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  2. Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital abnormalities1, 2. In July 2016, mosquito-borne ZIKV transmission was reported in the continental United States; since then, hundreds of locally acquired infections have been reported in Florida3, 4. To gain insights into the timing, source, and likely route(s) of ZIKV introduction, we tracked the virus from its first detection in Florida by sequencing ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least 4 introductions, but potentially as many as 40, contributed to the outbreak in Florida and that local transmission is likely to have started in the spring of 2016—several months before its initial detection. By analysing surveillance and genetic data, we show that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions were linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. Our study provides an understanding of how ZIKV initiates transmission in new regions.
  3. Genomic epidemiology reveals multiple introductions of Zika virus into the United States Nathan D. Grubaugh Jason T. Ladner Moritz U. G. Kraemer Gytis Dudas Amanda L. Tan Karthik Gangavarapu Michael R. Wiley Stephen White Julien Thézé Diogo M. Magnani Karla Prieto Daniel Reyes Andrea M. Bingham Lauren M. Paul Refugio Robles-Sikisaka Glenn Oliveira Darryl Pronty Carolyn M. Barcellona Hayden C. Metsky Mary Lynn Baniecki Kayla G. Barnes Bridget Chak Catherine A. Freije Adrianne Gladden-Young Andreas Gnirke Cynthia Luo Bronwyn MacInnis Christian B. Matranga Daniel J. Park James Qu Stephen F. Schaffner Christopher Tomkins-Tinch Kendra L. West Sarah M. Winnicki Shirlee Wohl Nathan L. Yozwiak Joshua Quick Joseph R. Fauver Kamran Khan Shannon E. Brent Robert C. Reiner Jr Paola N. Lichtenberger Michael J. Ricciardi Varian K. Bailey David I. Watkins Marshall R. Cone Edgar W. Kopp IV Kelly N. Hogan Andrew C. Cannons Reynald Jean Andrew J. Monaghan Robert F. Garry Nicholas J. Loman Nuno R. Faria Mario C. Porcelli Chalmers Vasquez Elyse R. Nagle Derek A. T. Cummings Danielle Stanek Andrew Rambaut Mariano Sanchez-Lockhart Pardis C. Sabeti Leah D. Gillis Scott F. Michael Trevor Bedford Oliver G. Pybus Sharon Isern Gustavo Palacios Kristian G. Andersen Affiliations Contributions Corresponding authors Nature (2017) doi:10.1038/nature22400 Received 01 February 2017 Accepted 28 April 2017 Published online 24 May 2017 These authors contributed equally to this work. Nathan D. Grubaugh, Jason T. Ladner, Moritz U. G. Kraemer, Gytis Dudas, Amanda L. Tan, Karthik Gangavarapu, Michael R. Wiley, Stephen White & Julien Thézé These authors jointly supervised this work. Pardis C. Sabeti, Leah D. Gillis, Scott F. Michael, Trevor Bedford, Oliver G. Pybus, Sharon Isern, Gustavo Palacios & Kristian G. Andersen Affiliations Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California 92037, USA Nathan D. Grubaugh, Karthik Gangavarapu, Refugio Robles-Sikisaka & Kristian G. Andersen Center for Genome Sciences, US Army Medical Research Institute of Infectious Diseases, Fort Detrick, Maryland 21702, USA Jason T. Ladner, Michael R. Wiley, Karla Prieto, Daniel Reyes, Elyse R. Nagle, Mariano Sanchez-Lockhart & Gustavo Palacios Department of Zoology, University of Oxford, Oxford OX1 3PS, UK Moritz U. G. Kraemer, Julien Thézé, Nuno R. Faria & Oliver G. Pybus Boston Children’s Hospital, Boston, Massachusetts 02115, USA Moritz U. G. Kraemer Harvard Medical School, Boston, Massachusetts 02115, USA Moritz U. G. Kraemer Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA Gytis Dudas & Trevor Bedford Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida 33965, USA Amanda L. Tan, Lauren M. Paul, Carolyn M. Barcellona, Scott F. Michael & Sharon Isern College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska 68198, USA