Quantitative risk assessment of avian influenza: A scoping review
Open Access
- 1 December 2026
- journal article
- review article
- Published by KEAI Publishing in Infectious Disease Modelling
- Vol. 11 (4) , 1583-1609
Abstract
Avian influenza virus (AIV) continues to pose serious risks to animal and public health. Understanding its spread requires integrating ecological, agricultural, and human information. Quantitative models provide a practical way to represent these interactions, evaluate multiple risk factors, and generate spatial insights that support early detection and control. In recent years, advances in data availability and computational methods have increased the use of these models for AIV risk assessment.Keywords
Funding Information
- Canadian Poultry Research Council
- Ministry of Agriculture, Food and Agribusiness
This publication has 69 references indexed in Scilit:
- Leveraging social media and google trends to identify waves of avian influenza outbreaks in USA and CanadaExpert Systems with Applications, 2025
- Exploring Zika's dynamics: A scoping review journey from epidemic to equations through mathematical modellingInfectious Disease Modelling, 2025
- Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemicInfectious Disease Modelling, 2025
- Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical reviewInfectious Disease Modelling, 2025
- Mathematical modeling of contact tracing and stability analysis to inform its impact on disease outbreaks; an application to COVID-19Infectious Disease Modelling, 2024
- Multifaceted analysis of temporal and spatial distribution and risk factors of global poultry HPAI-H5N1, 2005–2023Animal, 2024
- Waterfowl show spatiotemporal trends in influenza A H5 and H7 infections but limited taxonomic variationEcological Applications, 2023
- Environmental factors and spatiotemporal distribution characteristics of the global outbreaks of the highly pathogenic avian influenza H5N1Environmental Science and Pollution Research, 2022
- Bayesian Networks in Environmental Risk Assessment: A ReviewIntegrated Environmental Assessment and Management, 2020
- Maximum entropy modeling of species geographic distributionsEcological Modelling, 2006