Environmental circulation of multiple avian influenza subtypes and potential association with human infections in central China.

Avian influenza viruses (AIVs) continue to circulate in live poultry markets (LPMs), posing potential risks for zoonotic exposure. This study investigated the environmental circulation of AIVs and their potential epidemiological associations with human infection in Henan Province, China.

We analyzed 7,956 environmental samples collected from poultry-associated settings in Henan Province between 2020 and 2025. Multivariable logistic regression was used to identify factors associated with AIV detection. Serological surveillance was conducted among occupationally exposed individuals, and phylogenetic analyses were performed to characterize the genetic relationships between human-derived and environmental AIVs.

A total of 1,460 samples (18.35%) tested positive for AIVs. LPMs were significantly associated with higher odds of AIV detection (OR = 7.211, 95% CI: 5.039-10.319, P < 0.001), and the odds of AIV detection increased over the surveillance period (OR = 1.254, 95% CI: 1.210-1.301, P < 0.001). Multiple AIV subtypes were detected, with H9N2 remaining predominant throughout the study period. Five human infections were identified, including H5N6 and H3N8 infections in 2022 and three H9N2 infections in 2025. Serological surveillance identified H9N2-seropositive and H3N8-reactive samples among occupationally exposed individuals. Phylogenetic analyses revealed genetic similarities between human-derived and environmental viruses. Three H3N8 viruses, including one isolated from a human case, formed a distinct phylogenetic cluster, with their internal genes closely related to co-circulating H9N2 viruses.

These findings demonstrate sustained circulation of multiple AIV subtypes in poultry-associated environments and highlight the importance of integrated environmental and human surveillance for the early detection of viruses with zoonotic potential.
Chronic respiratory disease
Advocacy

Authors

Wu Wu, Zhao Zhao, Nie Nie, Liu Liu, Bo Bo, Luo Luo, Song Song, Zhu Zhu, Zhang Zhang, Mu Mu, Wei Wei, Pan Pan, Wang Wang, Ye Ye, Diao Diao, Ma Ma
View on Pubmed
Share
Facebook
X (Twitter)
Bluesky
Linkedin
Copy to clipboard