tetano
Editor, Senior Moderator
Animal
. 2024 Jan 24;18(3):101085.
doi: 10.1016/j.animal.2024.101085. Online ahead of print. Multifaceted analysis of temporal and spatial distribution and risk factors of global poultry HPAI-H5N1, 2005-2023
Yuepeng Li[SUP] 1 [/SUP], Qi An[SUP] 1 [/SUP], Zhuo Sun[SUP] 1 [/SUP], Xiang Gao[SUP] 1 [/SUP], Hongbin Wang[SUP] 2 [/SUP]
Affiliations
The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.
Keywords: HPAI-H5N1; Maximum entropy model; Risk factors; Spatial distribution; Time series decomposition.
. 2024 Jan 24;18(3):101085.
doi: 10.1016/j.animal.2024.101085. Online ahead of print. Multifaceted analysis of temporal and spatial distribution and risk factors of global poultry HPAI-H5N1, 2005-2023
Yuepeng Li[SUP] 1 [/SUP], Qi An[SUP] 1 [/SUP], Zhuo Sun[SUP] 1 [/SUP], Xiang Gao[SUP] 1 [/SUP], Hongbin Wang[SUP] 2 [/SUP]
Affiliations
- PMID: 38364655
- DOI: 10.1016/j.animal.2024.101085
The purpose of this study was to analyze the characteristics of occurrence and spread of highly pathogenic avian influenza H5N1 (HPAI-H5N1) globally, understand its spatiotemporal characteristics, investigate the risk factors influencing outbreaks, and identify high-risk areas for disease occurrence. We collected the data on global poultry HPAI-H5N1 outbreaks from January 2005 to April 2023, and conducted a thorough analysis of the spatial and temporal characteristics of the disease through time series decomposition and directional distribution analysis. Additionally, an ecological niche model was established to explore the major factors influencing the occurrence of HPAI-H5N1 and to pinpoint high-risk areas. Our findings revealed that HPAI-H5N1 outbreaks were cyclical, and seasonal, exhibiting a rising trend, with a predominant northwest-southeast transmission direction. The ecological niche model highlighted that species factors and economic trade factors are critical in influencing the outbreak of HPAI-H5N1. Variables such as chicken and duck density, population density, isothermality, and road density, contributed to importantly risk of outbreaks. High-risk areas for HPAI-H5N1 occurrence were primarily identified in Europe, West Africa, Southeast Asia, and Southeast China. This study provided valuable insights into the spatial and temporal distribution characteristics and risk factors of global poultry HPAI-H5N1 outbreaks. The identification of high-risk areas provides essential information that can be used to develop more effective prevention and control policies.
Keywords: HPAI-H5N1; Maximum entropy model; Risk factors; Spatial distribution; Time series decomposition.