Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies
Identifieur interne : 001B45 ( Ncbi/Merge ); précédent : 001B44; suivant : 001B46Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies
Auteurs : Gerardo Chowell [États-Unis] ; Julie M. Cleaton ; Cecile Viboud [États-Unis]Source :
- The Journal of Infectious Diseases [ 0022-1899 ] ; 2016.
Descripteurs français
- KwdFr :
- Afrique de l'Ouest (épidémiologie), Analyse spatio-temporelle, Collecte de données, Fièvre hémorragique à virus Ebola (transmission), Fièvre hémorragique à virus Ebola (épidémiologie), Humains, Infections à coronavirus (transmission), Infections à coronavirus (épidémiologie), Internet, Nombre de reproduction de base, République de Corée (épidémiologie), Épidémiosurveillance.
- MESH :
English descriptors
- KwdEn :
- Africa, Western (epidemiology), Basic Reproduction Number, Coronavirus Infections (epidemiology), Coronavirus Infections (transmission), Data Collection, Epidemiological Monitoring, Hemorrhagic Fever, Ebola (epidemiology), Hemorrhagic Fever, Ebola (transmission), Humans, Internet, Republic of Korea (epidemiology), Spatio-Temporal Analysis.
- MESH :
Abstract
The paucity of traditional epidemiological data during epidemic emergencies calls for alternative data streams to characterize the key features of an outbreak, including the nature of risky exposures, the reproduction number, and transmission heterogeneities. We illustrate the potential of Internet data streams to improve preparedness and response in outbreak situations by drawing from recent work on the 2014–2015 Ebola epidemic in West Africa and the 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea. We show that Internet reports providing detailed accounts of epidemiological clusters are particularly useful to characterize time trends in the reproduction number. Moreover, exposure patterns based on Internet reports align with those derived from epidemiological surveillance data on MERS and Ebola, underscoring the importance of disease amplification in hospitals and during funeral rituals (associated with Ebola), prior to the implementation of control interventions. Finally, we discuss future developments needed to generalize Internet-based approaches to study transmission dynamics.
Url:
DOI: 10.1093/infdis/jiw356
PubMed: 28830110
PubMed Central: 5144900
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PMC:5144900Le document en format XML
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<front><div type="abstract" xml:lang="en"><title>Abstract</title>
<p>The paucity of traditional epidemiological data during epidemic emergencies calls for alternative data streams to characterize the key features of an outbreak, including the nature of risky exposures, the reproduction number, and transmission heterogeneities. We illustrate the potential of Internet data streams to improve preparedness and response in outbreak situations by drawing from recent work on the 2014–2015 Ebola epidemic in West Africa and the 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea. We show that Internet reports providing detailed accounts of epidemiological clusters are particularly useful to characterize time trends in the reproduction number. Moreover, exposure patterns based on Internet reports align with those derived from epidemiological surveillance data on MERS and Ebola, underscoring the importance of disease amplification in hospitals and during funeral rituals (associated with Ebola), prior to the implementation of control interventions. Finally, we discuss future developments needed to generalize Internet-based approaches to study transmission dynamics.</p>
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<double pmid="28830110"><pmc><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies</title>
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<affiliation><nlm:aff id="aff1"><addr-line>School of Public Health</addr-line>
,<institution>Georgia State University</institution>
,<addr-line>Atlanta</addr-line>
</nlm:aff>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff2"><addr-line>Division of International Epidemiology and Population Studies</addr-line>
,<institution>Fogarty International Center, National Institutes of Health</institution>
,<addr-line>Bethesda, Maryland</addr-line>
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</author>
<author><name sortKey="Cleaton, Julie M" sort="Cleaton, Julie M" uniqKey="Cleaton J" first="Julie M." last="Cleaton">Julie M. Cleaton</name>
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,<institution>Georgia State University</institution>
