Fang Kang, Ni Xiansheng, Wang Xi, Song Wentao, Deng Zhiqiang, Zhao Zeyu, Hua Wei, Zeng Zhizhong, Wang Wei, Si Qianqian, Wu Jiang, Zhang Bo, Zhang Ping, Li Hui, Chen Tianmu
State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen 361102, China.
Nanchang Center for Disease Control and Prevention, Nanchang City, Jiangxi Province, People's Republic of China.
One Health. 2025 Apr 21;20:101047. doi: 10.1016/j.onehlt.2025.101047. eCollection 2025 Jun.
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.
最近，禽流感的流行病学特征在全球范围内发生了巨大变化。自2017年以来，对鄱阳湖西南地区最大的城市南昌的批发和零售市场进行了禽流感采样和监测。从时间、亚型变化、季节性和气象因素等多个维度对该地区禽流感的传播模式进行了综合评估。使用实时逆转录聚合酶链反应检测禽流感A病毒核酸样本，并对阳性结果进行分型。采用小波相干分析揭示与禽流感相关的气象因素的时频变化。利用随机森林算法对气象因素进行多因素分析。结果显示，禽流感阳性率最高为42.29%（95%CI：41.18-43.41），出现在夏季。发现气象因素与禽流感阳性率在一定周期内显著相关。随机森林分析显示气象因素与不同禽流感亚型阳性率变化之间存在显著异质性。污染浓度显著影响不同禽流感亚型的阳性率。温度对H5和H9亚型阳性率的影响模式与非H5/H7/H9阳性率相反。冬季，H5和H9亚型的阳性率较低，非H5/H7/H9样本的阳性率较高；春季则相反。污染物浓度与禽流感阳性率之间存在相关性。当局在禽流感防控中应考虑气候条件和污染物水平，并根据不同亚型的特点采取不同的防控措施。我们建议继续对该地区的禽流感进行监测，并采用“同一健康”方法进行综合防控。
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