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2014-02-20Zeitschriftenartikel DOI: 10.1371/journal.ppat.1003932
Unifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2
dc.contributor.authorLemey, Philippe
dc.contributor.authorRambaut, Andrew
dc.contributor.authorBedford, Trevor
dc.contributor.authorFaria, Nuno
dc.contributor.authorBielejec, Filip
dc.contributor.authorBaele, Guy
dc.contributor.authorRussell, Colin A.
dc.contributor.authorSmith, Derek J.
dc.contributor.authorPybus, Oliver G.
dc.contributor.authorBrockmann, Dirk
dc.contributor.authorSuchard, Marc A.
dc.date.accessioned2018-05-07T17:37:08Z
dc.date.available2018-05-07T17:37:08Z
dc.date.created2014-04-10
dc.date.issued2014-02-20none
dc.identifier.otherhttp://edoc.rki.de/oa/articles/reDHH8WjB34ho/PDF/24X6Ln8Jx7pqQ.pdf
dc.identifier.urihttp://edoc.rki.de/176904/1860
dc.description.abstractInformation on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.eng
dc.language.isoeng
dc.publisherRobert Koch-Institut
dc.subject.ddc610 Medizin
dc.titleUnifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2
dc.typeperiodicalPart
dc.identifier.urnurn:nbn:de:0257-10036138
dc.identifier.doi10.1371/journal.ppat.1003932
dc.identifier.doihttp://dx.doi.org/10.25646/1785
local.edoc.container-titlePLoS Pathogens
local.edoc.container-textLemey P, Rambaut A, Bedford T, Faria N, Bielejec F, et al. (2014) Unifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2. PLoS Pathog 10(2): e1003932.
local.edoc.fp-subtypeArtikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttp://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.1003932
local.edoc.container-publisher-namePublic Library of Science
local.edoc.container-volume10
local.edoc.container-issue2
local.edoc.container-year2014

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