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      Global and Local Persistence of Influenza A(H5N1) Virus

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          Abstract

          An understanding of the global migration dynamics of highly pathogenic avian influenza A(H5N1) virus is helpful for surveillance and disease prevention. To characterize the migration network of this virus, we used genetic analysis, which supported a global persistence model in which each of 9 regions acts to some extent as a source. Siberia is the major hub for the dispersal of the virus. Southeast Asia and Africa are major sources of genetically and antigenically novel strains. We found evidence of local persistence of the virus in Southeast Asia and Africa, which is rare for human influenza A viruses. The differences in migration dynamics between avian and human influenza viruses might help with the design of region-specific surveillance efforts and the selection of vaccine candidates.

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          Most cited references25

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          Dating of the human-ape splitting by a molecular clock of mitochondrial DNA.

          A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed. This method takes into account effectively the information contained in a set of DNA sequence data. The molecular clock of mitochondrial DNA (mtDNA) was calibrated by setting the date of divergence between primates and ungulates at the Cretaceous-Tertiary boundary (65 million years ago), when the extinction of dinosaurs occurred. A generalized least-squares method was applied in fitting a model to mtDNA sequence data, and the clock gave dates of 92.3 +/- 11.7, 13.3 +/- 1.5, 10.9 +/- 1.2, 3.7 +/- 0.6, and 2.7 +/- 0.6 million years ago (where the second of each pair of numbers is the standard deviation) for the separation of mouse, gibbon, orangutan, gorilla, and chimpanzee, respectively, from the line leading to humans. Although there is some uncertainty in the clock, this dating may pose a problem for the widely believed hypothesis that the pipedal creature Australopithecus afarensis, which lived some 3.7 million years ago at Laetoli in Tanzania and at Hadar in Ethiopia, was ancestral to man and evolved after the human-ape splitting. Another likelier possibility is that mtDNA was transferred through hybridization between a proto-human and a proto-chimpanzee after the former had developed bipedalism.
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            Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach.

            A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source-sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.
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              Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics.

              Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective population size. Temporal variation of this quantity characterizes the demographic history of a population. Because researchers are rarely able to choose a priori a deterministic model describing effective population size dynamics for data at hand, nonparametric curve-fitting methods based on multiple change-point (MCP) models have been developed. We propose an alternative to change-point modeling that exploits Gaussian Markov random fields to achieve temporal smoothing of the effective population size in a Bayesian framework. The main advantage of our approach is that, in contrast to MCP models, the explicit temporal smoothing does not require strong prior decisions. To approximate the posterior distribution of the population dynamics, we use efficient, fast mixing Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. In a simulation study, we demonstrate that the proposed temporal smoothing method, named Bayesian skyride, successfully recovers "true" population size trajectories in all simulation scenarios and competes well with the MCP approaches without evoking strong prior assumptions. We apply our Bayesian skyride method to 2 real data sets. We analyze sequences of hepatitis C virus contemporaneously sampled in Egypt, reproducing all key known aspects of the viral population dynamics. Next, we estimate the demographic histories of human influenza A hemagglutinin sequences, serially sampled throughout 3 flu seasons.
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                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                August 2014
                : 20
                : 8
                : 1287-1295
                Affiliations
                [1]Chinese Academy of Sciences, Shenzhen, China (X. Li);
                [2]Taishan Medical College, Taian, Shandong, China (Z. Zhang, A. Yu, W. Shi);
                [3]Chinese Academy of Sciences, Beijing, China (X. Li, W. Zheng, Y. Zhang, C. Zhu, F. Lei);
                [4]University of Sydney, Sydney, New South Wales, Australia (S.Y.W. Ho);
                [5]University College Dublin, Dublin, Ireland (M.J. Carr)
                [1 ]These authors contributed equally to this article.
                Author notes
                Address for correspondence: Weifeng Shi, Institute of Pathogen Biology, School of Basic Medical Sciences, Taishan Medical College, Yingshengdonglu 2, Taian 271000, Shandong, China; email: wfshi@ 123456tsmc.edu.cn
                Article
                13-0910
                10.3201/eid2008.130910
                4111173
                25061965
                aea16f3a-fa9d-44ed-bf69-ea8801ea1265
                History
                Categories
                Research
                Research

                Infectious disease & Microbiology
                h5n1,avian influenza,migration network,persistence,source,influenza,viruses

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