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Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study.

Identifieur interne : 001036 ( PubMed/Corpus ); précédent : 001035; suivant : 001037

Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study.

Auteurs : Moritz U G. Kraemer ; Nuno R. Faria ; Robert C. Reiner ; Nick Golding ; Birgit Nikolay ; Stephanie Stasse ; Michael A. Johansson ; Henrik Salje ; Ousmane Faye ; G R William Wint ; Matthias Niedrig ; Freya M. Shearer ; Sarah C. Hill ; Robin N. Thompson ; Donal Bisanzio ; Nuno Taveira ; Heinrich H. Nax ; Bary S R. Pradelski ; Elaine O. Nsoesie ; Nicholas R. Murphy ; Isaac I. Bogoch ; Kamran Khan ; John S. Brownstein ; Andrew J. Tatem ; Tulio De Oliveira ; David L. Smith ; Amadou A. Sall ; Oliver G. Pybus ; Simon I. Hay ; Simon Cauchemez

Source :

RBID : pubmed:28017559

English descriptors

Abstract

Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock.

DOI: 10.1016/S1473-3099(16)30513-8
PubMed: 28017559

Links to Exploration step

pubmed:28017559

Le document en format XML

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<nlm:affiliation>Department of Zoology, University of Oxford, Oxford, UK.</nlm:affiliation>
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<name sortKey="Reiner, Robert C" sort="Reiner, Robert C" uniqKey="Reiner R" first="Robert C" last="Reiner">Robert C. Reiner</name>
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<nlm:affiliation>Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.</nlm:affiliation>
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<name sortKey="Golding, Nick" sort="Golding, Nick" uniqKey="Golding N" first="Nick" last="Golding">Nick Golding</name>
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<nlm:affiliation>Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK; School of BioSciences, University of Melbourne, Parkville, VIC, Australia.</nlm:affiliation>
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</affiliation>
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<name sortKey="Stasse, Stephanie" sort="Stasse, Stephanie" uniqKey="Stasse S" first="Stephanie" last="Stasse">Stephanie Stasse</name>
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</affiliation>
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<name sortKey="Johansson, Michael A" sort="Johansson, Michael A" uniqKey="Johansson M" first="Michael A" last="Johansson">Michael A. Johansson</name>
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<nlm:affiliation>Centers for Disease Control and Prevention, San Juan, PR, USA; Center for Communicable Disease Dynamics, Harvard T H Chan School of Public Health, MA, USA.</nlm:affiliation>
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<name sortKey="Salje, Henrik" sort="Salje, Henrik" uniqKey="Salje H" first="Henrik" last="Salje">Henrik Salje</name>
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<nlm:affiliation>Arbovirus and Viral Hemorrhagic Fever Unit, Institut Pasteur da Dakar, Dakar, Senegal.</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Wint, G R William" sort="Wint, G R William" uniqKey="Wint G" first="G R William" last="Wint">G R William Wint</name>
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<nlm:affiliation>Environmental Research Group Oxford, Department of Zoology, Oxford, UK.</nlm:affiliation>
</affiliation>
</author>
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<name sortKey="Niedrig, Matthias" sort="Niedrig, Matthias" uniqKey="Niedrig M" first="Matthias" last="Niedrig">Matthias Niedrig</name>
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<nlm:affiliation>Robert Koch Institut, Berlin, Germany.</nlm:affiliation>
</affiliation>
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<name sortKey="Shearer, Freya M" sort="Shearer, Freya M" uniqKey="Shearer F" first="Freya M" last="Shearer">Freya M. Shearer</name>
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</affiliation>
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<name sortKey="Hill, Sarah C" sort="Hill, Sarah C" uniqKey="Hill S" first="Sarah C" last="Hill">Sarah C. Hill</name>
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<nlm:affiliation>Department of Zoology, University of Oxford, Oxford, UK.</nlm:affiliation>
</affiliation>
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<name sortKey="Thompson, Robin N" sort="Thompson, Robin N" uniqKey="Thompson R" first="Robin N" last="Thompson">Robin N. Thompson</name>
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<nlm:affiliation>Department of Zoology, University of Oxford, Oxford, UK.</nlm:affiliation>
</affiliation>
</author>
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<name sortKey="Bisanzio, Donal" sort="Bisanzio, Donal" uniqKey="Bisanzio D" first="Donal" last="Bisanzio">Donal Bisanzio</name>
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<nlm:affiliation>Department of Zoology, University of Oxford, Oxford, UK.</nlm:affiliation>
</affiliation>
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<name sortKey="Taveira, Nuno" sort="Taveira, Nuno" uniqKey="Taveira N" first="Nuno" last="Taveira">Nuno Taveira</name>
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<nlm:affiliation>Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Portugal; Centro de Investigacao Interdisciplinar Egas Moniz, Instituto Superior de Ciencias da Saude Egas Moniz, Caparica, Portugal.</nlm:affiliation>
