Risk analysis for the highly pathogenic avian influenza in China's mainland using meta-modeling

被引:1
作者
CAO ChunXiang1
2 Beijing Institute of Microbiology and Epidemiology
3 Graduate University of the Chinese Academy of Sciences
机构
基金
中国国家自然科学基金;
关键词
highly pathogenic avian influenza; meta-modeling; remote sensing; geographical information system; Bayesian maximum entropy; logistic regression; spatiotemporal autocorrelation;
D O I
暂无
中图分类号
S855.3 [病毒病];
学科分类号
0906 ;
摘要
A logistic model was employed to correlate the outbreak of highly pathogenic avian influenza (HPAI) with related environmental factors and the migration of birds. Based on MODIS data of the normalized difference vegetation index, environmental factors were considered in generating a probability map with the aid of logistic regression. A Bayesian maximum entropy model was employed to explore the spatial and temporal correlations of HPAI incidence. The results show that proximity to water bodies and national highways was statistically relevant to the occurrence of HPAI. Migratory birds, mainly waterfowl, were important infection sources in HPAI transmission. In addition, the HPAI outbreaks had high spatiotemporal autocorrelation. This epidemic spatial range fluctuated 45 km owing to different distribution patterns of cities and water bodies. Furthermore, two outbreaks were likely to occur with a period of 22 d. The potential risk of occurrence of HPAI in China’s mainland for the period from January 23 to February 17, 2004 was simulated based on these findings, providing a useful meta-model framework for the application of environmental factors in the prediction of HPAI risk.
引用
收藏
页码:4169 / 4179
页数:11
相关论文
共 50 条
  • [31] Estimating population sensitivity and confidence of freedom from highly pathogenic avian influenza in the Victorian poultry industry using passive surveillance
    Sergeant, Evan S. G.
    Dries, Leanna R.
    Moore, Karen M.
    Salmon, Sally E.
    PREVENTIVE VETERINARY MEDICINE, 2022, 202
  • [32] Biosecurity risk factors for highly pathogenic avian influenza (H5N8) virus infection in duck farms, France
    Guinat, Claire
    Comin, Arianna
    Kratzer, Gilles
    Durand, Benoit
    Delesalle, Lea
    Delpont, Mattias
    Guerin, Jean-Luc
    Paul, Mathilde C.
    TRANSBOUNDARY AND EMERGING DISEASES, 2020, 67 (06) : 2961 - 2970
  • [33] Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand
    Thanapongtharm, Weerapong
    Van Boeckel, Thomas P.
    Biradar, Chandrashekhar
    Xiao, Xiangming
    Gilbert, Marius
    GEOSPATIAL HEALTH, 2013, 8 (01) : 193 - 201
  • [34] Phylogeographic analysis of H5N1 highly pathogenic avian influenza virus isolated in Cambodia from 2018 to 2019
    Park, Yu-Ri
    Lee, Yu-Na
    Lee, Dong-Hun
    Si, Young-Jae
    Baek, Yoon-Gi
    Bunnary, Seng
    Theary, Ren
    Tum, Sothyra
    Kye, Soo-Jeong
    Lee, Myoung-Heon
    Park, Choi-Kyu
    Lee, Youn-Jeong
    INFECTION GENETICS AND EVOLUTION, 2020, 86
  • [35] Characterization of the amantadine-resistant H5N1 highly pathogenic avian influenza variants isolated from quails in Southern China
    Guoying Dong
    Jing Luo
    Kai Zhou
    Bin Wu
    Chao Peng
    Guangju Ji
    Hongxuan He
    Virus Genes, 2014, 49 : 223 - 232
  • [36] Characterization of the amantadine-resistant H5N1 highly pathogenic avian influenza variants isolated from quails in Southern China
    Dong, Guoying
    Luo, Jing
    Zhou, Kai
    Wu, Bin
    Peng, Chao
    Ji, Guangju
    He, Hongxuan
    VIRUS GENES, 2014, 49 (02) : 223 - 232
  • [37] Risk Prediction of Three Different Subtypes of Highly Pathogenic Avian Influenza Outbreaks in Poultry Farms: Based on Spatial Characteristics of Infected Premises in South Korea
    Yoo, Dae-sung
    Chun, Byung Chul
    Hong, Kwan
    Kim, Jeehyun
    FRONTIERS IN VETERINARY SCIENCE, 2022, 9
  • [38] Highly pathogenic avian influenza H5N8 in south-west France 2016-2017: A modeling study of control strategies
    Andronico, Alessio
    Courcoul, Aurelie
    Bronner, Anne
    Scoizec, Axelle
    Lebouquin-Leneveu, Sophie
    Guinat, Claire
    Paul, Mathilde C.
    Durand, Benoit
    Cauchemez, Simon
    EPIDEMICS, 2019, 28
  • [39] Molecular Epidemiological Analysis of the Transboundary Transmission of 2003 Highly Pathogenic Avian Influenza H7N7 Outbreaks Between The Netherlands and Belgium
    Van Borm, S.
    Jonges, M.
    Lambrecht, B.
    Koch, G.
    Houdart, P.
    van den Berg, T.
    TRANSBOUNDARY AND EMERGING DISEASES, 2014, 61 (01) : 86 - 90
  • [40] Spatio-Temporal Occurrence Modeling of Highly Pathogenic Avian Influenza Subtype H5N1: A Case Study in the Red River Delta, Vietnam
    Tran, Chinh C.
    Yost, Russell S.
    Yanagida, John F.
    Saksena, Sumeet
    Fox, Jefferson
    Sultana, Nargis
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2013, 2 (04) : 1106 - 1121