Influenza A H5N1 and H7N9 in China: A spatial risk analysis

被引:10
|
作者
Bui, Chau Minh [1 ]
Gardner, Lauren [2 ]
Macintyre, Raina [1 ,3 ]
Sarkar, Sahotra [4 ,5 ]
机构
[1] Univ New South Wales, Sch Publ Hlth & Community Med, Sydney, NSW, Australia
[2] Univ New South Wales, Sch Civil & Environm Engn, Sydney, NSW, Australia
[3] Arizona State Univ, Coll Publ Serv & Community Solut, Phoenix, AZ USA
[4] Univ Texas Austin, Dept Philosophy, Austin, TX 78712 USA
[5] Univ Texas Austin, Dept Integrat Biol, Austin, TX 78712 USA
来源
PLOS ONE | 2017年 / 12卷 / 04期
基金
英国医学研究理事会;
关键词
LIVE-POULTRY MARKETS; AVIAN INFLUENZA; HUMAN INFECTION; A(H7N9) VIRUS; SAMPLE-SIZE; WILD BIRDS; SPREAD; TRANSMISSION; CLOSURE; EPIDEMIC;
D O I
10.1371/journal.pone.0174980
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Zoonotic avian influenza poses a major risk to China, and other parts of the world. H5N1 has remained endemic in China and globally for nearly two decades, and in 2013, a novel zoonotic influenza A subtype H7N9 emerged in China. This study aimed to improve upon our current understanding of the spreading mechanisms of H7N9 and H5N1 by generating spatial risk profiles for each of the two virus subtypes across mainland China. Methods and findings In this study, we (i) developed a refined data set of H5N1 and H7N9 locations with consideration of animal/animal environment case data, as well as spatial accuracy and precision; (ii) used this data set along with environmental variables to build species distribution models (SDMs) for each virus subtype in high resolution spatial units of 1km(2) cells using Maxent; (iii) developed a risk modelling framework which integrated the results from the SDMs with human and chicken population variables, which was done to quantify the risk of zoonotic transmission; and (iv) identified areas at high risk of H5N1 and H7N9 transmission. We produced high performing SDMs (6 of 8 models with AUC > 0.9) for both H5N1 and H7N9. In all our SDMs, H7N9 consistently showed higher AUC results compared to H5N1, suggesting H7N9 suitability could be better explained by environmental variables. For both subtypes, high risk areas were primarily located in south-eastern China, with H5N1 distributions found to be more diffuse and extending more inland compared to H7N9. Conclusions We provide projections of our risk models to public health policy makers so that specific high risk areas can be targeted for control measures. We recommend comparing H5N1 and H7N9 prevalence rates and survivability in the natural environment to better understand the role of animal and environmental transmission in human infections.
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页数:28
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