref>
</contrib>
<contrib contrib-type="author" id="aut0010">
<name>
<surname>Stockwin</surname>
<given-names>J.E.</given-names>
</name>
<xref rid="aff0020" ref-type="aff">d</xref>
</contrib>
<contrib contrib-type="author" id="aut0015">
<name>
<surname>van Gaalen</surname>
<given-names>R.D.</given-names>
</name>
<xref rid="aff0025" ref-type="aff">e</xref>
</contrib>
<contrib contrib-type="author" id="aut0020">
<name>
<surname>Polonsky</surname>
<given-names>J.A.</given-names>
</name>
<xref rid="aff0030" ref-type="aff">f</xref>
<xref rid="aff0075" ref-type="aff">o</xref>
</contrib>
<contrib contrib-type="author" id="aut0025">
<name>
<surname>Kamvar</surname>
<given-names>Z.N.</given-names>
</name>
<xref rid="aff0035" ref-type="aff">g</xref>
</contrib>
<contrib contrib-type="author" id="aut0030">
<name>
<surname>Demarsh</surname>
<given-names>P.A.</given-names>
</name>
<xref rid="aff0040" ref-type="aff">h</xref>
<xref rid="aff0045" ref-type="aff">i</xref>
</contrib>
<contrib contrib-type="author" id="aut0035">
<name>
<surname>Dahlqwist</surname>
<given-names>E.</given-names>
</name>
<xref rid="aff0050" ref-type="aff">j</xref>
</contrib>
<contrib contrib-type="author" id="aut0040">
<name>
<surname>Li</surname>
<given-names>S.</given-names>
</name>
<xref rid="aff0050" ref-type="aff">j</xref>
</contrib>
<contrib contrib-type="author" id="aut0045">
<name>
<surname>Miguel</surname>
<given-names>E.</given-names>
</name>
<xref rid="aff0055" ref-type="aff">k</xref>
</contrib>
<contrib contrib-type="author" id="aut0050">
<name>
<surname>Jombart</surname>
<given-names>T.</given-names>
</name>
<xref rid="aff0035" ref-type="aff">g</xref>
<xref rid="aff0060" ref-type="aff">l</xref>
</contrib>
<contrib contrib-type="author" id="aut0055">
<name>
<surname>Lessler</surname>
<given-names>J.</given-names>
</name>
<xref rid="aff0065" ref-type="aff">m</xref>
</contrib>
<contrib contrib-type="author" id="aut0060">
<name>
<surname>Cauchemez</surname>
<given-names>S.</given-names>
</name>
<xref rid="aff0070" ref-type="aff">n</xref>
</contrib>
<contrib contrib-type="author" id="aut0065">
<name>
<surname>Cori</surname>
<given-names>A.</given-names>
</name>
<xref rid="aff0035" ref-type="aff">g</xref>
</contrib>
</contrib-group>
<aff id="aff0005">
<label>a</label>
Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK</aff>
<aff id="aff0010">
<label>b</label>
Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK</aff>
<aff id="aff0015">
<label>c</label>
Christ Church, University of Oxford, St Aldates, Oxford OX1 1DP, UK</aff>
<aff id="aff0020">
<label>d</label>
Lady Margaret Hall, University of Oxford, Norham Gardens, Oxford OX2 6QA, UK</aff>
<aff id="aff0025">
<label>e</label>
Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, the Netherlands</aff>
<aff id="aff0030">
<label>f</label>
World Health Organization, Avenue Appia, Geneva 1202, Switzerland</aff>
<aff id="aff0035">
<label>g</label>
MRC Centre for Global Infectious Disease Analysis, Imperial College London, Faculty of Medicine, London W2 1PG, UK</aff>
<aff id="aff0040">
<label>h</label>
The Surveillance Lab, McGill University, 1140 Pine Avenue West, Montreal H3A 1A3, Canada</aff>
<aff id="aff0045">
<label>i</label>
Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, 130 Colonnade Road, Ottawa, Ontario, K1A 0K9, Canada</aff>
<aff id="aff0050">
<label>j</label>
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden</aff>
<aff id="aff0055">
<label>k</label>
MIVEGEC, IRD, University of Montpellier, CNRS, Montpellier, France</aff>
<aff id="aff0060">
<label>l</label>
Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK</aff>
<aff id="aff0065">
<label>m</label>
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA</aff>
<aff id="aff0070">
<label>n</label>
Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris 75015, France</aff>
<aff id="aff0075">
<label>o</label>
Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, Geneva 1211, Switzerland</aff>
<author-notes>
<corresp id="cor0005">
<label></label>
Corresponding author at: Christ Church, University of Oxford, St Aldates, Oxford OX1 1DP, UK.