Michael R. Wiley & Karla Prieto Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Miami, Florida 33125, USA Stephen White, Darryl Pronty & Leah D. Gillis Department of Pathology, University of Miami Miller School of Medicine, Miami, Florida 33136, USA Diogo M. Magnani, Michael J. Ricciardi, Varian K. Bailey & David I. Watkins Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska 68198, USA Daniel Reyes, Elyse R. Nagle & Mariano Sanchez-Lockhart Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, Florida 32399, USA Andrea M. Bingham & Danielle Stanek Scripps Translational Science Institute, La Jolla, California 92037, USA Glenn Oliveira & Kristian G. Andersen The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA Hayden C. Metsky, Mary Lynn Baniecki, Kayla G. Barnes, Bridget Chak, Catherine A. Freije, Adrianne Gladden-Young, Andreas Gnirke, Cynthia Luo, Bronwyn MacInnis, Christian B. Matranga, Daniel J. Park, James Qu, Stephen F. Schaffner, Christopher Tomkins-Tinch, Kendra L. West, Sarah M. Winnicki, Shirlee Wohl, Nathan L. Yozwiak & Pardis C. Sabeti Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK Joshua Quick & Nicholas J. Loman Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, Colorado 80523, USA Joseph R. Fauver Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario M5B 1T8, Canada Kamran Khan & Shannon E. Brent Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada Kamran Khan Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA Robert C. Reiner Jr Division of Infectious Diseases, University of Miami Miller School of Medicine, Miami, Florida 33136, USA Paola N. Lichtenberger Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, Florida 33612, USA Marshall R. Cone, Edgar W. Kopp IV, Kelly N. Hogan & Andrew C. Cannons Florida Department of Health in Miami-Dade County, Miami, Florida 33125, USA Reynald Jean National Center for Atmospheric Research, Boulder, Colorado 80307, USA Andrew J. Monaghan Department of Microbiology and Immunology, Tulane University School of Medicine, New Orleans, Louisiana 70112, USA Robert F. Garry Miami-Dade County Mosquito Control, Miami, Florida 33178, USA Mario C. Porcelli & Chalmers Vasquez Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida 32610, USA Derek A. T. Cummings Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK Andrew Rambaut Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA Andrew Rambaut Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA Pardis C. Sabeti Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts 02115, USA Pardis C. Sabeti Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA Pardis C. Sabeti Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, USA Kristian G. Andersen Contributions All contributions are listed in order of authorship. Designed the experiments: N.D.G., J.T.L., G.D., M.U.G.K., D.A.T.C., P.C.S., L.D.G., S.F.M., T.B., O.G.P., S.I., G.P., and K.G.A. Collected samples: A.L.T., S.W., D.M.M., A.M.B., L.M.P., D.P., C.M.B., P.N.L., M.J.R., V.K.B., D.I.W., M.R.C., E.W.K., K.N.H., A.C.C., R.J., M.C.P., C.V., D.S., L.D.G., S.F.M., and S.I. Performed the sequencing: N.D.G., M.R.W., K.P., D.R., R.R.-S., G.O., and E.R.N. Provided data, reagents, or protocols: N.D.G., J.T.L., G.D., M.U.G.K., K.G., M.R.W., R.R.-S., G.O., H.C.M., M.L.B., K.G.B., B.C., C.A.F., A.G.-Y., A.G., C.L., B.M., C.B.M., D.J.P., J. Q.U, S.F.S., C.T.-T., K.L.W., S.M.W., S.W., N.L.Y., J.Qui., J.R.F., K.K., S.E.B., A.J.M., R.F.G., N.J.L., M.C.P., C.V., P.C.S., S.F.M., and S.I. Analysed the data: N.D.G., J.T.L., G.D., M.U.G.K., K.G., J.T., J.R.F., R.C.R., N.R.F., D.A.T.C., A.R., M.S.-L., T.B., S.F.M, O.G.P., S.I., and K.G.A. Edited manuscript: G.D., M.U.G.K., J.T., S.F.S., A.R., T.B., O.G.P., S.I., and G.P. Wrote manuscript: N.D.G., J.T.L., and K.G.A. All authors read and approved the manuscript.