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<nlm:affiliation>Computational Social Science, ETH Zurich, Zurich, Switzerland.</nlm:affiliation>
</affiliation>
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<name sortKey="Pradelski, Bary S R" sort="Pradelski, Bary S R" uniqKey="Pradelski B" first="Bary S R" last="Pradelski">Bary S R. Pradelski</name>
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<nlm:affiliation>Computational Social Science, ETH Zurich, Zurich, Switzerland.</nlm:affiliation>
</affiliation>
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<name sortKey="Nsoesie, Elaine O" sort="Nsoesie, Elaine O" uniqKey="Nsoesie E" first="Elaine O" last="Nsoesie">Elaine O. Nsoesie</name>
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<name sortKey="Murphy, Nicholas R" sort="Murphy, Nicholas R" uniqKey="Murphy N" first="Nicholas R" last="Murphy">Nicholas R. Murphy</name>
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<name sortKey="Bogoch, Isaac I" sort="Bogoch, Isaac I" uniqKey="Bogoch I" first="Isaac I" last="Bogoch">Isaac I. Bogoch</name>
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</affiliation>
</author>
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<name sortKey="Khan, Kamran" sort="Khan, Kamran" uniqKey="Khan K" first="Kamran" last="Khan">Kamran Khan</name>
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<nlm:affiliation>Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada.</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Brownstein, John S" sort="Brownstein, John S" uniqKey="Brownstein J" first="John S" last="Brownstein">John S. Brownstein</name>
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</affiliation>
</author>
<author>
<name sortKey="Tatem, Andrew J" sort="Tatem, Andrew J" uniqKey="Tatem A" first="Andrew J" last="Tatem">Andrew J. Tatem</name>
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</affiliation>
</author>
<author>
<name sortKey="De Oliveira, Tulio" sort="De Oliveira, Tulio" uniqKey="De Oliveira T" first="Tulio" last="De Oliveira">Tulio De Oliveira</name>
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<name sortKey="Smith, David L" sort="Smith, David L" uniqKey="Smith D" first="David L" last="Smith">David L. Smith</name>
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</affiliation>
</author>
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<name sortKey="Sall, Amadou A" sort="Sall, Amadou A" uniqKey="Sall A" first="Amadou A" last="Sall">Amadou A. Sall</name>
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<nlm:affiliation>Arbovirus and Viral Hemorrhagic Fever Unit, Institut Pasteur da Dakar, Dakar, Senegal.</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Pybus, Oliver G" sort="Pybus, Oliver G" uniqKey="Pybus O" first="Oliver G" last="Pybus">Oliver G. Pybus</name>
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<nlm:affiliation>Department of Zoology, University of Oxford, Oxford, UK.</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Hay, Simon I" sort="Hay, Simon I" uniqKey="Hay S" first="Simon I" last="Hay">Simon I. Hay</name>
<affiliation>
<nlm:affiliation>Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name>
<affiliation>
<nlm:affiliation>Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France; Centre National de la Recherche Scientifique, URA 3012, Paris, France.</nlm:affiliation>
</affiliation>
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<series>
<title level="j">The Lancet. Infectious diseases</title>
<idno type="eISSN">1474-4457</idno>
<imprint>
<date when="2017" type="published">2017</date>
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<keywords scheme="KwdEn" xml:lang="en">
<term>Aedes (virology)</term>
<term>Angola</term>
<term>Animals</term>
<term>Democratic Republic of the Congo</term>
<term>Disease Outbreaks (prevention & control)</term>
<term>Humans</term>
<term>Immunization Schedule</term>
<term>Models, Statistical</term>
<term>Rural Population (statistics & numerical data)</term>
<term>Travel</term>
<term>Urban Population (statistics & numerical data)</term>
<term>Vaccination</term>
<term>Yellow Fever (epidemiology)</term>
<term>Yellow Fever (mortality)</term>
<term>Yellow Fever (transmission)</term>
<term>Yellow fever virus (isolation & purification)</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en">
<term>Yellow Fever</term>
</keywords>
<keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en">
<term>Yellow fever virus</term>
</keywords>
<keywords scheme="MESH" qualifier="mortality" xml:lang="en">
<term>Yellow Fever</term>
</keywords>
<keywords scheme="MESH" qualifier="prevention & control" xml:lang="en">
<term>Disease Outbreaks</term>
</keywords>
<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en">
<term>Rural Population</term>
<term>Urban Population</term>
</keywords>
<keywords scheme="MESH" qualifier="transmission" xml:lang="en">
<term>Yellow Fever</term>
</keywords>
<keywords scheme="MESH" qualifier="virology" xml:lang="en">
<term>Aedes</term>
</keywords>
<keywords scheme="MESH" xml:lang="en">
<term>Angola</term>
<term>Animals</term>
<term>Democratic Republic of the Congo</term>
<term>Humans</term>
<term>Immunization Schedule</term>
<term>Models, Statistical</term>
<term>Travel</term>