<email>robin.thompson@chch.ox.ac.uk</email>
</corresp>
</author-notes>
<pub-date pub-type="pmc-release">
<day>26</day>
<month>8</month>
<year>2019</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub">
<month>12</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>26</day>
<month>8</month>
<year>2019</year>
</pub-date>
<volume>29</volume>
<fpage>100356</fpage>
<lpage>100356</lpage>
<history>
<date date-type="received">
<day>8</day>
<month>3</month>
<year>2019</year>
</date>
<date date-type="rev-recd">
<day>15</day>
<month>7</month>
<year>2019</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>7</month>
<year>2019</year>
</date>
</history>
<permissions>
<copyright-statement>© 2019 The Authors</copyright-statement>
<copyright-year>2019</copyright-year>
<license>
<license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p>
</license>
</permissions>
<abstract abstract-type="author-highlights" id="abs0005">
<title>Highlights</title>
<p>
<list list-type="simple" id="lis0005">
<list-item id="lsti0005">
<label></label>
<p id="par0005">Real-time estimation of reproduction numbers during outbreaks can guide control.</p>
</list-item>
<list-item id="lsti0010">
<label></label>
<p id="par0010">Using up-to-date serial interval data and accounting for imported cases is vital.</p>
</list-item>
<list-item id="lsti0015">
<label></label>
<p id="par0015">We develop a framework for estimating pathogen transmissibility appropriately.</p>
</list-item>
<list-item id="lsti0020">
<label></label>
<p id="par0020">We demonstrate it using data from outbreaks of influenza, Ebola and MERS.</p>
</list-item>
<list-item id="lsti0025">
<label></label>
<p id="par0025">Our approach is implemented in R package
<italic>EpiEstim</italic>
and online application
<italic>EpiEstim App</italic>
.</p>
</list-item>
</list>
</p>
</abstract>
<abstract id="abs0010">
<p>Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.</p>
</abstract>
<kwd-group id="kwd0005">
<title>Keywords</title>
<kwd>Mathematical modelling</kwd>
<kwd>Infectious disease epidemiology</kwd>
<kwd>Parameter inference</kwd>
<kwd>Reproduction number</kwd>
<kwd>Serial interval</kwd>
<kwd>Disease control</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>Canada</li>
<li>France</li>
<li>Pays-Bas</li>
<li>Royaume-Uni</li>
<li>Suisse</li>
<li>Suède</li>
<li>États-Unis</li>
</country>
<region>
<li>Angleterre</li>
<li>Canton de Genève</li>
<li>Languedoc-Roussillon</li>
<li>Occitanie (région administrative)</li>
<li>Oxfordshire</li>
<li>Québec</li>
<li>Île-de-France</li>
</region>
<settlement>
<li>Genève</li>
<li>Montpellier</li>
<li>Montréal</li>
<li>Oxford</li>
</settlement>
<orgName>
<li>Université McGill</li>
<li>Université d'Oxford</li>
<li>Université de Genève</li>
</orgName>
</list>
<tree>
<country name="Royaume-Uni">
<region name="Angleterre">
<name sortKey="Thompson, R N" sort="Thompson, R N" uniqKey="Thompson R" first="R. N." last="Thompson">R. N. Thompson</name>
</region>
<name sortKey="Cori, A" sort="Cori, A" uniqKey="Cori A" first="A." last="Cori">A. Cori</name>
<name sortKey="Jombart, T" sort="Jombart, T" uniqKey="Jombart T" first="T." last="Jombart">T. Jombart</name>
<name sortKey="Jombart, T" sort="Jombart, T" uniqKey="Jombart T" first="T." last="Jombart">T. Jombart</name>
<name sortKey="Kamvar, Z N" sort="Kamvar, Z N" uniqKey="Kamvar Z" first="Z. N." last="Kamvar">Z. N. Kamvar</name>
<name sortKey="Stockwin, J E" sort="Stockwin, J E" uniqKey="Stockwin J" first="J. E." last="Stockwin">J. E. Stockwin</name>
<name sortKey="Thompson, R N" sort="Thompson, R N" uniqKey="Thompson R" first="R. N." last="Thompson">R. N. Thompson</name>
<name sortKey="Thompson, R N" sort="Thompson, R N" uniqKey="Thompson R" first="R. N." last="Thompson">R. N. Thompson</name>
</country>
<country name="Pays-Bas">
<noRegion>
<name sortKey="Van Gaalen, R D" sort="Van Gaalen, R D" uniqKey="Van Gaalen R" first="R. D." last="Van Gaalen">R. D. Van Gaalen</name>
</noRegion>
</country>
<country name="Suisse">
<noRegion>
<name sortKey="Polonsky, J A" sort="Polonsky, J A" uniqKey="Polonsky J" first="J. A." last="Polonsky">J. A. Polonsky</name>
</noRegion>
<name sortKey="Polonsky, J A" sort="Polonsky, J A" uniqKey="Polonsky J" first="J. A." last="Polonsky">J. A. Polonsky</name>
</country>
<country name="Canada">
<region name="Québec">
<name sortKey="Demarsh, P A" sort="Demarsh, P A" uniqKey="Demarsh P" first="P. A." last="Demarsh">P. A. Demarsh</name>
</region>
<name sortKey="Demarsh, P A" sort="Demarsh, P A" uniqKey="Demarsh P" first="P. A." last="Demarsh">P. A. Demarsh</name>
</country>
<country name="Suède">
<noRegion>
<name sortKey="Dahlqwist, E" sort="Dahlqwist, E" uniqKey="Dahlqwist E" first="E." last="Dahlqwist">E. Dahlqwist</name>
</noRegion>
<name sortKey="Li, S" sort="Li, S" uniqKey="Li S" first="S." last="Li">S. Li</name>
</country>
<country name="France">
<region name="Occitanie (région administrative)">
<name sortKey="Miguel, E" sort="Miguel, E" uniqKey="Miguel E" first="E." last="Miguel">E. Miguel</name>
</region>
<name sortKey="Cauchemez, S" sort="Cauchemez, S" uniqKey="Cauchemez S" first="S." last="Cauchemez">S. Cauchemez</name>
</country>
<country name="États-Unis">
<noRegion>
<name sortKey="Lessler, J" sort="Lessler, J" uniqKey="Lessler J" first="J." last="Lessler">J. Lessler</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>

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