Assessing the role of live poultry trade in community-structured transmission of avian influenza in China

Significance The emergence and transmission of avian influenza viruses (AIVs) pose a threat to public health and result in enormous economic losses. Here we discover an association between the community structure of the poultry trade network and AIV transmission in China by combining virus genomes and statistical modeling of the poultry trade. Importantly, we are able to “replicate” this finding by comparing the dynamics of three strains of AIV (H5N1, H7N9, and H5N6) that currently cocirculate in poultry in China. Given the detection of a continuous process of AIV geographic spread among poultry, our results indicate that at the national scale there are repeatable and potentially predictable patterns that can be used to shape future strategies for AIV control and prevention. The live poultry trade is thought to play an important role in the spread and maintenance of highly pathogenic avian influenza A viruses (HP AIVs) in Asia. Despite an abundance of small-scale observational studies, the role of the poultry trade in disseminating AIV over large geographic areas is still unclear, especially for developing countries with complex poultry production systems. Here we combine virus genomes and reconstructed poultry transportation data to measure and compare the spatial spread in China of three key subtypes of AIV: H5N1, H7N9, and H5N6. Although it is difficult to disentangle the contribution of confounding factors, such as bird migration and spatial distance, we find evidence that the dissemination of these subtypes among domestic poultry is geographically continuous and likely associated with the intensity of the live poultry trade in China. Using two independent data sources and network analysis methods, we report a regional-scale community structure in China that might explain the spread of AIV subtypes in the country. The identification of this structure has the potential to inform more targeted strategies for the prevention and control of AIV in China.

[1]  G. Gao,et al.  Epidemiology, Evolution, and Pathogenesis of H7N9 Influenza Viruses in Five Epidemic Waves since 2013 in China. , 2017, Trends in microbiology.

[2]  A. Leigh Brown,et al.  Quantifying predictors for the spatial diffusion of avian influenza virus in China , 2017, BMC Evolutionary Biology.

[3]  Hongjie Yu,et al.  Genesis, Evolution and Prevalence of H5N6 Avian Influenza Viruses in China. , 2016, Cell host & microbe.

[4]  Lu Lu,et al.  Role for migratory wild birds in the global spread of avian influenza H5N8 , 2016, Science.

[5]  E. Holmes,et al.  The impact of migratory flyways on the spread of avian influenza virus in North America , 2017, BMC Evolutionary Biology.

[6]  D. Pfeiffer,et al.  Investigating poultry trade patterns to guide avian influenza surveillance and control: a case study in Vietnam , 2016, Scientific Reports.

[7]  Eric J. Ma,et al.  Ecosystem Interactions Underlie the Spread of Avian Influenza A Viruses with Pandemic Potential , 2016, PLoS pathogens.

[8]  Kenth Engø-Monsen,et al.  Impact of human mobility on the emergence of dengue epidemics in Pakistan , 2015, Proceedings of the National Academy of Sciences.

[9]  Yi Guan,et al.  Dissemination, divergence and establishment of H7N9 influenza viruses in China , 2015, Nature.

[10]  Bing Xu,et al.  Spatial, temporal and genetic dynamics of highly pathogenic avian influenza A (H5N1) virus in China , 2015, BMC Infectious Diseases.

[11]  H. Mehlhorn.  World Organization for Animal Health , 2015 .

[12]  Ruifu Yang,et al.  Avian influenza H5N1 viral and bird migration networks in Asia , 2014, Proceedings of the National Academy of Sciences.

[13]  Marius Gilbert,et al.  Risks of Avian Influenza Transmission in Areas of Intensive Free-Ranging Duck Production with Wild Waterfowl , 2014, EcoHealth.

[14]  M. Suchard,et al.  Unifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2 , 2014, PLoS pathogens.

[15]  D. Pfeiffer,et al.  Live Poultry Trade in Southern China Provinces and HPAIV H5N1 Infection in Humans and Poultry: The Role of Chinese New Year Festivities , 2012, PloS one.

[16]  M. Gilbert,et al.  Risk factor modelling of the spatio-temporal patterns of highly pathogenic avian influenza (HPAIV) H5N1: a review. , 2012, Spatial and spatio-temporal epidemiology.

[17]  M. Suchard,et al.  Bayesian Phylogenetics with BEAUti and the BEAST 1.7 , 2012, Molecular biology and evolution.

[18]  Timothy B. Stockwell,et al.  Migratory flyway and geographical distance are barriers to the gene flow of influenza virus among North American birds. , 2012, Ecology letters.

[19]  Ricardo J Soares Magalhães,et al.  Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis , 2011, Preventive Veterinary Medicine.

[20]  M. V. Van Kerkhove,et al.  Highly Pathogenic Avian Influenza (H5N1): Pathways of Exposure at the Animal‐Human Interface, a Systematic Review , 2011, PloS one.

[21]  T. P. van den Berg,et al.  H5N1 High Pathogenicity Avian Influenza Virus Survival in Different Types of Water , 2010, Avian diseases.

[22]  Ricardo J Soares Magalhães,et al.  Associations between attributes of live poultry trade and HPAI H5N1 outbreaks: a descriptive and network analysis study in northern Vietnam , 2010, BMC veterinary research.

[23]  Alexei J. Drummond,et al.  Bayesian Phylogeography Finds Its Roots , 2009, PLoS Comput. Biol..

[24]  Van Kerkhove,et al.  H5N1/highly pathogenic avian influenza in Cambodia : evaluating poultry movement and the extent of interaction between poultry and humans , 2009 .

[25]  Oie,et al.  Toward a Unified Nomenclature System for Highly Pathogenic Avian Influenza Virus (H5N1) , 2008, Emerging infectious diseases.

[26]  M. Suchard,et al.  Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics. , 2008, Molecular biology and evolution.

[27]  L. Fang,et al.  Environmental Factors Contributing to the Spread of H5N1 Avian Influenza in Mainland China , 2008, PloS one.

[28]  Ke Bingsheng,et al.  Poultry sector in China : structural changes during the past decade and future trends , 2008 .

[29]  S. Ho,et al.  Relaxed Phylogenetics and Dating with Confidence , 2006, PLoS biology.

[30]  Y. Guan,et al.  Establishment of multiple sublineages of H5N1 influenza virus in Asia: implications for pandemic control. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[31]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[32]  Alexei J Drummond,et al.  Choosing appropriate substitution models for the phylogenetic analysis of protein-coding sequences. , 2006, Molecular biology and evolution.

[33]  Dennis Normile,et al.  Are Wild Birds to Blame? , 2005, Science.

[34]  Y. Guan,et al.  Genesis of a highly pathogenic and potentially pandemic H5N1 influenza virus in eastern Asia , 2004, Nature.

[35]  R. Webster.  Wet markets—a continuing source of severe acute respiratory syndrome and influenza? , 2004, The Lancet.

[36]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[37]  M. Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[39]  N. Cox,et al.  Genetic characterization of the pathogenic influenza A/Goose/Guangdong/1/96 (H5N1) virus: similarity of its hemagglutinin gene to those of H5N1 viruses from the 1997 outbreaks in Hong Kong. , 1999, Virology.

[40]  W. J. Bean,et al.  Replication of avian influenza A viruses in mammals , 1981, Infection and immunity.