<term>Vaccination</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock.</div>
</front>
</TEI>
<pubmed>
<MedlineCitation Status="MEDLINE" Owner="NLM">
<PMID Version="1">28017559</PMID>
<DateCreated>
<Year>2016</Year>
<Month>12</Month>
<Day>26</Day>
</DateCreated>
<DateCompleted>
<Year>2017</Year>
<Month>06</Month>
<Day>13</Day>
</DateCompleted>
<DateRevised>
<Year>2017</Year>
<Month>09</Month>
<Day>22</Day>
</DateRevised>
<Article PubModel="Print-Electronic">
<Journal>
<ISSN IssnType="Electronic">1474-4457</ISSN>
<JournalIssue CitedMedium="Internet">
<Volume>17</Volume>
<Issue>3</Issue>
<PubDate>
<Year>2017</Year>
<Month>Mar</Month>
</PubDate>
</JournalIssue>
<Title>The Lancet. Infectious diseases</Title>
<ISOAbbreviation>Lancet Infect Dis</ISOAbbreviation>
</Journal>
<ArticleTitle>Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study.</ArticleTitle>
<Pagination>
<MedlinePgn>330-338</MedlinePgn>
</Pagination>
<ELocationID EIdType="pii" ValidYN="Y">S1473-3099(16)30513-8</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.1016/S1473-3099(16)30513-8</ELocationID>
<Abstract>
<AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region.</AbstractText>
<AbstractText Label="FINDINGS" NlmCategory="RESULTS">The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected.</AbstractText>
<AbstractText Label="INTERPRETATION" NlmCategory="CONCLUSIONS">Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy.</AbstractText>
<AbstractText Label="FUNDING" NlmCategory="BACKGROUND">Wellcome Trust.</AbstractText>
<CopyrightInformation>Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.</CopyrightInformation>
</Abstract>
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<Author ValidYN="Y">
<LastName>Kraemer</LastName>
<ForeName>Moritz U G</ForeName>
<Initials>MUG</Initials>
<AffiliationInfo>
<Affiliation>Department of Zoology, University of Oxford, Oxford, UK. Electronic address: moritz.kraemer@zoo.ox.ac.uk.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Faria</LastName>
<ForeName>Nuno R</ForeName>
<Initials>NR</Initials>
<AffiliationInfo>
<Affiliation>Department of Zoology, University of Oxford, Oxford, UK.</Affiliation>
</AffiliationInfo>
</Author>
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<LastName>Reiner</LastName>
<ForeName>Robert C</ForeName>
<Initials>RC</Initials>
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<Affiliation>Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.</Affiliation>
</AffiliationInfo>
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<ForeName>Nick</ForeName>
<Initials>N</Initials>
<AffiliationInfo>
<Affiliation>Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK; School of BioSciences, University of Melbourne, Parkville, VIC, Australia.</Affiliation>
</AffiliationInfo>
</Author>
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<LastName>Nikolay</LastName>
<ForeName>Birgit</ForeName>
<Initials>B</Initials>
<AffiliationInfo>
<Affiliation>Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France; Centre National de la Recherche Scientifique, URA 3012, Paris, France.</Affiliation>
</AffiliationInfo>
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<Affiliation>Health Programme, European Commission, International Cooperation and Development, Delegation en RDC, Kinshasa, Democratic Republic of the Congo.</Affiliation>
</AffiliationInfo>
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<LastName>Johansson</LastName>
<ForeName>Michael A</ForeName>
<Initials>MA</Initials>
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<Affiliation>Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France; Centre National de la Recherche Scientifique, URA 3012, Paris, France; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.</Affiliation>
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<Affiliation>Arbovirus and Viral Hemorrhagic Fever Unit, Institut Pasteur da Dakar, Dakar, Senegal.</Affiliation>
</AffiliationInfo>
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<ForeName>G R William</ForeName>
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</AffiliationInfo>
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<LastName>Thompson</LastName>
<ForeName>Robin N</ForeName>
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<ForeName>Nuno</ForeName>
<Initials>N</Initials>
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<Affiliation>Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Portugal; Centro de Investigacao Interdisciplinar Egas Moniz, Instituto Superior de Ciencias da Saude Egas Moniz, Caparica, Portugal.</Affiliation>
</AffiliationInfo>
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<ForeName>Heinrich H</ForeName>
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<ForeName>Bary S R</ForeName>
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<ForeName>Elaine O</ForeName>
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<AffiliationInfo>
<Affiliation>Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.</Affiliation>
</AffiliationInfo>
</Author>
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<LastName>Murphy</LastName>
<ForeName>Nicholas R</ForeName>
<Initials>NR</Initials>
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</AffiliationInfo>
</Author>
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<ForeName>Isaac I</ForeName>
<Initials>II</Initials>