,<addr-line>Atlanta</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Viboud, Cecile" sort="Viboud, Cecile" uniqKey="Viboud C" first="Cecile" last="Viboud">Cecile Viboud</name>
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,<institution>Fogarty International Center, National Institutes of Health</institution>
,<addr-line>Bethesda, Maryland</addr-line>
</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">Maryland</region>
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<idno type="RBID">PMC:5144900</idno>
<idno type="doi">10.1093/infdis/jiw356</idno>
<date when="2016">2016</date>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies</title>
<author><name sortKey="Chowell, Gerardo" sort="Chowell, Gerardo" uniqKey="Chowell G" first="Gerardo" last="Chowell">Gerardo Chowell</name>
<affiliation><nlm:aff id="aff1"><addr-line>School of Public Health</addr-line>
,<institution>Georgia State University</institution>
,<addr-line>Atlanta</addr-line>
</nlm:aff>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff2"><addr-line>Division of International Epidemiology and Population Studies</addr-line>
,<institution>Fogarty International Center, National Institutes of Health</institution>
,<addr-line>Bethesda, Maryland</addr-line>
</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">Maryland</region>
</placeName>
<wicri:cityArea>Bethesda</wicri:cityArea>
</affiliation>
</author>
<author><name sortKey="Cleaton, Julie M" sort="Cleaton, Julie M" uniqKey="Cleaton J" first="Julie M." last="Cleaton">Julie M. Cleaton</name>
<affiliation><nlm:aff id="aff1"><addr-line>School of Public Health</addr-line>
,<institution>Georgia State University</institution>
,<addr-line>Atlanta</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Viboud, Cecile" sort="Viboud, Cecile" uniqKey="Viboud C" first="Cecile" last="Viboud">Cecile Viboud</name>
<affiliation wicri:level="2"><nlm:aff id="aff2"><addr-line>Division of International Epidemiology and Population Studies</addr-line>
,<institution>Fogarty International Center, National Institutes of Health</institution>
,<addr-line>Bethesda, Maryland</addr-line>
</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">Maryland</region>
</placeName>
<wicri:cityArea>Bethesda</wicri:cityArea>
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</author>
</analytic>
<series><title level="j">The Journal of Infectious Diseases</title>
<idno type="ISSN">0022-1899</idno>
<idno type="eISSN">1537-6613</idno>
<imprint><date when="2016">2016</date>
</imprint>
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<front><div type="abstract" xml:lang="en"><title>Abstract</title>
<p>The paucity of traditional epidemiological data during epidemic emergencies calls for alternative data streams to characterize the key features of an outbreak, including the nature of risky exposures, the reproduction number, and transmission heterogeneities. We illustrate the potential of Internet data streams to improve preparedness and response in outbreak situations by drawing from recent work on the 2014–2015 Ebola epidemic in West Africa and the 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea. We show that Internet reports providing detailed accounts of epidemiological clusters are particularly useful to characterize time trends in the reproduction number. Moreover, exposure patterns based on Internet reports align with those derived from epidemiological surveillance data on MERS and Ebola, underscoring the importance of disease amplification in hospitals and during funeral rituals (associated with Ebola), prior to the implementation of control interventions. Finally, we discuss future developments needed to generalize Internet-based approaches to study transmission dynamics.</p>
</div>
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<pubmed><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies.</title>
<author><name sortKey="Chowell, Gerardo" sort="Chowell, Gerardo" uniqKey="Chowell G" first="Gerardo" last="Chowell">Gerardo Chowell</name>
<affiliation><nlm:affiliation>School of Public Health, Georgia State University, Atlanta.</nlm:affiliation>
<wicri:noCountry code="subField">Atlanta</wicri:noCountry>
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<author><name sortKey="Viboud, Cecile" sort="Viboud, Cecile" uniqKey="Viboud C" first="Cecile" last="Viboud">Cecile Viboud</name>
<affiliation wicri:level="2"><nlm:affiliation>Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
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<wicri:cityArea>Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda</wicri:cityArea>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Elucidating Transmission Patterns From Internet Reports: Ebola and Middle East Respiratory Syndrome as Case Studies.</title>