  4. Nature paper describing the multiple Zika introductions into Florida has been published Genomic epidemiology reveals multiple introductions of Zika virus into the United States http://www.nature.com/nature/journal/vaop/ncurrent/full/nature22400.html
  5. Report date : 2017-05-26 10:13:27 Country : Germany Disease: : Highly path. avian influenza View the full article
  6. Report date : 2017-05-26 10:49:59 Country : Vietnam Disease: : Highly path. avian influenza View the full article
  7. On 15 May 2017, the Ministry of Health and Family Welfare-Government of India (MoHFW) reported three laboratory confirmed cases of Zika virus disease in Bapunagar area, Ahmedabad District, Gujarat, State, India. View the full article
  8. Report date : 2017-05-23 00:00:00 Country : Uganda Disease: : Highly path. avian influenza View the full article
  9. Report date : 2017-05-24 14:29:47 Country : Sweden Disease: : Highly path. avian influenza View the full article
  10. On 13 May 2017, the National Health and Family Planning Commission of China (NHFPC) notified WHO of 23 additional laboratory-confirmed cases of human infection with avian influenza A(H7N9) virus in China. View the full article
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  12. Report date : 2017-05-21 00:00:00 Country : Libya Disease: : Low pathogenic avian influenza (poultry) View the full article
  13. Report date : 2017-05-22 16:51:02 Country : Egypt Disease: : Highly path. avian influenza View the full article
  14. Report date : 2017-05-22 13:41:29 Country : Russia Disease: : Highly path. avian influenza View the full article
  15. Report date : 2017-05-22 16:04:53 Country : United States of America Disease: : Low pathogenic avian influenza (poultry) View the full article
  16. Report date : 2017-05-22 11:20:51 Country : South Africa Disease: : Low pathogenic avian influenza (poultry) View the full article
  17. Report date : 2017-05-21 04:49:33 Country : Vietnam Disease: : Highly path. avian influenza View the full article
  18. Report date : 2017-05-19 17:36:34 Country : Sweden Disease: : Highly path. avian influenza View the full article
  19. Report date : 2017-05-19 11:26:05 Country : Cameroon Disease: : Highly pathogenic influenza A viruses (infection with) (non-poultry including wild birds) View the full article
  20. Report date : 2017-05-19 11:23:47 Country : Cameroon Disease: : Highly path. avian influenza View the full article
  21. Report date : 2017-05-18 00:00:00 Country : United Kingdom Disease: : Highly path. avian influenza View the full article
  22. On 5 May 2017, the National Health and Family Planning Commission of China (NHFPC) notified WHO of 24 additional laboratory-confirmed human infections with avian influenza A(H7N9) virus in China. View the full article
  23. Eur J Hum Genet. 2009 Feb; 17(2): 147–149. Published online 2008 Oct 22. doi: 10.1038/ejhg.2008.198 PMCID: PMC2986051 On Jim Watson's APOE status: genetic information is hard to hide Dale R Nyholt,1,* Chang-En Yu,2 and Peter M Visscher1 Author information ► Copyright and License information ► This article has been cited by other articles in PMC. The recent publication and release to public databases of Dr James Watson's sequenced genome,1 with the exception of all gene information about apolipoprotein E (ApoE), provides a pertinent example of the challenges concerning privacy and the complexities of informed consent in the era of personalized genomics.2 Dr Watson requested that his ApoE gene (APOE) information be redacted, citing concerns about the association that has been shown with late onset Alzheimer's disease (LOAD), which is currently incurable and claimed one of his grandmothers.3 In this letter, without any ‘analysis' of Dr Watson's genome, and thus respecting Dr Watson's wishes for APOE risk status anonymity, we highlight the challenges concerning the privacy and the complexities of informed consent by pointing out that the deletion of the APOE gene information only may not prevent accurate prediction of Dr Watson's risk for LOAD conveyed by APOE risk alleles. Specifically, linkage disequilibrium (LD) between one or multiple polymorphisms and APOE can be used to predict APOE status using advanced computational tools. Therefore, simply blanking out genotypes at known risk factors is generally not sufficient if the aim is to hide genetic information at these loci. The major APOE risk for LOAD is generally assumed to come from the ɛ2/ɛ3/ɛ4 haplotype system, with the ɛ4 allele increasing risk for the disorder and the ɛ2 allele being protective.4 The ɛ2/ɛ3/ɛ4 haplotype system is defined by two nonsynonymous single nucleotide polymorphisms (SNPs) in APOE exon 4. One is a C/T SNP (rs429358) that encodes either arginine (C) or cysteine (T) in the ApoE at amino acid 112. The second site defining this haplotype system is a C/T SNP (rs7412), which again encodes arginine (C) or cysteine (T) at ApoE amino acid 158. The allelic compositions of the commonly investigated rs429358-rs7412 