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Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds.
Yoo, Dae-Sung; Lee, Kyuyoung; Beatriz, Martínez López; Chun, Byung Chul; Belkhiria, Jaber; Lee, Kwang-Nyeong.
Afiliação
  • Yoo DS; Department of Public Health, Graduate School, Korea University, Seoul, Republic of Korea.
  • Lee K; Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California, USA.
  • Beatriz ML; Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California, USA.
  • Chun BC; Department of Public Health, College of Medicine, Korea University, Seoul, Republic of Korea.
  • Belkhiria J; One Health Institute, School of Veterinary Medicine, University of California, Davis, California, USA.
  • Lee KN; Department of Public Health, Graduate School, Korea University, Seoul, Republic of Korea.
Transbound Emerg Dis ; 69(4): e953-e967, 2022 Jul.
Article em En | MEDLINE | ID: mdl-34738338
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vírus da Influenza A / Influenza Aviária Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Animals Idioma: En Revista: Transbound Emerg Dis Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vírus da Influenza A / Influenza Aviária Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Animals Idioma: En Revista: Transbound Emerg Dis Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2022 Tipo de documento: Article