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<Affiliation>Divisions of General Internal Medicine and Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, ON, Canada.</Affiliation>
</AffiliationInfo>
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<ForeName>Kamran</ForeName>
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<Affiliation>Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada.</Affiliation>
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<Initials>JS</Initials>
<AffiliationInfo>
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</AffiliationInfo>
</Author>
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<ForeName>Andrew J</ForeName>
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<AffiliationInfo>
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</AffiliationInfo>
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<ForeName>Tulio</ForeName>
<Initials>T</Initials>
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<Initials>DL</Initials>
<AffiliationInfo>
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</AffiliationInfo>
</Author>
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<LastName>Sall</LastName>
<ForeName>Amadou A</ForeName>
<Initials>AA</Initials>
<AffiliationInfo>
<Affiliation>Arbovirus and Viral Hemorrhagic Fever Unit, Institut Pasteur da Dakar, Dakar, Senegal.</Affiliation>
</AffiliationInfo>
</Author>
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<LastName>Pybus</LastName>
<ForeName>Oliver G</ForeName>
<Initials>OG</Initials>
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</AffiliationInfo>
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<ForeName>Simon I</ForeName>
<Initials>SI</Initials>
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<ForeName>Simon</ForeName>
<Initials>S</Initials>
<AffiliationInfo>
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</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
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<Grant>
<GrantID>U01 GM110721</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant>
<GrantID>095066</GrantID>
<Agency>Wellcome Trust</Agency>
<Country>United Kingdom</Country>
</Grant>
<Grant>
<GrantID>R01 LM010812</GrantID>
<Acronym>LM</Acronym>
<Agency>NLM NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant>
<GrantID>K01 ES025438</GrantID>
<Acronym>ES</Acronym>
<Agency>NIEHS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant>
<GrantID>U54 GM088558</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant>
<GrantID>U19 AI089674</GrantID>
<Acronym>AI</Acronym>
<Agency>NIAID NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
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<Year>2016</Year>
<Month>12</Month>
<Day>23</Day>
</ArticleDate>
</Article>
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<Country>United States</Country>
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<MeshHeadingList>
<MeshHeading>
<DescriptorName UI="D000330" MajorTopicYN="N">Aedes</DescriptorName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000810" MajorTopicYN="N">Angola</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015023" MajorTopicYN="N">Democratic Republic of the Congo</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName>
<QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D007115" MajorTopicYN="N">Immunization Schedule</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015233" MajorTopicYN="Y">Models, Statistical</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D012424" MajorTopicYN="N">Rural Population</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D014195" MajorTopicYN="N">Travel</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D014505" MajorTopicYN="N">Urban Population</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D014611" MajorTopicYN="N">Vaccination</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015004" MajorTopicYN="N">Yellow Fever</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName>
<QualifierName UI="Q000635" MajorTopicYN="N">transmission</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015005" MajorTopicYN="N">Yellow fever virus</DescriptorName>
<QualifierName UI="Q000302" MajorTopicYN="Y">isolation & purification</QualifierName>
</MeshHeading>
</MeshHeadingList>
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<Year>2016</Year>
<Month>09</Month>
<Day>20</Day>
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<PubMedPubDate PubStatus="revised">
<Year>2016</Year>
<Month>10</Month>
<Day>28</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted">
<Year>2016</Year>
<Month>11</Month>
<Day>09</Day>
</PubMedPubDate>
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<Year>2016</Year>
<Month>12</Month>
<Day>27</Day>
<Hour>6</Hour>
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<PubMedPubDate PubStatus="medline">
<Year>2017</Year>
<Month>6</Month>
<Day>14</Day>
<Hour>6</Hour>
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<Month>12</Month>
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}}

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HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/RBID.i   -Sk "pubmed:28017559" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd   \
       | NlmPubMed2Wicri -a AustralieFrV1 

Wicri

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