Background <p>Avian influenza, a significant threat to public health, requires monitoring for the development of control strategies. This study aims to analyze the spatiotemporal distribution of avian influenza virus in the external environment of Xinjiang from 2021 to 2023, to enhance understanding of its transmission patterns and provide a scientific basis for public health response measures.</p> Methods <p>A total of 3913 avian-related environmental samples were collected from nine monitoring areas in Xinjiang. Sample types included poultry drinking water, meat cutting boards, cage surfaces, feces, and wastewater. Real-time RT-PCR was used to detect nucleic acid for H5, H7, and H9 subtypes. Data were statistically analyzed using Excel and SPSS, and spatial distribution was visualized through Kriging interpolation using ArcGIS.</p> Results <p>Among the collected samples, 810 tested positive, with an overall positivity rate of 20.70%. The H9 subtype was predominant, accounting for 85.43% of positive samples. Significant differences in detection rates were observed across different years, regions, sample types, and monitoring sites. Temporally, the positive rate showed an upward trend from 2021 to 2023, with higher positive rates in January and July. Geographically, Aksu, Turpan, and Ili were identified as high-risk areas. Urban and rural live poultry markets had the highest positivity rate (24.31%), and poultry drinking water, cage surfaces, and cleaning wastewater samples showed relatively high detection rates. Kriging analysis revealed several high-risk zones for virus presence.</p> Conclusion <p>This study provides crucial information for understanding the epidemiological characteristics of avian influenza virus in the external environment of Xinjiang. The H9 subtype was found to be predominant, with notable seasonal and regional variations. Live poultry markets were identified as key risk sites. These findings underscore the need for continuous surveillance and offer theoretical support for developing targeted prevention and control strategies. However, the limited scope of monitoring suggests that broader and longer-term studies are needed to better understand subtype interactions and epidemic risks.</p>

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Environmental monitoring and spatiotemporal trend analysis of avian influenza virus in Xinjiang, 2021-2023

  • Zhe Yin,
  • Fuerhati Wushouer,
  • Jia Huang,
  • Yan Dong,
  • Qi Wang,
  • Xiapikatijiang Aihaiti,
  • Xiayidanmu Abudusaimaiti,
  • Yuanyuan Ma,
  • Zihan Chen,
  • Ruiying Qiu,
  • Quanxi Li,
  • Zhenguo Gao

摘要

Background

Avian influenza, a significant threat to public health, requires monitoring for the development of control strategies. This study aims to analyze the spatiotemporal distribution of avian influenza virus in the external environment of Xinjiang from 2021 to 2023, to enhance understanding of its transmission patterns and provide a scientific basis for public health response measures.

Methods

A total of 3913 avian-related environmental samples were collected from nine monitoring areas in Xinjiang. Sample types included poultry drinking water, meat cutting boards, cage surfaces, feces, and wastewater. Real-time RT-PCR was used to detect nucleic acid for H5, H7, and H9 subtypes. Data were statistically analyzed using Excel and SPSS, and spatial distribution was visualized through Kriging interpolation using ArcGIS.

Results

Among the collected samples, 810 tested positive, with an overall positivity rate of 20.70%. The H9 subtype was predominant, accounting for 85.43% of positive samples. Significant differences in detection rates were observed across different years, regions, sample types, and monitoring sites. Temporally, the positive rate showed an upward trend from 2021 to 2023, with higher positive rates in January and July. Geographically, Aksu, Turpan, and Ili were identified as high-risk areas. Urban and rural live poultry markets had the highest positivity rate (24.31%), and poultry drinking water, cage surfaces, and cleaning wastewater samples showed relatively high detection rates. Kriging analysis revealed several high-risk zones for virus presence.

Conclusion

This study provides crucial information for understanding the epidemiological characteristics of avian influenza virus in the external environment of Xinjiang. The H9 subtype was found to be predominant, with notable seasonal and regional variations. Live poultry markets were identified as key risk sites. These findings underscore the need for continuous surveillance and offer theoretical support for developing targeted prevention and control strategies. However, the limited scope of monitoring suggests that broader and longer-term studies are needed to better understand subtype interactions and epidemic risks.