ArticleEnvironmental science and pollution research international2022
Environmental factors and spatiotemporal distribution characteristics of the global outbreaks of the highly pathogenic avian influenza H5N1.
Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Quantitative risk assessment of avian influenza: A scoping review.Infectious Disease Modelling · 2026Review
- Evaluating transient risk factors for avian influenza outbreaks in Canada using case-crossover study and machine learning.Poultry science · 2026Article
- Optimizing wild bird fecal surveillance sites for HPAI through risk estimation using machine learning algorithms.One health (Amsterdam, Netherlands) · 2026Article
- Machine Learning-Based Geospatial Risk Modeling of Global Avian Influenza Outbreaks.Transboundary and emerging diseases · 2026Article
- Avian influenza and One Health: bridging animal and human health through integrated surveillance and vaccination.Frontiers in cellular and infection microbiology · 2026Review
- Transboundary Spread and Ecological Drivers of HPAI H5N1 Clade 2.3.4.4b During the 2022-2023 Outbreak in Chile: An Integrated Genomic and Spatial Epidemiology Framework.Transboundary and emerging diseases · 2026Article
- Investigating environmental determinants and spatiotemporal dynamics of highly pathogenic avian influenza H5N1 outbreaks in India through machine learning.Scientific reports · 2025Article
- A Review of Avian Influenza Virus Exposure Patterns and Risks Among Occupational Populations.Veterinary sciences · 2025Review
- Making sense of the virome in light of evolution and ecology.Proceedings. Biological sciences · 2025Review
- A single immunization with H5N1 virus-like particle vaccine protects chickens against divergent H5N1 influenza viruses and vaccine efficacy is determined by adjuvant and dosage.Emerging microbes & infections · 2024Article
- Avian Influenza: Lessons from Past Outbreaks and an Inventory of Data Sources, Mathematical and AI Models, and Early Warning Systems for Forecasting and Hotspot Detection to Tackle Ongoing Outbreaks.Healthcare (Basel, Switzerland) · 2024Review
- Risk distribution of human infections with avian influenza A (H5N1, H5N6, H9N2 and H7N9) viruses in China.Frontiers in public health · 2024Article
- Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control.Transboundary and emerging diseases · 2024Article
- Spatial and Temporal Characteristic Analysis and Risk Assessment of Global Highly Pathogenic Avian Influenza H5N8 Subtype.Transboundary and emerging diseases · 2024Article
- Potential risk zones and climatic factors influencing the occurrence and persistence of avian influenza viruses in the environment of live bird markets in Bangladesh.One health (Amsterdam, Netherlands) · 2023Article
- The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh.One health (Amsterdam, Netherlands) · 2023Article
- Potential cross-species transmission of highly pathogenic avian influenza H5 subtype (HPAI H5) viruses to humans calls for the development of H5-specific and universal influenza vaccines.Cell discovery · 2023Review
- Investigation of risk factors for introduction of highly pathogenic avian influenza H5N1 infection among commercial turkey operations in the United States, 2022: a case-control study.Frontiers in veterinary science · 2023Article
- Bioengineering Outlook on Cultivated Meat Production.Micromachines · 2022Review
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6 authors.
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Abstract
The spread of highly pathogenic avian influenza H5N1 has posed a major threat to global public health. Understanding the spatiotemporal outbreak characteristics and environmental factors of H5N1 outbreaks is of great significance for the establishment of effective prevention and control systems. The time and location of H5N1 outbreaks in poultry and wild birds officially confirmed by the World Organization for Animal Health from 2005 to 2019 were collected. Spatial autocorrelation analysis and multidistance spatial agglomeration analysis methods were used to analyze the global outbreak sites of H5N1. 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 outbreak and environmental factors and finally made a risk prediction for the global H5N1 outbreaks. The results show that the peak of the H5N1 outbreaks occurs in winter and spring. H5N1 outbreaks exhibit aggregation, and a weak aggregation phenomenon is noted on 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 the outbreak of H5N1, and the odds ratio (OR) were 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. Given that the novel coronavirus (COVID-19) is spreading globally, the methods and results of this study can provide a reference for studying the spread of COVID-19.
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