ArticlePloS one2018
Identification of high risk areas for avian influenza outbreaks in California using disease distribution models.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United States: Descriptive Study.JMIR public health and surveillance · 2026Article
- Molecular surveillance and predictive risk modelling of avian influenza virus in wild birds in Egypt.The Journal of general virology · 2026Article
- The influence, promise, and potential perils of artificial intelligence in veterinary medicine: a call for improved awareness and literacy.Journal of veterinary internal medicine · 2026Article
- Ecology and environment predict spatially stratified risk of H5 highly pathogenic avian influenza clade 2.3.4.4b in wild birds across Europe.Scientific reports · 2025Article
- Risk Assessment of Avian Influenza Virus Subtype H7 Introduction and Spread in the Russian Federation.Pathogens (Basel, Switzerland) · 2025Article
- Multiscale environmental drivers of human brucellosis transmission in Xinjiang: A spatiotemporal analysis integrating GAM and MaxEnt modeling (2015-2023).PLoS neglected tropical diseases · 2025Article
- Predictiveness and drivers of highly pathogenic avian influenza outbreaks in Europe.Scientific reports · 2025Article
- Environmental Suitability of Kazakhstan to Highly Pathogenic Avian Influenza Using Data on Eurasian Outbreaks, 2020-2024.Viruses · 2025Article
- Prediction models show differences in highly pathogenic avian influenza outbreaks in Japan and South Korea compared to Europe.Scientific reports · 2025Article
- Risk for Waterborne Transmission and Environmental Persistence of Avian Influenza Virus in a Wildlife/Domestic Interface in Mexico.Food and environmental virology · 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 of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models.Ecology and evolution · 2024Article
- Using an adaptive modeling framework to identify avian influenza spillover risk at the wild-domestic interface.Scientific reports · 2024Article
- Risk factors for avian influenza in Danish poultry and wild birds during the epidemic from June 2020 to May 2021.Frontiers in veterinary science · 2024Article
- Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula.Transboundary and emerging diseases · 2024Article
- Identification of Pre-Emptive Biosecurity Zone Areas for Highly Pathogenic Avian Influenza Based on Machine Learning-Driven Risk Analysis.Animals : an open access journal from MDPI · 2023Article
- Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.Scientific reports · 2023Article
- Machine learning to predict risk for community-onset Staphylococcus aureus infections in children living in southeastern United States.PloS one · 2023Article
- Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape.Transboundary and emerging diseases · 2022Article
- Wild Bird Densities and Landscape Variables Predict Spatial Patterns in HPAI Outbreak Risk across The Netherlands.Pathogens (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
The coexistence of different types of poultry operations such as free range and backyard flocks, large commercial indoor farms and live bird markets, as well as the presence of many areas where wild and domestic birds co-exist, make California susceptible to avian influenza outbreaks. The 2014-2015 highly pathogenic Avian Influenza (HPAI) outbreaks affecting California and other states in the United States have underscored the need for solutions to protect the US poultry industry against this devastating disease. We applied disease distribution models to predict where Avian influenza is likely to occur and the risk for HPAI outbreaks is highest. We used observations on the presence of Low Pathogenic Avian influenza virus (LPAI) in waterfowl or water samples at 355 locations throughout the state and environmental variables relevant to the disease epidemiology. We used two algorithms, Random Forest and MaxEnt, and two data-sets Presence-Background and Presence-Absence data. The models performed well (AUCc > 0.7 for testing data), particularly those using Presence-Background data (AUCc > 0.85). Spatial predictions were similar between algorithms, but there were large differences between the predictions with Presence-Absence and Presence-Background data. Overall, predictors that contributed most to the models included land cover, distance to coast, and broiler farm density. Models successfully identified several counties as high-to-intermediate risk out of the 8 counties with observed outbreaks during the 2014-2015 HPAI epizootics. This study provides further insights into the spatial epidemiology of AI in California, and the high spatial resolution maps may be useful to guide risk-based surveillance and outreach efforts.
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