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      Establishment and cryptic transmission of Zika virus in Brazil and the Americas.

      1 , 2 , 3 , 4 , 1 , 5 , 5 , 6 , 1 , 7 , 8 , 1 , 9 , 10 , 3 , 2 , 2 , 11 , 1 , 12 , 13 , 1 , 14 , 15 , 16 , 17 , 18 , 19 , 18 , 20 , 18 , 17 , 21 , 22 , 23 , 23 , 24 , 24 , 25 , 25 , 26 , 27 , 28 , 29 , 29 , 29 , 2 , 2 , 2 , 5 , 30 , 30 , 31 , 30 , 32 , 33 , 33 , 33 , 33 , 34 , 34 , 34 , 35 , 34 , 36 , 34 , 37 , 37 , 37 , 38 , 39 , 40 , 4 , 4 , 41 , 4 , 42 , 4 ,   43 , 44 , 45 , 7 , 2 , 46 , 4 , 5 , 3 , 1 , 47
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          Abstract

          Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 2016) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 2016). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus.

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          Most cited references20

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          Is Open Access

          First report of autochthonous transmission of Zika virus in Brazil

          In the early 2015, several cases of patients presenting symptoms of mild fever, rash, conjunctivitis and arthralgia were reported in the northeastern Brazil. Although all patients lived in a dengue endemic area, molecular and serological diagnosis for dengue resulted negative. Chikungunya virus infection was also discarded. Subsequently, Zika virus (ZIKV) was detected by reverse transcription-polymerase chain reaction from the sera of eight patients and the result was confirmed by DNA sequencing. Phylogenetic analysis suggests that the ZIKV identified belongs to the Asian clade. This is the first report of ZIKV infection in Brazil.
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            Choosing appropriate substitution models for the phylogenetic analysis of protein-coding sequences.

            Although phylogenetic inference of protein-coding sequences continues to dominate the literature, few analyses incorporate evolutionary models that consider the genetic code. This problem is exacerbated by the exclusion of codon-based models from commonly employed model selection techniques, presumably due to the computational cost associated with codon models. We investigated an efficient alternative to standard nucleotide substitution models, in which codon position (CP) is incorporated into the model. We determined the most appropriate model for alignments of 177 RNA virus genes and 106 yeast genes, using 11 substitution models including one codon model and four CP models. The majority of analyzed gene alignments are best described by CP substitution models, rather than by standard nucleotide models, and without the computational cost of full codon models. These results have significant implications for phylogenetic inference of coding sequences as they make it clear that substitution models incorporating CPs not only are a computationally realistic alternative to standard models but may also frequently be statistically superior.
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              Anticipating the international spread of Zika virus from Brazil.

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                Author and article information

                Journal
                Nature
                Nature
                Springer Nature
                1476-4687
                0028-0836
                May 24 2017
                Affiliations
                [1 ] Department of Zoology, University of Oxford, Oxford OX1 3SY, UK.
                [2 ] Evandro Chagas Institute, Ministry of Health, Ananindeua, Brazil.
                [3 ] Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK.
                [4 ] Department of Infectious Disease, School of Medicine &Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil.
                [5 ] Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Bahia, Brazil.
                [6 ] University of Rome Tor Vergata, Rome, Italy.
                [7 ] Harvard Medical School, Boston, Massachusetts, USA.
                [8 ] Boston Children's Hospital, Boston, Massachusetts, USA.
                [9 ] Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
                [10 ] Department of Epidemiology, University of Washington, Seattle, Washington, USA.
                [11 ] Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
                [12 ] Mathematical Modelling of Infectious Diseases and Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France.
                [13 ] Centre National de la Recherche Scientifique, URA3012, Paris, France.
                [14 ] Coordenação dos Laboratórios de Saúde (CGLAB/DEVIT/SVS), Ministry of Health, Brasília, Brazil.
                [15 ] Coordenação Geral de Vigilância e Resposta às Emergências em Saúde Pública (CGVR/DEVIT), Ministry of Health, Brasília, Brazil.
                [16 ] Center of Data and Knowledge Integration for Health (CIDACS), Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil.
                [17 ] Departamento de Vigilância das Doenças Transmissíveis, Ministry of Health, Brasilia, Brazil.
                [18 ] Coordenação Geral dos Programas de Controle e Prevenção da Malária e das Doenças Transmitidas pelo Aedes, Ministry of Health, Brasília, Brazil.
                [19 ] Pan American Health Organization (PAHO), Buenos Aires, Argentina.
                [20 ] Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Brazil.
                [21 ] Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
                [22 ] University of Nottingham, Nottingham, UK.
                [23 ] Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California 92037, USA.
                [24 ] Departments of Laboratory Medicine and Medicine &Infectious Diseases, University of California, San Francisco, California, USA.
                [25 ] División de Laboratorios de Vigilancia e Investigación Epidemiológica, Instituto Mexicano del Seguro Social, Ciudad de México, Mexico.
                [26 ] Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
                [27 ] Instituto Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Brazil.
                [28 ] Paul-Ehrlich-Institut, Langen, Germany.
                [29 ] Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro, Brazil.
                [30 ] Laboratório Central de Saúde Pública do Estado do Rio Grande do Norte, Natal, Brazil.
                [31 ] Universidade Potiguar do Rio Grande do Norte, Natal, Brazil.
                [32 ] Faculdade Natalense de Ensino e Cultura, Rio Grande do Norte, Natal, Brazil.
                [33 ] Laboratório Central de Saúde Pública do Estado da Paraíba, João Pessoa, Brazil.
                [34 ] Fundação Oswaldo Cruz (FIOCRUZ), Recife, Pernambuco, Brazil.
                [35 ] Department of Microbiology, Immunology &Pathology, Colorado State University, Fort Collins, Colorado 80523, USA.
                [36 ] Section Clinical Tropical Medicine, Department for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
                [37 ] Laboratório Central de Saúde Pública do Estado de Alagoas, Maceió, Brazil.
                [38 ] Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil.
                [39 ] Secretaria de Saúde de Feira de Santana, Feira de Santana, Bahia, Brazil.
                [40 ] Universidade Federal do Amazonas, Manaus, Brazil.
                [41 ] Hospital São Francisco, Ribeirão Preto, Brazil.
                [42 ] Universidade Federal do Tocantins, Palmas, Brazil.
                [43 ] University of Sydney, Sydney, Australia.
                [44 ] Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
                [45 ] Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA.
                [46 ] Department of Pathology, University of Texas Medical Branch, Galveston, Texas 77555, USA.
                [47 ] Metabiota, San Francisco, California 94104, USA.
                Article
                nature22401
                10.1038/nature22401
                28538727
                ce182302-3108-4577-9bcf-699667a093c7
                History

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