<author><name sortKey="Chowell, Gerardo" sort="Chowell, Gerardo" uniqKey="Chowell G" first="Gerardo" last="Chowell">Gerardo Chowell</name>
<affiliation><nlm:affiliation>School of Public Health, Georgia State University, Atlanta.</nlm:affiliation>
<wicri:noCountry code="subField">Atlanta</wicri:noCountry>
</affiliation>
</author>
<author><name sortKey="Cleaton, Julie M" sort="Cleaton, Julie M" uniqKey="Cleaton J" first="Julie M" last="Cleaton">Julie M. Cleaton</name>
<affiliation><nlm:affiliation>School of Public Health, Georgia State University, Atlanta.</nlm:affiliation>
<wicri:noCountry code="subField">Atlanta</wicri:noCountry>
</affiliation>
</author>
<author><name sortKey="Viboud, Cecile" sort="Viboud, Cecile" uniqKey="Viboud C" first="Cecile" last="Viboud">Cecile Viboud</name>
<affiliation wicri:level="2"><nlm:affiliation>Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland.</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">Maryland</region>
</placeName>
<wicri:cityArea>Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda</wicri:cityArea>
</affiliation>
</author>
</analytic>
<series><title level="j">The Journal of infectious diseases</title>
<idno type="eISSN">1537-6613</idno>
<imprint><date when="2016" type="published">2016</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Africa, Western (epidemiology)</term>
<term>Basic Reproduction Number</term>
<term>Coronavirus Infections (epidemiology)</term>
<term>Coronavirus Infections (transmission)</term>
<term>Data Collection</term>
<term>Epidemiological Monitoring</term>
<term>Hemorrhagic Fever, Ebola (epidemiology)</term>
<term>Hemorrhagic Fever, Ebola (transmission)</term>
<term>Humans</term>
<term>Internet</term>
<term>Republic of Korea (epidemiology)</term>
<term>Spatio-Temporal Analysis</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Afrique de l'Ouest (épidémiologie)</term>
<term>Analyse spatio-temporelle</term>
<term>Collecte de données</term>
<term>Fièvre hémorragique à virus Ebola (transmission)</term>
<term>Fièvre hémorragique à virus Ebola (épidémiologie)</term>
<term>Humains</term>
<term>Infections à coronavirus (transmission)</term>
<term>Infections à coronavirus (épidémiologie)</term>
<term>Internet</term>
<term>Nombre de reproduction de base</term>
<term>République de Corée (épidémiologie)</term>
<term>Épidémiosurveillance</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Africa, Western</term>
<term>Coronavirus Infections</term>
<term>Hemorrhagic Fever, Ebola</term>
<term>Republic of Korea</term>
</keywords>
<keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Coronavirus Infections</term>
<term>Hemorrhagic Fever, Ebola</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Afrique de l'Ouest</term>
<term>Fièvre hémorragique à virus Ebola</term>
<term>Infections à coronavirus</term>
<term>République de Corée</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Basic Reproduction Number</term>
<term>Data Collection</term>
<term>Epidemiological Monitoring</term>
<term>Humans</term>
<term>Internet</term>
<term>Spatio-Temporal Analysis</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Analyse spatio-temporelle</term>
<term>Collecte de données</term>
<term>Humains</term>
<term>Internet</term>
<term>Nombre de reproduction de base</term>
<term>Épidémiosurveillance</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The paucity of traditional epidemiological data during epidemic emergencies calls for alternative data streams to characterize the key features of an outbreak, including the nature of risky exposures, the reproduction number, and transmission heterogeneities. We illustrate the potential of Internet data streams to improve preparedness and response in outbreak situations by drawing from recent work on the 2014-2015 Ebola epidemic in West Africa and the 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea. We show that Internet reports providing detailed accounts of epidemiological clusters are particularly useful to characterize time trends in the reproduction number. Moreover, exposure patterns based on Internet reports align with those derived from epidemiological surveillance data on MERS and Ebola, underscoring the importance of disease amplification in hospitals and during funeral rituals (associated with Ebola), prior to the implementation of control interventions. Finally, we discuss future developments needed to generalize Internet-based approaches to study transmission dynamics.</div>
</front>
</TEI>
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