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Title:   Author  item
                                            NELSON, MARTHA - Fogarty International Centeritem
                                            VIBOUD, CECILE - Fogarty International Centeritem
                                            Baker, Amyitem
                                            CULHANE, MARIE - University Of Minnesotaitem
                                            DETMER, SUSAN - University Of Saskatchewanitem
                                            WENTWORTH, DAVID - J Craig Venter Instituteitem
                                            RAMBAUT, ANDREW - University Of Edinburghitem
                                            SUCHARD, MARC A - University Of Californiaitem
                                            HOLMES, EDWARD - University Of Sydneyitem
                                            LEMEY, PHILIPPE - University Of Leuven
  Submitted to: Nature Communications
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 2/19/2015
                                    Publication  Date: 3/27/2015
                                    Citation: Nelson, M.I., Viboud, C., Vincent, A.L., Culhane, M.R., Detmer, S.E., Wentworth, D.E., Rambaut, A., Suchard, M.A., Holmes, E.C., Lemey, P. 2015. Global migration of influenza A viruses in swine. Nature Communications. 6:6696.Interpretive Summary: Despite major advances in genomic sequencing and investment in pandemic influenza research, we know little about the ecology and circulation of influenza viruses in swine, and the geographic origins of the 2009 pandemic H1N1 influenza virus within its animal reservoir host remain unclear. This lack of knowledge owes to gaps in our understanding of influenza virus evolution and ecology in swine populations globally. Here, we use a combination of genetic, population, and live swine trade data to (a) characterize patterns in the dispersal of influenza viruses in swine populations globally, (b) demonstrate the importance of live swine trade in driving these patterns, and (c) predict the probability of swine influenza virus invasion in countries with little or no data.
                                Technical Abstract: The emergence of the 2009 A/H1N1 pandemic virus underscores the importance of understanding how influenza A viruses evolve in swine on a global scale. To reveal the frequency, patterns and drivers of the spread of swine influenza virus globally, we conducted the largest phylogenetic analysis of swine influenza virus sequence data undertaken to date, integrating demographic and swine trade data. Using phylogenetic and modeling approaches, we demonstrate the importance of the asymmetrical global live swine trade on the evolution of influenza virus diversity in swine, with Europe and North America acting as global source populations. The size of a country’s swine population was not found to be an important independent factor, as exemplified by China, which hosts the world’s largest swine population but has relatively little outgoing swine trade and does not appear to be a major source of viral diversity in neighboring Asian countries or globally. Rather, Japan, Thailand, Vietnam, and South Korea independently import influenza viruses from Europe and North America via long-distance live swine trade. As an extension of these empirical patterns, we built a meta-population simulation model for the global spread of swine influenza viruses that incorporated trade data and could estimate the likelihood of emergence of the H1N1 pandemic virus in swine in the years leading up to 2009. We find that co-invasion is most likely in East and South-East Asia, although the probability of onward international spread in swine is low, and surveillance should be strengthened in hotspots for viral diversity that currently lack data, such as Russia. Knowledge of the global linkages between swine influenza virus populations has important implications for designing efficient surveillance strategies in resource-limited settings and predicting future disease threats.


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