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Risk distribution of humaninfections with avian influenza A (H5N1, H5N6, H9N2 and H7N9) viruses in China

Avian influenza A viruses; distribution; boosted regression tree model

Risk distribution of human infections with avian influenza A (H5N1, H5N6, H9N2 and H7N9)

viruses in China

Rongrong Qu¹ , Mengsha Chen¹ , Can Chen¹ , Kexin Cao¹ , Xiaoyue Wu¹ , Wenkai Zhou¹, Jiaxing Qi¹, Jiani Miao¹, Dong Yan^2 * and Shigui Yang<sup>1 * 



1</sup> Department of Emergency Medicine, Second Affiliated Hospital, Department of Epidemiology and Biostatistics, School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China,

² State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

 

Background: This study aimed to investigate epidemiologic characteristics of major human infection with avian influenza and explore the factors underlying the spatial distributions, particularly H5N6 and H9N2, as H9N2 could directly infect mankind and contribute partial or even whole internal genes to generate novel human-lethal reassortants such as H5N6. They pose potential threats to public health and agriculture.

Methods: This study collected cases of H5N1, H5N6, H9N2, and H7N9 in China, along with data on ecoclimatic, environmental, social and demographic factors at the provincial level. Boosted regression tree (BRT) models, a popular approach to ecological studies, has been commonly used for risk mapping of infectious diseases, therefore, it was used to investigate the association between these variables and the occurrence of human cases for each subtype, as well as to map the probabilities of human infections.

Results: A total of 1,123 H5N1, H5N6, H9N2, and H7N9 human cases have been collected in China from 2011 to 2024. Factors including density of pig and density of human population emerged as common significant predictors for H5N1 (relative contributions: 5.3, 5.8%), H5N6 (10.8, 6.4%), H9N2 (11.2, 7.3%), and H7N9 (9.4, 8.0%) infection. Overall, each virus has its own ecological and

social drivers. The predicted distribution probabilities for H5N1, H5N6, H9N2, and H7N9 presence are highest in Guangxi, Sichuan, Guangdong, and Jiangsu, respectively, with values of 0.86, 0.96, 0.93 and 0.99.

Conclusion: This study highlighted the important role of social and demographic factors in the infection of different avian influenza, and suggested that monitoring and control of predicted high-risk areas should be prioritized.



Keywords

Avian influenza A viruses; distribution; boosted regression tree model