ArticleOne health (Amsterdam, Netherlands)2025
Detection and prevalence of avian influenza epidemic in the southwest of Poyang Lake and analysis of the influence of meteorological factors.
Article in One health (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Integrated region-specific modeling of H5 avian influenza in Asia using ENSO-based forecasts.One health (Amsterdam, Netherlands) · 2026Article
- Comparative and predictive analysis of avian influenza in live bird markets of the Poyang Lake region: a long-term monitoring study.Virology journal · 2026Article
- Assessing HPAI-H5 transmission risk across wild bird migratory flyways in the United States.Nature communications · 2026Article
- Molecular epidemiological characteristics of H9N2 subtype avian influenza virus in the external environment of western Zhejiang, China, 2014-2025.Frontiers in public health · 2026Article
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15 authors.
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Abstract
Recently, the epidemiological profile of avian influenza has changed dramatically worldwide. Avian influenza sampling and surveillance of wholesale and retail markets in Nanchang, the largest city in the southwestern region of Poyang Lake, have been conducted since 2017. The transmission pattern of avian influenza in this region was comprehensively evaluated in multiple dimensions including time, subtype changes, seasonality and meteorological factors. Samples were tested for avian influenza A virus nucleic acids using real-time reverse transcription polymerase chain reaction, and positive results were typed. Wavelet coherence analysis was used to reveal the time-frequency variation in meteorological factors associated with avian influenza. The random forest algorithm was used to perform a multifactorial analysis of meteorological factors. Results revealed that the highest avian influenza positivity rate of 42.29 % (95 % CI: 41.18-43.41) occurred in summer. Meteorological factors were found to be significantly associated with the avian influenza positivity rate on a periodic basis. Random forest analysis revealed significant heterogeneity between meteorological factors and changes in the positivity rates of different avian influenza subtypes. Pollution concentration significantly affected the positivity rate of different avian influenza subtypes. The effect of temperature on the positivity rate of the H5 and H9 subtypes followed the opposite pattern to that of the non-H5/H7/H9 positivity rate. In winter, positivity rates of the H5 and H9 subtypes were lower and those of the non-H5/H7/H9 samples were higher; the opposite was true in spring. There is a correlation between pollutant concentration and avian influenza positivity rate. Authorities should consider climatic conditions and the level of contaminants in the prevention and control of avian influenza and adopt different preventive and control measures according to the characteristics of the different subtypes. We recommend continued surveillance of avian influenza in the region and the adoption of a 'one-health' approach for integrated prevention and control.
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