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Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds

Authors
Yoo, Dae-SungLee, KyuyoungBeatriz, Martinez LopezChun, Byung ChulBelkhiria, JaberLee, Kwang-Nyeong
Issue Date
7월-2022
Publisher
WILEY
Keywords
avian influenza; habitat suitability model; highly pathogenic avian influenza; poultry; spatialtemporal risk model; species distribution model; wild birds
Citation
TRANSBOUNDARY AND EMERGING DISEASES, v.69, no.4, pp.e953 - e967
Indexed
SCIE
SCOPUS
Journal Title
TRANSBOUNDARY AND EMERGING DISEASES
Volume
69
Number
4
Start Page
e953
End Page
e967
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/138497
DOI
10.1111/tbed.14376
ISSN
1865-1674
Abstract
Highly pathogenic avian influenza (HPAI) has predominantly damaged the poultry industry worldwide. The fundamental prevention and control strategy for HPAI includes early detection and timely intervention enforcement through a systematic surveillance system for wild birds based on the ecological understanding of the dynamics of wild birds' movements. Our study aimed to develop a spatiotemporal risk assessment model for avian influenza (AI) infection in wild birds to empower surveillance information for a contingency strategy. For this purpose, first, we predicted the monthly habitat suitability of seven waterfowl species, using 227,671 Global Positioning System (GPS) tracking records of 562 birds from 2014 to 2018 in the Republic of Korea (ROK). Then, that predicted habitat suitability and 421 coordinates of AI detection sites in wild birds were used to build the risk assessment model. Subsequently, we compared the monthly predicted risk of avian influenza virus (AIv) identification in wild birds between case and non-case poultry farms with HPAI H5N6 outbreak in the ROK between 2016 and 2017. The results reported considerable variation of monthly habitat suitability of seven waterfowls and the impact of predicting AI occurrences in wild birds. The high habitat suitability for spot-billed ducks (contribution rate in November = 40.9%) and mallards (contribution rate in January = 34.3%) significantly contributed to predicting the average risk of AIv identification in wild birds, with high predictive performance [the monthly mean of area under the curve (AUC) = 0.978]. Moreover, our model showed that the averaged risk of identification AI in wild birds was significantly higher in HPAI infected premises, with infected domestic duck holdings exhibiting a significantly higher risk than the chicken farms in November. This study suggests that animal health authority establishes a risk-based HPAI surveillance system grounded on the ecological nature of wild birds to improve the effectiveness of prevention and preparedness of emerging epidemics.
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