haplotypes are T-T for ɛ2, T-C for ɛ3, and C-C for ɛ4. The effects of these coding variants on ApoE function are well defined.5 A recent meta-analysis of LOAD risk in Caucasians (clinic/autopsy cohorts) indicated odds ratios (OR) of 15.6 (95% CI, 10.9–22.5) and 4.3 (95% CI, 3.3–5.5) for APOE ɛ4 homozygotes and ɛ4/ɛ3heterozygotes respectively, compared to ɛ3 homozygotes.6 The meta-analytic odds ratios in population-based Caucasian samples were 11.8 (95% CI, 7.0–19.8) and 2.8 (95% CI, 2.3–3.5), respectively.6 In a large Rotterdam (Netherlands), population-based prospective study of people aged 55 years or above, it was estimated that 17% of the overall risk of AD could be attributed to the ɛ4 allele, with 3% (95% CI, 0–6%) of cases attributed to the ɛ4/ɛ4 genotype, and 14% (95% CI, 7–21%) to the ɛ4/ɛ3 genotype.7 A recent investigation of LD for 50 SNPs in and surrounding APOE in 550 Caucasians identified multiple SNPs in the TOMM40 gene ∼15 kb upstream of APOE, and at least one SNP in the other surrounding genes LU, PVRL2, APOC1, APOC4 and CLPTM1 were associated with LOAD risk.8 In particular, the C allele of SNP rs157581 in TOMM40 is in strong LD (r2>0.6) with the C allele of rs429358 in APOE, which defines the ɛ4 allele. For an additive (allelic) logit model, the OR for the presence of ɛ4 versus the status of LOAD was estimated to be 4.1, whereas the OR for LOAD status using the alleles of rs157581 was 2.9.8Furthermore, using data sets such as those of Yu et al8 and SNPs identified in the surrounding regions of APOE in Dr Watson's sequence, haplotype phasing software could be utilized to easily and accurately predict Dr Watson's APOE risk haplotype status. In addition, even if genotypes for non-APOE SNPs conveying LOAD risk are not listed in Dr Watson's sequence (ie, because of low sequence coverage), as in the case of TOMM40 SNP rs157581, it would be straightforward to predict Dr Watson's APOE risk status by exclusively using publicly available data, such as HapMap data. Specifically, although the LOAD high-risk APOE SNPs rs429358 and rs7412 and TOMM40 SNP rs157581 are not in the HapMap, a recent genome-wide association screen using 502 627 SNPs performed in 1086 histopathologically verified LOAD cases (n=664) and controls (n=442), identified HapMap SNP rs4420638, located in the APOC1 gene 14 kb downstream of the APOE ɛ4 allele, which has a powerful association with LOAD.9 Indeed, the association between LOAD and the G allele of rs4420638 (P=1 × 10−39) is similar to the association with the APOE ɛ4 allele (rs429358 C allele) itself (P=1 × 10−44), with additive allelic ORs of approximately 4 and 5, respectively.9, 10 Coon et al9 report strong LD between rs4420638 and rs429358 at D′=0.86, which implies an r2 of approximately 0.60 based on Caucasian allele frequency estimates for these SNPs listed in dbSNP. We note that Dr Watson received genetic counseling and after being made aware of the privacy risks associated with public data broadcast, Dr Watson decided to share his personal genome by releasing it into a publicly accessible scientific database (for full details concerning Dr Watson and Protection of human subjects, Returning research results to research participants, and Data release and data flow, see Box 1 of Wheeler et al1). Nevertheless, during the preparation of this Letter, we contacted Dr Watson and colleagues in December 2007 and February 2008 informing them of the possibility of inferring his risk for LOAD conveyed by APOE risk alleles using surrounding SNP data. As a consequence, the online James Watson Genome Browser (JWGB) has nominally removed all data from the 2-Mb region surrounding APOE. To demonstrate our point that genetic information is hard to hide, without contravening Dr Watson's wishes for APOE risk status anonymity (see Box 1 of Wheeler et al1), we utilized SNP genotypes identified in Dr J Craig Venter's genome sequence.11 Furthermore, Dr Venter's sequence data reports that he is heterozygote for both the LOAD high-risk APOE SNP rs429358 (T/C) and APOC1 SNP rs4420638 (A/G). Briefly, genotype imputation was performed using the MACH (version 1.0.16) computer program,12 HapMap (CEU)-phased haplotype data (encompassing 144 SNPs) and Dr Venter's genotypes listed for the 200-kb region surrounding rs4420638 (encompassing all 144 HapMap SNPs). Following the two-step approach outlined in the MACH online tutorial and after excluding Dr Venter's genotype data for rs4420638 and all APOE SNPs, we were able to correctly impute Dr Venter's rs4420638 genotype as A/G. The posterior probabilities for Dr Venter's rs4420638 genotype being A/A, A/G or G/G were estimated to be 0.008, 0.992 and 0.000, respectively. The high accuracy of Dr Venter's imputed rs4420638 genotype exemplifies the utility of imputing APOE genetic risk for LOAD. Finally, although the deletion of 2 Mb is likely excessive for the surrounding APOE region (based on reported LD), as more detailed characterization of the human genome comes to light, it will