This article was originally published here
About Sci Pollut Res Int. 2022 Feb 6. doi: 10.1007/s11356-022-19016-1. Online ahead of print.
The spread of highly pathogenic avian influenza H5N1 has posed a major threat to global public health. Understanding the spatio-temporal characteristics of outbreaks and the environmental factors of H5N1 outbreaks is of great importance for the establishment of effective prevention and control systems. The time and location of outbreaks of H5N1 in poultry and wild birds officially confirmed by the World Organization for Animal Health from 2005 to 2019 were collected. Spatial autocorrelation analysis and multi-distance spatial agglomeration analysis methods were used to analyze global H5N1 outbreak sites. Combined with remote sensing data, the correlation between H5N1 outbreaks and environmental factors was analyzed using binary logistic regression methods. We analyzed the correlation between the H5N1 epidemic and environmental factors and finally made a risk prediction for global H5N1 epidemics. The results show that the peak of H5N1 epidemics occurs in winter and spring. The H5N1 foci present an aggregation, and a weak aggregation phenomenon is noted at the scale close to 5000 km. Water distance, road distance, railway distance, wind speed, leaf area index (LAI) and specific humidity were protective factors for H5N1 outbreak , and the odds ratio (OR) was 0.985, 0.989, 0.995, 0.717, 0.832, and 0.935, respectively. Temperature was a risk factor with an OR of 1.073. The significance of these ORs was greater than 95%. The global risk prediction map was obtained. Since the novel coronavirus (COVID-19) is spreading globally, the methods and results of this study can provide a benchmark for studying the spread of COVID-19.
PMID:35128608 | DOI:10.1007/s11356-022-19016-1