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Int J Infect Dis . Spatial and temporal analysis of human infection with the avian influenza A (H7N9) virus in China and research on risk assessment agent-based model

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  • Int J Infect Dis . Spatial and temporal analysis of human infection with the avian influenza A (H7N9) virus in China and research on risk assessment agent-based model


    Int J Infect Dis


    . 2021 Apr 12;S1201-9712(21)00341-6.
    doi: 10.1016/j.ijid.2021.04.030. Online ahead of print.
    Spatial and temporal analysis of human infection with the avian influenza A (H7N9) virus in China and research on risk assessment agent-based model


    Dongqing Huang 1 , Wen Dong 2 , Qian Wang 3



    Affiliations

    Abstract

    Objectives: From 2013 to 2017, human infection with avian influenza A (H7N9) virus frequently occurred in China, which seriously affected the public health of society. The purpose of this study is to analyze the spatial characteristics of human infection with avian influenza A (H7N9) virus in China and assess the risk area of the epidemic.
    Methods: Using kernel density estimation, standard deviation ellipse analysis, spatial and temporal scanning cluster analysis, and Pearson correlation analysis, we studied the spatial characteristics and possible risk factors of the epidemic. We also combined meteorological factors, time (month), and environmental factors to establish an epidemic risk assessment proxy model to assess the risk range of an epidemic.
    Results: The epidemic situation is significantly correlated with atmospheric pressure, temperature, and daily precipitation (P < 0.05), and there are six temporal and spatial clusters. The fitting accuracy of the epidemic risk assessment agent-based model for lower-risk, low-risk, medium-risk, and high-risk is 0.795, 0.672, 0.853, 0.825, respectively.
    Conclusions: In winter and spring, this epidemic is easy to break out. And gradually spread to the inland areas of China. Our model can well reflect the risk area of human infection with avian influenza A (H7N9) virus.

    Keywords: Agent-based model; Avian influenza; GIS; H7N9; MLP.

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