become even more necessary to redact substantial regions surrounding identified genetic risk variants to avoid the indirect, though accurate, estimation of genetic risk such as those we detail above. For example, in a recent study, using gene expression profiling of Epstein–Barr virus-transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium, Stranger et al13 reported many instances of the most significant SNP associated with gene expression being located often 100 s of kb and up to 1 Mb outside of the gene transcript, with additional, less significant SNPs, although still useful in estimating risk, being located even further from the gene. Moreover, the potential for indirect estimation of risk will further increase as additional and more detailed genome-wide association studies are performed (which identify new risk loci) and individual human genomes are sequenced. In summary, hiding genetic information in an otherwise fully disclosed genome sequence is not straightforward because of the availability of genomic data in the public domain that can be used to predict the missing data. We believe the potential for such indirect estimation of genetic risk has considerable relevance to concerns about privacy, confidentiality, discriminatory and defamatory use of genetic data, and the complexities of informed consent for both research participants and their close genetic relatives in the era of personalized genomics. Acknowledgments This study was supported by Australian NHMRC Grants 389892, 339462 and 442915 and Australian Research Council Grant DP0770096. Footnotes Conflict of interest None declared. Web Resources The URL for data presented here are as follows: James Watson Genome Browser (JWGB), http://jimwatsonsequence.cshl.edu/cgi-perl/gbrowse/jwsequence/ James Watson Genome Browser (JWGB); local copy installation download, ftp://jimwatsonsequence.cshl.edu/jimwatsonsequence/gbrowse/ Dr J Craig Venter's genome sequence, http://huref.jcvi.org/ MACH (version 1.0.16) computer program, http://www.sph.umich.edu/csg/abecasis/MACH HapMap (CEU) phased haplotype data (encompassing 144 SNPs), http://www.hapmap.org/cgi-perl/gbrowse/hapmap_B35/ Dr Venter's genotypes (downloaded on June 19, 2008), ftp://ftp.jcvi.org/pub/data/huref/HuRef.InternalHuRef-NCBI.gff MACH online tutorial, http://www.sph.umich.edu/csg/abecasis/MACH/tour/imputation.html References Wheeler DA, Srinivasan M, Egholm M, et al. The complete genome of an individual by massively parallel DNA sequencing. Nature. 2008;452:872–876. [PubMed] McGuire AL, Caulfield T, Cho MK. Research ethics and the challenge of whole-genome sequencing. Nat Rev Genet. 2008;9:152–156. [PMC free article] [PubMed] Check E. James Watson's genome sequenced – discoverer of the double helix blazes trail for personal genomics Nature News 2008. doi:10.1038/news070528-10 :http://www.nature.com/news/2007/070528/full/news070528-10.html [Cross Ref] Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA. 1997;278:1349–1356. [PubMed] Raber J, Huang Y, Ashford JW. ApoE genotype accounts for the vast majority of AD risk and AD pathology. Neurobiol Aging. 2004;25:641–650. [PubMed] Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet. 2007;39:17–23. [PubMed] Slooter AJ, Cruts M, Kalmjin S, et al. Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: the Rotterdam Study. Ann Neurol. 1998;55:964–968. [PubMed] Yu CE, Seltman H, Peskind ER, et al. Comprehensive analysis of APOE and selected proximate markers for late-onset Alzheimer's disease: patterns of linkage disequilibrium and disease/marker association. Genomics. 2007;89:655–665. [PMC free article] [PubMed] Coon KD, Myers AJ, Craig DW, et al. A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. J Clin Psychiatry. 2007;68:613–618. [PubMed] Reiman EM. In this issue: entering the era of high-density genome-wide association studies. J Clin Psychiatry. 2007;68:611–612. [PubMed] Levy S, Sutton G, Ng PC, et al. The diploid genome sequence of an individual human. PLoS Biol. 2007;5:e254. [PMC free article] [PubMed] Li Y, Abecasis GR. Mach 1.0: rapid haplotype reconstruction and missing genotype inference. Am J Hum Genet. 2006;S79:2290. Stranger BE, Nica AC, Forrest MS, et al. Population genomics of human gene expression. Nat Genet. 2007;39:1217–1224. [PMC free article] [PubMed] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2986051/ Articles from European Journal of Human Genetics are provided here courtesy of Nature Publishing Group
  24. Report date : 2017-05-17 14:03:52 Country : Russia Disease: : Highly path. avian influenza View the full article
  25. Report date : 2017-05-18 09:29:27 Country : Vietnam Disease: : Highly path. avian influenza View the full article
  26. Report date : 2017-05-17 17:08:24 Country : Netherlands Disease: : Highly path. avian influenza View the full article
  27. Report date : 2017-05-17 15:28:56 Country : Netherlands Disease: : Highly path. avian influenza View the full article
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