Influenza A Virus Surveillance in Live-Bird Markets: First Report of Influenza A Virus Subtype H4N6, H4N9, and H10N3 in Thailand

Wisedchanwet, Trong; Wongpatcharachai, Manoosak; Boonyapisitsopa, Supanat; Bunpapong, Napawan; Jairak, Waleemas; Kitikoon, Pravina; Sasipreeyajun, Jiroj; Amonsin, Alongkorn

doi:10.1637/9681-020811-reg.1

Cited by 15 publications

(9 citation statements)

References 36 publications

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“…H10 viruses occasionally infect humans. An H10N3 virus was isolated in Hong Kong in 1979 8 , and in a live-bird market in Thailand in 2011 9 . However, pathogenicity in mammals due to H10N3 viruses remains largely unclear.…”

mentioning

confidence: 99%

Characterization of the Pathogenesis of H10N3, H10N7, and H10N8 Subtype Avian Influenza Viruses Circulating in Ducks

Zhang

et al. 2016

Sci Rep

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Three H10 subtype avian influenza viruses were isolated from domestic ducks in China, designated as SH602/H10N8, FJ1761/H10N3 and SX3180/H10N7, with an intravenous pathogenicity index (IVPI) of 0.39, 1.60, and 1.27, respectively. These H10 viruses showed a complex pathology pattern in different species, although full genome characterizations of the viruses could not identify any molecular determinant underlying the observed phenotypes. Our findings describe the pathobiology of the three H10 subtype AIVs in chickens, ducks, and mice. FJ1761/H10N3 evolved E627K and Q591K substitutions in the gene encoding the PB2 protein in infected mice with severe lung damage, suggesting that H10 subtype avian influenza viruses are a potential threat to mammals.

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confidence: 99%

Characterization of the Pathogenesis of H10N3, H10N7, and H10N8 Subtype Avian Influenza Viruses Circulating in Ducks

Zhang

et al. 2016

Sci Rep

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“…This may indicate LBMs play a role in facilitating co-infection, a possibility supported by previous studies in Thailand and China, and one which deserves further investigation [170,171].…”

Section: Discussionsupporting

confidence: 53%

Landscape genetics of avian influenza (H5N1 and H9N2) in Egyptian poultry from 2006-2015

Young¹

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With a case fatality rate higher than the 1918 Spanish Flu pandemic, H5N1 highly pathogenic avian influenza represents a threat to global public health. Efforts to identify locations with the greatest potential for pandemic emergence, as well as how the virus is spreading, may help minimize this threat. First detected in Egypt in 2006, H5N1 viruses have resulted in the deaths of millions of birds in both commercial and backyard poultry flocks, and more than 350 human infections, the most of any country, have been confirmed. Human outbreaks have been so far constrained by poor viral adaptation to non-avian hosts. There are two evolutionary mechanisms by which the H5N1 avian influenza virus could acquire pandemic potential: 1) via reassortment as a result of coinfection with another subtype (such as low pathogenic avian influenza H9N2); and/or 2) via antigenic drift and the accumulation of randomly occurring genetic changes found to improve viral fitness, herein called key substitutions (KS). Both mechanisms were investigated using geospatial methods including ecological niche modeling and hot spot analyses to predict locations with elevated potential for pandemic emergence. Using ecological niche modeling environmental, behavioral, and population characteristics of H5N1 and H9N2 niches within Egypt were identified, with niches differing markedly by subtype. Niche estimates were combined using raster overlay to estimate co-infection potential, with known occurrences used for validation. Co-infection was successfully predicted with high accuracy (area under the receiver operating characteristic (ROC) curve (AUC) 0.991). 41 distinct KS in H5N1 were detected in Egyptian isolates, including 17 not previously reported in Egypt. Phenotypic consequences of detected KS were varied, but the majority have been implicated in improving mammalian host vi adaptation and increasing virulence. Statistically significant spatial clustering of high KS rates was detected in the northwestern portion of the Nile River delta in the governorates of Alexandria and Beheira. To investigate how the virus spreads between poultry farms, landscape genetics techniques were employed. Viral genetic sequences were evaluated using phylogenetics to determine viral relatedness between samples, then distance models representing competing diffusion mechanisms were created using road networks and a least-cost path model designed to approximate wild waterbird travel using niche modeling and circuit theory. Spatial correlations were evaluated using Mantel tests, Mantel correlograms, and multiple regression of distance matrices within causal modeling and relative support frameworks. Samples from backyard farms were most strongly correlated with least cost path distances, implicating wild bird diffusion, while samples from commercial farms were most strongly correlated with road network distances, implicating human-mediated diffusion. Results were largely consistent across gene segments. Identifying areas at risk of co-infection can help target spaces for inc...

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“…Distance to LBM was only a moderate contributor to the single-subtype models, but was the single best predictor for the co-infection model. This may indicate LBMs play a role in facilitating co-infection, a possibility supported by previous studies in Thailand and China, and one which deserves further investigation [ 60 , 61 ].…”

Section: Discussionmentioning

confidence: 62%

Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt

Young

Carrel

Malanson

et al. 2016

IJERPH

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Human outbreaks with avian influenza have been, so far, constrained by poor viral adaptation to non-avian hosts. This could be overcome via co-infection, whereby two strains share genetic material, allowing new hybrid strains to emerge. Identifying areas where co-infection is most likely can help target spaces for increased surveillance. Ecological niche modeling using remotely-sensed data can be used for this purpose. H5N1 and H9N2 influenza subtypes are endemic in Egyptian poultry. From 2006 to 2015, over 20,000 poultry and wild birds were tested at farms and live bird markets. Using ecological niche modeling we identified environmental, behavioral, and population characteristics of H5N1 and H9N2 niches within Egypt. Niches differed markedly by subtype. The subtype niches were combined to model co-infection potential with known occurrences used for validation. The distance to live bird markets was a strong predictor of co-infection. Using only single-subtype influenza outbreaks and publicly available ecological data, we identified areas of co-infection potential with high accuracy (area under the receiver operating characteristic (ROC) curve (AUC) 0.991).

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Influenza A Virus Surveillance in Live-Bird Markets: First Report of Influenza A Virus Subtype H4N6, H4N9, and H10N3 in Thailand

Cited by 15 publications

References 36 publications

Characterization of the Pathogenesis of H10N3, H10N7, and H10N8 Subtype Avian Influenza Viruses Circulating in Ducks

Characterization of the Pathogenesis of H10N3, H10N7, and H10N8 Subtype Avian Influenza Viruses Circulating in Ducks

Landscape genetics of avian influenza (H5N1 and H9N2) in Egyptian poultry from 2006-2015

Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt

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